A teaching-playback robot manipulator system whereby the user controls the manipulator through a teaching pendant has been used widely in industrial applications. Kinematic singularity issue becomes an important problem in the control of robot with a teaching-playback system. In this paper, we propose and investigate three singularity avoidance methods for a teaching-playback robot manipulator system. Nonredundancy singularity avoidance (NRSA) attempts to reduce both the position and orientation errors of the end-effector with the same priority. Redundancy singularity avoidance (RSA) attempts to reduce the position error of the end-effector with the first priority and reduce the orientation error of the end-effector with the second priority; Both NRSA and RSA are based on a modification of a Jacobian matrix. Point-to-point singularity avoidance (PTPSA) makes the end-effector pass through a singular region based on joint-interpolated control without maintaining the position and orientation of the end-effector. Experimental case studies are developed to investigate the manipulator performance when the end-effector approaches the wrist and shoulder singularity. The maximal end-effector trajectory error and users' feelings are statistically evaluated and analyzed in the experiment. The results of the experiment show the effectiveness and practice of the proposed methods.

Although a cellular manufacturing system can produce diversified products flexibly, its assembly efficiency is mainly limited by the operators' assembly performance. To improve the operators' assembly performance without longtime training, an assembly-skill-transferring method was proposed to realize the assembly skill transfer process from skilled operators to novice operators. In the cellular manufacturing system, the assembly skills consist of cognition skills and motor skills. Taking a “Peg-in-Hole Task” as an example, the effect of the proposed assembly transfer method was verified for motor skills. The results show that the proposed assembly-skill-transferring system can improve the novice operators' assembly performance greatly.

A cellular manufacturing system is good at producing diversified products flexibly; however, its assembly efficiency depends mainly on its operators' abilities. As the workforce shrinks in Japan, cellular manufacturing systems are difficult to maintain. In this case, a new assembly system has been developed since 2006 that combines both the dexterities of human operators and the advantages of automatic machinery. Its characteristics consist of three aspects: collaboration between an operator and twin manipulators on a mobile base, assembly information guidance, and safe design for collaboration. To meet the rapid changing tastes of customers, operators have to assemble various products without longtime training. This requires an effective assembly skill transfer system to extract assembly skills from skilled operators, and then transfer them to novice ones. Considering the characteristics of a cellular manufacturing system, an assembly skill transfer system was proposed and used to extract and transfer assembly skills in both cognition and execution aspects. Taking a cable harness task as an example, the proposed skill transfer system was applied in a developed assembly system. The results show that working under the developed assembly system with physical support, informational support, and the assembly skill transfer system, novice operators' assembly performance was greatly improved. This verified the effect of the proposed solution to maintain the cellular manufacturing system in the aging Japanese society.

Minimizing the task completion time of manipulator systems is essential in order to achieve high productivity. In this paper, this problem is dealt with by utilizing the redundant degrees of freedom (DOF) of a given task and the tool attachment optimization. For example, in a vision-based inspection where a camera is held by a manipulator, the extra DOF can be brought about by allowing the camera to be translated along its approach axis or rotated about this axis when capturing images. Furthermore, the manipulator end-effector position and orientation is optimized by designing an additional linkage at the manipulator end-effector which is called a tool attachment. A 7-DOF manipulator system is used in the simulations to verify the proposed approach. Results showed that this approach can minimize the task completion time by about 17% compared to conducting only motion coordination.

Task completion time and cost are two significant criteria for the selection of manipulator system. For a given task, several Pareto solutions of manipulator systems should be derived based on the evaluation of these two criteria. However, this process requires a large calculation time. In this paper, we propose a method that can select appropriate systems by evaluating task completion time and cost within the desired calculation time. In the proposed method, multiple objective particle swarm optimization (MOPSO) is employed to search for appropriate manipulator systems from a set of candidate systems. Location optimization and motion coordination are integrated to derive the task completion time and the relative cost is used to evaluate the cost of a manipulator system. We employ particle swarm optimization (PSO) for location optimization and use nearest-neighborhood algorithm (NNA) for motion coordination, since PSO and NNA have a high speed of convergence to a good solution. The proposed method is applied to a set of tasks and is proved to be effective and practical.

Practices of developing applications based on SOA principles need to be renovated to meet new requirements for large-scale data processing and to adapt advancements in IT infrastructures in cloud computing. Resource planners will have a significant role as they bridge the development and operation phases in application development. To accomplish these tasks, this paper presents architecture design methods, which reinforce designing and assessing architecture with an applied Design Structure Matrix (DSM). This approach can embrace development of both business logics of applications and IT resources to run them in the cloud and the methods are established through consulting practices on a datacenter.

This paper proposes a framework, which integrates the development and operation environments for cloud applications. Adopting perspectives on lifecycle management, the framework is equipped with tools and platforms, which seamlessly integrate lifetime phases: requirement analysis, architecture design, application implementation, operation and improvement. These are predicated on theories in design engineering, enabling identification of constraints arising in the development process and of dependencies among functional modules. A case study shows the feasibilities of the design principles, and indicates possibilities for the framework to be an Application Platform as a Service (APaaS), which can form an ecosystem of datacenter operators, systems integrators and application providers.

To classify the five individual finger motions from an electromyogram (EMG) signal, a classification system that hybridizes EMG signals in both the transient and converged states of a motion is proposed. The classifications of finger motions are executed individually in each state by a well-established artificial neural network (ANN). Then, the outputs of the two classifiers are combined. The efficacy of the result is evaluated via a piano-tapping task, in which the subjects are instructed to tap a keyboard with each of their five fingers. We use this task to compare the proposed hybrid system and a conventional converged system that uses an EMG signal only in the converged state. For five of the six subjects, the accuracy ratio of finger motions was better in the proposed method: approximately 85% for each finger except the second. Further analysis suggests two remarkable advantages of the hybrid method: (1) the output of the ANN is more credible, and (2) finger motion in the transient state (i.e., the early phase) is more predictable.

This paper addresses the use of a service robot system working for humans in a daily life environment. The robot system described here always interacts with humans, and is therefore required to consider the satisfaction of users to provide suitable services. Our goal is to develop a robot system offering a hand-over service according to the preference of users. Here, we construct a task instruction system for the hand-over task utilizing the idea of Service Engineering as the first step in our research. The system can be used to instruct a robot to bring the indicated objects only by selecting task information, such as grasping position and posture, which can be utilized to estimate the user's preference.

To improve productivity of assembly in cell production, human robot collaboration is introduced. In the collaboration, robot manipulator supports human operators by handing over an assembly part in the assembly process. However, when the human operator works coexisitently with the moving robot in close distance, it might induce high stress to the operator. This paper studies on strain measurement caused by the hand-over motion of an industrial robot, and discuss design criterions of the robot arm motion when working with a human operator. Several basic stresses are experimentally measured: motion speed at robot's movement, motion trajectory and so on. Experimental results indicated following two points. First, low motion speed (less than 500[mm/s]) or non-straight motion is preferred to design hand over motion which induce low mental strain. Second, it is recommended for a human operator to be notified of robot motion speed before it moves to avoid mental strain.

Even if a cellular manufacturing system is robot assisted with assembly support, the main operator is human. A system designer cannot therefore ignore the mental strain experienced by the operator as a result of improper assembly support. In this paper, authors analyzed operators' mental strain induced by physical and informational support in an advanced cellular manufacturing system with human-robot collaboration using physiological parameters related to cognition and emotion. Our results showed that higher speeds of an approaching robot's motion and closer distances between human operator and robot increase mental strain related to emotion, while augmenting text instruction with voice guidance and optical instruction increase mental strain related to cognition and emotion.

The purpose of this work is to develop information support for human-robot collaboration in cellular manufacturing based on human-centered approach to improve the human adaptability of the support system. In this paper, six main developments are presented to illustrate the human-centered approach. Before the human-robot collaboration system can be developed, a human-human collaboration experiment is conducted to investigate the interactions within the collaboration. Instead of analyzing the assembly process in conventional mechanical approach, task analysis approach is used to analyze human operations in assembly. This approach explains the assembly process by human operations for better understanding of the assembly by the operator. Collaboration analysis in both quantitative and qualitative analyses is conducted in design phase to understand the collaboration relationship in assembly. The collaboration is analyzed from the given assembly operations and the tasks are reassigned to the appropriate working agent based on the capabilities of the human operator and the robot system. Risk assessment is conducted to enhance safety information in the support system. Based on human cognitive process and experimental studies, a multimodal information support system is developed with horizontal display providing information support by multimedia presentation. Support information design and presentation are developed based on human information processing. A set of design guidelines is developed to prepare the multimedia presentation. The support system is successfully implemented in a prototype production cell for cable harness assembly. Comparison study is conducted to validate the improvement by the support system.

The IT industry traditionally offers system services to user companies. The services which integrate software and hardware products are geared toward product-based business models. However, with the emergence of cloud computing, users' in-house systems and applications are virtualized on the net, and are replaced with ones provided through outsourcing services. The alternative systems will be combinations of service functions of their companies' and of outsourcers'. This will relieve user companies from their legacy systems, allowing them to concentrate on their competence and to develop new business models effectively. In order to meet this trend, IT vendors should focus not only on the values of platform development but also on those of creating business opportunities. They need to share users' business goals and collaborate with them to enhance their business values. This paper proposes a framework and supporting tools to co-create business values between IT vendors and clients through the business lifecycle, showing the results from partly applying them to the early stages of development of e-learning services.

The minimization of task completion time of robot arms has been an extensively studied area in robotics. Previous researches mostly focused on optimization methods for the motion planning and collision avoidance, which did not involve any modifications in the hardware design of a robot arm. Some researches, on the other hand, fully design a specialized robot arm for a given task. In this study, we propose a hybrid design composed of a hardware design and an optimization method. The hardware design is a tool attachment, which is a fixed linkage attached between the end-effector of a robot arm and a tool. In the optimization method, we incorporate base placement design, goal rearrangement and collision avoidance through motion coordination in order to minimize the task completion time of a robot arm. Our proposed design is tested using a 6-DOF robot arm and a 1-DOF rotating table. The method is evaluated over a single task and a set of tasks showing its effectiveness and applicability for practical applications.

Long-time exposure to repetitive or monotonous work is associated with increased risk for musculoskeletal disorders that are due to muscle fatigue. Previously, researchers reported that muscle fatigue can be estimated using a low-frequency band of an SEMG signal. However, these studies were performed exclusively during static contraction tasks. The objective of the present study was to evaluate and determine the frequency range for a low-frequency band. In addition, the performance during dynamic contraction tasks was analyzed. A group of healthy university students (8 males) was recruited, and endurance handgrip tasks were conducted. SEMG signals were captured from the forearm muscle. The frequency range for the low-frequency band was redefined as 5 - 40 Hz. The results from a dynamic contraction task indicated that a low-frequency band is a reliable method for indexing muscle fatigue from SEMG signals.

The objective of this work is to enhance man-machine collaboration in cell production by task modeling approach. Task modeling provides a method to define and study the collaboration between man and machine. Six requirements have been derived as basis of development. In this work, the task modeling has extended classical HTA method to represent collaborative operation in a hierarchical structure with the classification of operation task levels and extended operation details as task properties. A modeling tool is developed to provide a development and data management platform. The man-machine collaboration is well defined in a structural format by the ability of task analysis method to address human task in a more flexible way. The collaboration modeling and operation resources information have significantly facilitated operation planning in both assembly and control levels. From the case study, the improvement in safety aspect has proven the ability of this approach in assisting safety design and development of production system. The integration with operation control system has shown the execution potential in real-time operation. The unique development of operation data management has expanded this work into operation information support. Through the multimodal information support system, the human operator is well guided by the operation information corresponded to the task components. The operation information also can work as evaluation functions to measure the human working performance and system performance as a whole.

A work cell is generally designed to achieve a high throughput and its size is typically viewed as contingent to component sizes. In this paper, we aim to design a compact work cell (spatial requirement) and to minimize its task completion time (temporal requirement) to a value set as a constraint. By doing so, a work cell occupies a minimal space and achieves its desired throughput. The work cell size is evaluated based on the size and the swept volume of components. This evaluation is important since a robot arm can have a very large swept volume depending on a given task. To satisfy the spatial and temporal requirements, we propose the integration of the base placement optimization, goal rearrangement, and motion coordination between the robot arm and the positioning table. Furthermore, we introduce two motion coordination schemes based on the spatial and temporal requirements. We showed the effectiveness of the proposed method through simulations.

The challenge of this work is to study the design and development of human-robot collaboration (HRC) in cellular manufacturing. Based on the concept of human collaborative design, four main design factors are being identified and developed in an active HRC prototype production cell for cable harness assembly. Human collaborative design aims to optimize the system design for the advantage of collaboration between human and robots based on human considerations. Task modeling approach is developed to study and analyze the task in order to identify the collaboration tasks to develop the collaboration planning. In the collaboration safety development, five safety designs, cover both hardware and control design, are proposed and developed in the prototype system. Risk assessment is conducted to verify the safety design. Two main experiments were conducted as preliminary study to investigate mental workload in HRC. A multimodal information support system is developed in the study of man-machine interface in this work to provide a comprehensive human-robot interface to facilitate human operator. The system performance evaluation had proven the improvement of prototype production cell with HRC design for cellular manufacturing.

In the near future robots will be used in home environments to provide assistance for the elderly and challenged people. As home environments are complicated, external sensors like ceiling cameras need to be placed on the environment to provide the robot with information about its position. The pose of cameras influences the area covered by the cameras, as well as the error of the robot localization. We examine the problem of the finding the arrangement of ceiling cameras at home environments that maximizes the area covered and minimizes the localization error. Genetic algorithms are proposed for the single and multi-objective optimization problem. Simulation results indicate that we can obtain the optimal arrangement of cameras that satisfies the given objectives and the required constraints.

The purpose of this work is to conduct human factors studies in the development of an information support system for human-robot collaborative cellular manufacturing system. Multimedia technologies are being utilized to enhance the support system to function as operational information support and interface between human operator and robot system. In the study, five experiments were carried out in both system hardware and support information developments to investigate the human factors design of the support system. In the information display approach study, comparison of information presentation ability among paper manual, LCD TV and projector was conducted. Similar information was displayed in different visual areas by vertical and horizontal LCD TV configurations to study the effect on human visual working area. The comparison experiment on image, text and voice formats had resulted varying modality effectiveness of information. Different information formats require different human cognitive processes even though the information contents are similar. The investigation on multimedia displays in five combinations of information elements was performed in multimedia display design study. The information support system is implemented in a human-robot collaborative prototype production cell. The cable harness assembly experiment had proven the effectiveness of the information support system in guiding the operators on the assembly operation and also to collaborate well with the robot system.

The minimum-time motion coordination is an important subject in robotics. In this study, the arrangement of several goals, which is treated as a traveling salesman problem (TSP), is incorporated to this subject. Although TSP has been studied in most previous works; but, solving a TSP that takes into account collision occurrences has not received much attention. This instance arises when a robot arm has to plan a sequence of reaching goals with other moving objects and/or other robot arms. If goals are also moving, then the problem becomes more complex since the end configuration of robot arm is undefined when reaching a goal. In this study, in particular, a 6-DOF robot arm has to reach several goals found in an object while a 1-axis positioning table simultaneously positions the object; thereby changing the goal locations and collision occurrences are inevitable. For the purpose of this study, the TSP is solved effectively with motion coordination and collision avoidance. The collision-free configurations of a robot arm when reaching goals are solved through motion coordination. Collision is avoided by exploiting the redundancy of the system. The above-mentioned solution is verified through a simulation utilizing an object with various numbers of goals and their positions, and is proven effective.

We have proposed “attentive workbench (AWB),” an assembly cell that supports the production activities of human workers. Attentive Workbench is composed of an augmented desk interface and self-moving trays with the Sawyer planar motors. In this paper, real assembly experiments using the implemented AWB system are carried out. The merit of the physical assembly support by the proposed system is evaluated quantitatively in the view of necessary time for product assembly.

In this paper, we investigate characteristics of a dynamic programming (DP) algorithm when it is applied to a control problem of a chaotic system. We choose a height task of the Acrobot, which is an underactuated robot. For various reasons, a straightforward method of DP is thought that it is not suitable for such a system. However, DP is attractive because of its conciseness, versatility, and flexibility toward boundary conditions. Our simulation results suggest that to apply DP methods to the task is possible under some conditions. Moreover, even when the conditions are not fulfilled, some interesting behavior of the Acrobot can be found.

We aim to realize an intelligent robotic system that delivers necessary objects to human desk-workers in home or office environments. In order to meet this goal, we propose methods to understand a request for support of a user of the system. We adopt an approach that the system measures the userpsilas hand and eye movements in reaching for an object to detect and understand the request. Based on the detection and understanding of the request, the system delivers necessary objects to the user using self-moving trays. The experimental results demonstrate the advantage of the methods proposed here.

We propose a method for generating robot motions by integrating multiple policies effective for task achievement. The method obtains a new policy efficiently based on the applied policies. However, there might be some states in which the applied policies fail to achieve the task. The failing states are found by means of a decrease in the state values. The policies for the states are then modified. In this paper, we applied this method to clutch assembly in order to demonstrate its validity for assembly tasks. We integrated insertion motion and search motion for the task and finally obtained the effective motion that accords to the task states.

To solve decision making problems of multi-agent systems, researchers have devised complicated methods, which are expected to solve curse of dimensionality. In this paper, we go to the opposite extreme. We generate cooperative behavior of two soccer robots with a simple dynamic programming (DP), which was proposed in '50s. Through the example, the ability of DP on a recent computer is measured and evaluated both qualitatively and quantitatively. We then show that the simple structure of DP is useful in obtaining behavior of robots in a convincing way. In the implementation of DP, space that is spanned by eight variables for decision making is divided into 610 million states. DP solves the optimal actions of two robots in every division and creates a look-up table, which is called a state-action map. The ability of this state-action map is measured by simulation and the result is discussed.

In this paper, the sampling real-time QMDP value method is proposed and applied to a goalkeeper task of a soccer robot. Soccer is a challenging task for an autonomous robot that has poor computing resources and sensors, and a good subject in the study of decision making in dynamic environments. A robot frequently decides its behavior without enough observation of the environment. In the proposed method, the risk of a score is solved beforehand toward every set of position of the goalkeeper and motion of the ball. The shortage of observation is calculated and represented by particle filters. The proposed method uses the risk function and the particle filters so as to choose appropriate behavior of the goalkeeper. The experiment with an actual robot suggests that the method can decide actions reflexively toward the motion of the ball.

We aim to realize a robotic system that hands over a necessary object to a user as soon as he/she attempts to reach out his/her hand for it. In order to realize such system, the following is required: 1) detection of the reaching movements, 2) prediction of the target object among multiple objects, and 3) handing-over the object to a user. In this paper, the first two of them are discussed. To detect the reaching movements, we use the speed of a hand movement, the smoothness of the hand trajectory, and the relation between a position of hand and a gaze point. To predict the target object, we use a probabilistic model based on the user's hand movements and his/her gaze direction. The proposed system can detect reaching movements and predict the target object at a very early stage. A description of the experimental results demonstrates the advantage of the method proposed here.

Embedded processors for video image recognition in most cases not only need to address the conventional cost (die size and power) versus real-time performance issue, but must also maintain high flexibility due to the immense diversity of recognition targets, situations, and applications. This paper describes IMAP, a highly parallel SIMD linear processor and memory array architecture that addresses these trade-off requirements. By using parallel and systolic algorithmic techniques, but based on a simple linear array architecture, IMAP successfully exploits not only the straightforward per-image row data level parallelism (DLP), but also the inherent DLP of other memory access patterns frequently found in various image recognition tasks, while allowing programming to be done using an explicit parallel C language (1DC). We describe and evaluate IMAP-CE, one of the latest IMAP processors, integrating 128 100 MHz 8 bit 4-way VLIW PEs, 128 2 KByte RAMs, and one 16 bit RISC control processor onto a single chip. The PE instruction set is enhanced to support 1DC code. The die size of IMAP-CE is 11 times11 mm2integrating 32.7 M transistors, while the power consumption is, on average, approximately 2 watts. IMAP-CE is evaluated mainly by comparing its performance while running 1DC code with that of a 2.4 GHz Intel P4 running optimized C code. Based on the use of parallelizing techniques, benchmark results show a speed increase of up to 20 times for image filter kernels and of 4 times for a full image recognition application

Time optimal control method for quadruped walking robots are developed and installed into a practical robot system. Each leg is modeled as a two link manipulator whose time optimal control theory has already been established by Bobrow. However, in legged robot systems, each leg supports their body weight, and the reaction forces from its ground must be inside of their friction corn. Moreover, the ZMP (zero moment point) of the robot is constrained for stable walk. Therefore, time optimal control inputs must be designed considering these constraints. SONY ERS-7 is used as a quadruped walking robot and a fundamental experiment is done. From the experimental results, the effectiveness of the developed control algorithm is verified

Nowadays, the Man-Machine interfaces are becoming more important in our interaction with robotic systems. One particular case is on prosthetic devices, where the need of "biofeedback" is of vital importance to achieve subconscious control of these devices. In order to provide this feedback, so the device can be included into the user's body image, we use electrical stimulation as a substitute for tactile feedback. In this study we analyze the effects of the electrical stimulation together with the intention, provided by the electromyography, for the sensation generation, and its inclusion on the user's body schema. To evaluate our system, we use functional Magnetic Resonance Imaging, to measure the changes in the brain due to the use of an EMG controlled prosthetic hand with electrical stimulation as tactile feedback.

This paper describes a new real-time learning method for the development of a robust motion discriminating method from an EMG signal, to adjust to the change in user's characteristics. This method is done under the assumptions that the input motions are continuous, and the teaching motions are ambiguous in nature, therefore, automatic addition, elimination and selection of learning data are possible. Applying our proposed method, we conducted experiments to discriminate eight forearm motions, with the results, a stable and highly effective discrimination rate was achieved and maintained even when changes occurred in user's characteristics

We have proposed "attentive workbench (AWB)," a deskwork support system. Using cameras, projectors, and self-moving trays, the system supports human user from both physical and informational aspects. In this paper, an interface between the user and AWB based on pointing gestures is developed. Considering the usage of AWB, a simple and reliable interface with quick response is implemented. Deskwork support using the present interface and real self-moving trays are demonstrated

The Acrobot is an underactuated robot and provides challenging control problems due to its nonlinearity. We try creating global control policies depending on the limitation of memory that is available for recording them. A swinging up task of the Acrobot is solved by dynamic programming (DP) without heuristics. The result of DP is compressed to an arbitrary size of control policy by our vector quantization (VQ) method. A chaotic but performable control policy can be obtained in the global state space of the Acrobot by DP. Moreover, we can verify that our VQ algorithm can reduce the dimension of the control policy from four to two in the process of compression

This paper proposes a method for planning robot motions by integrating multiple knowledge that is effective in task achievement. The method efficiently obtains a new policy, which is a mapping from states to actions, on the basis of the knowledge presented in a state-action map. However, in some states, the applied knowledge fails to achieve a given task. In our method, the failing states are found by using the decrease in the state values, and the policy for these states is then modified. In order to demonstrate the validity of our method, we applied it to rearrangement tasks of multiple objects. The appropriate policies were obtained by integrating programs for similar tasks and a simple rule for the task process; moreover, a new knowledge that is effective in the rearrangement tasks was extracted from the obtained policies

We developed a new adaptable EMG prosthetic hand, which executes recognition process and learning process in parallel and can keep up with change in the mapping between an electromyographic signals (EMG) to the desired motion, for amputee. EMG-to-motion classifier which used in proposed prosthetic hand is done under the assumptions that the input motions are continuous, and the teaching motions are ambiguous in nature, therefore, automatic addition, elimination and selection of learning data are possible. Using our proposed prosthetic hand system, we conducted experiments to discriminate eight forearm motions, with the results, a stable and highly effective discrimination rate was achieved and maintained even when changes occurred in the mapping. Moreover, we analyzed mutual adaptation between human and adaptable prosthetic hand using ability test and f-MRI, and clarified each adaptation process

The purpose of our research is to build a system for mutual adaptation between a user and assistive devices for restoration of motor function. To build such system, it is necessary to know human's motion patterns. In this paper, as the first step, we investigated human motion characteristic on human-machine system like EMG (electromyogram) prosthetic hand and EMG to motion classifier system. In the experiment, we measured the EMG signals and investigated a difference between motion patterns of teaching motion, i.e. user's intended motion, and that of actual motion using the proposed criteria. As results, it is clear that these criteria are useful to analyze changes of human motion patterns

In this paper, we introduce our robot package for educational use. The main characteristics are the followings: robots are built by connecting plastic bottles and RC servo motors with glues so that technical skills such as machining are not required for students; three types of robot controllers, such as manual controller, autonomous controller, bio-signal interface controller, are provided so that students can experience autonomous robots and bio-signal interface techniques. Thus, this package provides opportunities to design both robot structure and control architecture and, moreover, to experience new engineering technologies. So far, we have conducted robot education courses for undergraduates and graduates three times. The first course purposed to teach students morpho-functionality, which is a concept of embodied artificial intelligence. As results, all the students have designed locomotive robots and understood "morpho-functionality." In the second and third courses, students have experienced to control locomotive robots with bio-signal interface techniques. Thus, we have shown that this educational package provide variety of robot techniques and, depending on course hour and students target, we can modify course programs

We aim to realize a robotic system that hands over a necessary object to a user as soon as he/she attempts to reach out for it. In order to realize such system, the following is required: 1) detection of the reaching movement, 2) prediction of the target object among multiple objects, and 3) handing over the object to a user. In this paper, the first two of them are described and discussed. We apply the smoothness and the speed of the hand movement to distinguish whether the movement is for reaching or not. And in order to predict the target object, we define the certainty according to the relative movement of the hand to each object. To evaluate the performance of the proposed method, we compare the method with the minimum jerk model based approach. A description of the experimental results demonstrates the usefulness of the method proposed here

The purpose of our research is to build a system for mutual adaptation between a user and assistive devices for restoration of motor function. To build such system, it is necessary to know human's motion patterns. In this paper, as the first step, we investigated human motion characteristic on human-machine system like EMG (electromyogram) prosthetic hand and EMG to motion classifier system. In the experiment, we measured the EMG signals and investigated a difference between motion patterns of teaching motion, i.e. user's intended motion, and that of actual motion using the proposed criteria. As results, it is clear that these criteria are useful to analyze changes of human motion patterns.

An algorithm that acquires the intermediate goals between the initial and goal states is proposed for an agent executing multiple tasks. We demonstrate the algorithm in the problem of rearranging multiple objects. The result shows that the moving distance to transfer the entire objects to their goal configuration is 1/15 of that without using intermediate goals. We experiment using a real robot to confirm that the intermediate goal can be adapted to a real environment. Our experimental results showed that an agent could adapt the intermediate goals, which were acquired in the simulation, to the experimental environment.

We propose “Attentive Workbench (AWB),” a new cell production system in which an intelligent system supports human workers. Using cameras, projectors, planar motor driven self-moving trays and other devices, the system supports workers from both physical and information aspects, recognizing worker’s condition and intention. This paper outlines AWB and deals with physical assembly support using self-moving parts trays. Two different schemes, centralized and decentralized, for controlling multiple parts trays are evaluated through experiments and simulations. The centralized control scheme is found to have the higher performance than the decentralized control scheme.

We have proposed the real-time QMDP method for decision making of a robot under uncertain state recognition. This method evaluates every action and chooses the best one with a particle filter for estimation and a state-value function of dynamic programming. Different from our past work, this paper applies it to a complicated decision making task that yields local maxima and discontinuity on the state-value function. We then verify whether the method can choose proper actions or not in such a condition. As an example, total behavior of a goalkeeper for robot soccer is planned by using value iteration. This task contains three strategies, which are related to three kinds of local maxima respectively. Simulations, experiments and actual games have suggested that the method can decide actions effectively according as uncertain result of state estimation.

Design process of a robust flow-path network for automated guided vehicle (AGV) systems is proposed in this paper. An effectiveness of a system with a robust flow-path network does not sink against any task. However, for this robust flow-path, the number of possible tasks is very large in AGV systems, therefore it is impossible to test the promising flow-path network against all of possible tasks. The problem is solved by the method of difficult task design with genetic algorithm (GA). The effective flow-path network is designed with GA simultaneously, because the difficult tasks depend on the flow-path networks. Competitive co-evolution is applied to the simultaneous design. Results of the designing are shown through simulations and the designed flow-path network makes it possible to complete 10000 tasks that are generated randomly.

SMA has been used as an actuator alongside with certain heat sinking mechanism which makes the structure of the actuator as a whole, bulky and heavy in nature. This paper describes the effort taken in speeding up the rate of heat transfer of the SMA in ambient environment by introducing a simple, new heat sink, consisting of a combination of an outer metal tube and silicone grease as cooling medium. The SMA wire of diameter 0.3 mm is first coated with a layer of silicone grease, and is inserted into the outer metal tube making sure that the silicone coated SMA does not inhibit the mobility of the outer metal tube. An experimental setting, with the task of using the SMA to vertically haul up a 3kg weight was set up. PWM (pulse width modulation) control was applied to the SMA and by using a position sensor, the rise and fall of weight can be easily monitored, therefore the response speed of the actuator can be observed. Meanwhile a temperature sensor, a thermocouple type-K, was used to monitor the temperature of the SMA for temperature control. Simulation results of the rate of heat transfer based on the heat transfer equation are also presented to validate the effectiveness of this proposed heat sink.

We have proposed "attentive workbench (AWB)", a new cell production system in which an intelligent system supports human workers. Recognizing worker's condition and intention, the system supports workers from both physical and information aspects. This paper deals with physical assembly support using self-moving parts trays. The system delivers necessary assembly parts to workers and clears finished products quickly. On transporting large products, multiple trays are subjected to form a rigid body working as a large single tray. In order to realize this arrangement of trays in real-time, a planning method based on the priority scheme and heuristic rule is proposed. The present method is evaluated through simulations. A demonstration of assembly support using real self-moving trays is shown.

We have proposed "attentive workbench (AWB)," a deskwork support system. Using cameras, projectors, and self-moving trays, the system supports human from both physical and informational aspects. This paper deals with the problem for estimating the object that a user needs. We present one of the approaches for accurate estimation of a necessary object from the user's pointing gesture. The system arranges the self-moving trays by itself based on the user's past action sequences. Using force-directed method, good placement, which decrease false estimations and is not moved very much from the initial placement, can be obtained. A description of the experimental results demonstrates the usefulness of the method proposed here.

We have proposed to use vector quantization (VQ) for compressing a decision making rule (a policy) on a multi-dimensional memory array. Our VQ method can reduce the amount of memory for recording a policy. In this paper, we compare this method with other techniques that economize the amount of memory in order to measure the ability of this method more rigidly than ever. One of the techniques is tile coding, which is frequently used for reinforcement learning. The other is the mere reduction of the resolution of a policy. Moreover, we try applying VQ to already compressed policies. As a result, vector quantized policies and double vector quantized policies could mark better performance than the others.

Parameter tuning of force control is important for successful robotic assembly and ensuring high efficiency operations. In this paper, we present a method of designing damping control parameters for general assembly operations by considering the cycle time. In this method, optimal parameters are obtained through iterative simulations of assembly operations because it is difficult to estimate the cycle time analytically. We have applied the method to clutch assembly, which is a complicated insertion of a splined axis into movable toothed plates, and demonstrate how the operation can be sped up using the obtained parameters.

Embedded processors for video image recognition require to address both the cost (die size and power) versus real-time performance issue, and also to achieve high flexibility due to the immense diversity of recognition targets, situations, and applications. This paper describes IMAP, a highly parallel SIMD linear processor and memory array architecture that addresses these trading-off requirements. By using parallel and systolic algorithmic techniques, despite of its simple architecture IMAP achieves to exploit not only the straightforward per image row data level parallelism (DLP), but also the inherent DLP of other memory access patterns frequently found in various image recognition tasks, under the use of an explicit parallel C language (IDC). We describe and evaluate IMAP-CE, a latest IMAP processor, which integrates 128 of 100MHz 8 bit 4-way VLIW PEs, 128 of 2KByte RAMs, and one 16 bit RISC control processor, into a single chip. The PE instruction set is enhanced for supporting IDC codes. IMAP-CE is evaluated mainly by comparing its performance running IDC codes with that of a 2.4GHz Intel P4 running optimized C codes. Based on the use of parallelizing techniques, benchmark results show a speedup of up to 20 for image filter kernels, and of 4 for a full image recognition application.

In this paper, we present a method of motion planning of multiple robot fingertips for graspless (or nonprehensile) manipulation. The method can automatically generate various graspless operations, including pushing and tumbling. By considering whether each robot finger should be position- or force-controlled, we can obtain robust manipulation plans against external disturbances. Some examples of planned graspless manipulation of a cuboid by two robot fingers are presented. We also show an experimental result of execution of planned graspless manipulation by a robot with a multi-fingered hand.

Vector quantization (VQ) is a useful method for compressing data in an array such as images and sounds. We have applied it to motion planning for robots. Dynamic programming is used for planning and outputs the result as a large multi-dimensional array. The array is compressed with VQ, and installed on a robot whose memory space is smaller than the array. Some experiments have shown the potential of this method. In this paper, we improve this method with value iteration algorithms that are applied to a compressed map. Simulations verified the improvement of the compression ratio with the value iteration algorithms.

It is necessary to design appropriate parameters of force control in robotic assembly so as to achieve successful operations. Moreover, obtaining control parameters that can shorten the cycle time to perform operations is very important in industrial applications. In this paper, we propose a method to obtain control parameters through repetitive simulation of an assembly operation in order to estimate the cycle time because it is difficult to calculate the cycle time analytically. First, a simulator of a robotic peg-in-hole operation is developed based on preliminary experiments. We then formulate our proposed method as an optimization problem and solve the problem using the simulator. Finally, results of the optimization are presented.

Integrated design process for automated guided vehicle (AGV) systems is proposed in this paper. There are two problems to design AGV systems: transporter routings and flow-path networks. These two should be solved at the same time, because one problem depends on the other. This issue is solved with cooperative co-evolution in this paper. Both problems are represented as different species and genetic algorithm is applied to them. AGV systems designed with this method are evaluated through simulations with real data.

This paper proposes a method that reasons intent of motion through task order such as "switch on the light." Intent of motion means kinds of path of a contact point between a target and an end effector when a robot recreates ordered task. The intent is used for teaching. After a robot fixes a framework of task using the intent, it asks questions to a user to specify concrete values in the framework, the user replies them. This interaction creates motions of the robot. The kinds of path are defined as linear, circular and point to point. Moreover, impossible task is also considered. Four sets of P/sub f/(w): Probability that a word represents a path, and C/sub p/(w}: Certainty of P/sub p/(w) are added to each word in an electric thesaurus to enable the reasoning. After values are input in part of the sets by 8 production rules, they are propagated to the other sets through hierarchical relationship of words in the thesaurus. When the user enters two words, namely task and target, argmax/sub p/{P/sub p/(w)*C/sub p/(w)} becomes answer. Moreover, update and re-propagation of values in the sets using answers from the user make the reasoning more precise.

Though Monte Carlo localization is a popular method for mobile robot localization, it requires a method for recovery of large estimation error in itself. In this paper, a recovery method, which is named an expansion resetting method, is newly proposed. A blending of the expansion resetting method and another, which is called the sensor resetting method, is also proposed. We then compared our methods and others in a simulated RoboCup environment. Typical accidents for mobile robots were produced in the simulator during trials. We could grasp the characteristics of each method. Especially, the blending method was robust against the kidnapped robot problems.

Designing appropriate force control parameters is necessary in robotic assembly for successful operations. Moreover, obtaining control parameters that can shorten the cycle time to perform operations is very important in industrial applications. In this paper, we present a method to design damping control parameters that can shorten the cycle time and show the effectiveness of the parameters obtained through the method. In the method, sub-optimal parameters are obtained through repetitive simulations of assembly operations in order to estimate the cycle time because it is difficult to calculate the cycle time analytically. We apply the method to peg-in-hole operations and show experimental results using the control parameters obtained through the method.

In this paper, region exploration path planning algorithm is proposed. In order for a mobile robot to perform this task, appropriate measures with the shape of the working environment, which may be intricate or curved, is necessary. In addition, a robot must be able to react and be flexible when confronted with obstacles. With this algorithm, these challenges can be met by approximately expressing the working environment in grid points and regenerating the path using one that was planned beforehand. Simulations are used to demonstrate proposed exploration path planning and re-planning algorithm.

The design for an artificial mark attached to small objects is presented in this paper. Three conditions are required for the design of the marks: (1) short calculation time, (2) easy attachment, and (3) individual calculation for each item. The marks are obtained by using three different extraction methods. The experiments determine the best mark. The mark using the method that extract colors and calculated the gravity has good results. We analyze the errors of the mark that has best experiment. The appropriateness of the experimental results is then confirmed. We have the experiment that the manipulator handles the objects with the best mark. The experiment is successful. Therefore, the usability of the mark is verified.

To achieve smooth motion of car-like robots, it is necessary to generate paths that satisfy the following conditions: maximum curvature, maximum curvature derivative, and curvature continuity. Another requirement is that human operators can manipulate the robots with ease. In this paper, a path expression methodology consisting of line segments, circular arcs and clothoid arcs is presented. In addition, a method of global path generation with a visibility graph is proposed. To establish this method, the following steps are proposed: (a) the arrangement of subgoals (middle points) and (b) the construction of the graph for path generation. By using the proposed method, the paths were shortened 14% on average.

In this paper, a flexible robotic assembly system with decentralized architecture is presented. The system is designed to achieve high reconfigurability so that it can adapt to changes in manufacturing environment; a new robot can be easily installed to the system and execute assembly tasks immediately, together with other devices. For easier reconfiguration, a semi-automated calibration method for positions of newly installed robots is integrated into the system. Our implementation of the assembly system consists of conventional manipulators and a belt conveyor. In the experiment, a new mobile manipulator was installed successfully and performed an assembly operation jointly with other existing manipulators.

In this paper, we propose cooperative exploration method for mobile robots in a working area. The method will generate and share the minimal-cost path for each mobile robot. Each mobile robot goes through several observation points to accomplish the exploration. The observation points should be arranged at a fixed distance from at least on corresponding observation point. In addition, the number of observation points and the lengths of paths for each mobile robot are to be minimized. The proposed method should have the efficiency in computational cost concurrently with the adaptability to dynamic environmental changes.

It sounds clever to achieve intelligence of a mobile robot by means of pre-computed algorithm, because it can cut down computation on a small computer installed on the robot. However, the amount of pre-computed results is usually too large to store. This paper proposes a compression method for pre-computed data of dynamic programming. A vector quantization method is proposed with the studies on entropy evaluation. Robot motions in RoboCup are planned by means of dynamic programming. States on the optimal state-action map are once bounded into a neighboring group and then compressed into a tiny number of state-action. The distortion, the bad side effect of compression, is evaluated and minimized. The proposed method is verified on both simulations and experiments of robots.

This paper offers a proposal for an algorithm of controlling a mobile robot that searches for and rearranges objects with unknown locations and shape. In this paper, we divide the task into two parts: exploration task and rearrangement task. The algorithms for each part of the task are presented with respect to the effectiveness of the path length and computational cost. Additionally integration algorithm that effectively combines exploration and rearrangement is presented. Experiments with a real robot are conducted to demonstrate the effectiveness of the proposed algorithm.

This paper presents a robot system for handling various objects in home or office environments. A fixed manipulator utilizes marks on objects for handling and motion planning. A mark consists of two parts. One is the outer part, which indicates its pose (in this paper, "pose " denotes 3D position and orientation), and the other is a QR code, which is a kind of 2D barcode. A QR code is stored information of an object (e.g. its name). A user attaches several marks on each object. The manipulator accesses the information using a camera in its hand. The robot can decide its complex handling motion based on the information in QR codes, pose of the objects, which are estimated from pose of marks, and signals from proximity sensors. Experiments are conducted to verify the whole system.

To achieve various manipulation tasks by robot fingers, we have to use both position control and force control appropriately. In this paper, we propose a method to determine such control modes of robot fingers in graspless manipulation. Using the method, we can assign a position- or force-control mode to each robot finger so that the maximum manipulation stability will be achieved without excessive internal force. Desired finger forces are also determined for robot fingers to be force-controlled. We show some numerical examples of automatic determination of control modes in graspless manipulation of polyhedra on a plane by two robot fingers.

Uncertainty of self-localization is one of the most serious problems related to navigation of autonomous mobile robots. There are some studies that deal with this problem. However, most of them assume that the extent of the uncertainty is known or has been measured previously, though it changes easily with some trivial changes of the environment. To avoid this assumption, we take the following approach: 1) a robot uses a self- localization method that is quite robust against sensing noise and the environment change, 2) the plan for robot behavior is based on the assumption that the robot can recognize the environment perfectly, 3) a novel decision-making algorithm computes proper behavior from the planning result and self-localization results in real time. These algorithms were implemented on a soccer robot of the RoboCup four-legged robot league, and their efficiency was verified with experiments.

Seamless and high resolution images that copy a room is expected to be used for many applications (e.g. a guard system, amusement, remote control, and so forth). We are developing a mobile robot system for obtaining such images automatically. This system utilizes single kind of line marker, which is adhesive tape and is attached horizontally by a user beforehand. A mobile robot goes round a room and builds map. The map is used to collect images of above part of each marker. It means that the mobile robot does not need to know prior information of the room. Therefor, the underlying problems in this paper are localization and exploration by a mobile robot without prior information of the environment.

Proposes a flexible assembly system, where autonomous manufacturing devices and production management agents communicate with one another to accomplish production tasks. This architecture allows the system to arrange manufacturing devices independently of the type of products assembled and to assemble multiple products in parallel and asynchronous progress. This system also supports plug and produce, a system function that realizes easy reconfiguration. Thus, the system can return quick responses to breakdowns and changes in production quantities. This paper also presents an index for the general evaluation of reconfigurable manufacturing systems. With this index and the plug-and-produce function, the system can be reconfigured appropriately to adapt to changes in the manufacturing environments.

In this paper, we propose a motion-planning method of multiple mobile robots for cooperative transportation of a large object in a three-dimensional environment. This task has various kinds of problems, such as obstacle avoidance and stable manipulation. All of these problems cannot be solved at once, since it would result in a dramatic increase of the computational time. Accordingly, we divided the motion planner into a global path planner and a local manipulation planner, designed them, and integrated them. The aim was to integrate a gross motion planner and a fine motion planner. Concerning the global path planner, we reduced the dimensions of the configuration space (C-space) using the feature of transportation by mobile robots. We used the potential field to find the solution by searching in this smaller-dimension reconstructed C-space. In the global path planner, the constraints of the object manipulation are considered as the cost function and the heuristic function in the A/sup */ search. For the local manipulation planner, we developed a manipulation technique, which is suitable for mobile robots by position control. We computed the conditions in which the object becomes unstable during manipulation and generated each robot's motion, considering the robots' motion errors and indefinite factors from the planning stage. We verified the effectiveness of our proposed motion planning method through simulations.

The stability of objects in graspless manipulation (or nonprehensile manipulation) is investigated. In contrast with the stability of grasps, it is crucial for the stability of graspless manipulation to evaluate frictional forces applied to objects in contact motion. We formulate the effect of Coulomb friction and propose a quantitative stability measure for graspless manipulation. The measure can be calculated approximately with linear programming. Finally, we show numerical examples. Our stability measure will be useful in planning of graspless manipulation.

Describes a concept of a distributively placed modular robot system and a methodology of parameter identification of the system. The robot system consists of modules which have monofunction (e.g. sensor or actuator) and radio communication. Depending on tasks, the system is constructed by attaching modules to an object or in a working area distributively. Then the modules achieve a task by their cooperation. In our algorithm, the parameters are identified by executing motions with actuators, and observing the changes of the state with sensors. The motion which we call testing motion influences accuracy of identification because of sensing errors. Accounting for this, especially for the case of a mobile robot and a ceiling camera module, the design of modules' testing motion is made by evaluating the influence of the camera's sensing error and dead-reckoning's locating error. The effectiveness of the algorithm is shown in the simulation and a basic experiment.

In this paper, we describe a novel self-localization algorithm. Self-localization methods are required for lowering the computational cost and handling vague sensor data. Thus, we propose to use only the uniform distribution to represent probability distributions in Monte Carlo localization, and name this method a uniform Monte Carlo localization (Uniform MCL). We manifest the low computational cost and robustness of Uniform MCL in the environment of RoboCup Sony legged robot league.

This paper presents an integrated design for an automated guided vehicle (AGV) system. Three kinds of integration problems are solved: transporter routings are classified; the number of AGVs for the systems is determined; and suitable flow paths are calculated for the various kinds of transporter routings. The flow paths are calculated by solving an iterative direct problem using a genetic algorithm (GA). The set of transporter routings, the number of AGVs, and the flow path of the AGV systems are constructed with simulations.

In this paper, we propose a simple teaching method for industrial robots by human demonstration. The method can be divided into two parts: the teaching phase and the planning phase. In the teaching phase, a human operator demonstrates a manipulation of an object, and two cameras recognize the path of the object by observing markers attached on the object. In the planning phase, a motion planner generates a sequence of robot operations to play back the demonstrated path by pick-and-place and pushing. The proposed method incorporates automated camera calibration required for human demonstration, which enables labor-saving teaching and compensates the absolute positional error of industrial robots.

This paper describes interface design and implementation based on a concept of simple instruction by pointing environmental features on navigation task of a modular robot system. The robot system is constructed by attaching modules (e.g. camera or mobile mechanism) to objects or a working environment distributively. The attached modules achieve tasks through cooperation, after constructing the system. Assuming that the system is constructed in different environments depending on tasks, the system is not expected to have knowledge of environment for autonomous behaviors. According to this, we propose a simple interface with instructing tasks on multi displayed images of cameras which are attached in unknown wider working area. The main features of the interface are as follows: (1)Indication of over lapped view of cameras for support human recognition of working area, (2) Easy precise operation by pointing environmental features on captured images. Our experiments show the effectiveness of our interface and the whole robot system.

This paper deals with the method to generate human whole body motion by identifying performance index to be optimized. Most of the human motion in daily life, including a "lift-up an object" motion, is complex and the performance index are regarded to vary during the motion. Lift-up an object motion is generated by solving inverse kinematics. The experimentally measured trajectory of the hand is given and the rest of the degree of freedom is determined by optimizing a performance index that blends several sub-functions. The coefficients for each sub-function are identified through the motion generation simulation.

Recently the activity of robots has been remarkable, and robots are branching out into general environment such as home or office. Although robots are active, planners uniquely decide the action method of robots when robots operate missions. Therefore, the most suitable approach is not assured. So, in this report we propose a method that we evaluate robots' actions from the viewpoint of both reliability and time, when robots operate missions. Then we calculate the most suitable approach for robots. To be concrete, by using a diagram we evaluate robots' actions and calculate the most suitable approach. In addition, we evaluate them not from all the actions immediately, but from the action units by making an evaluation index. So, we can shorten the time for evaluation. Finally, we realize the operations by a real robot with the most appropriate approach.

This paper deals with a task-assignment architecture for cooperative transport by multiple mobile robots in an unknown static environment. The architecture should satisfy three features: deal with a variety of tasks in time and space, deal with a large number of tasks compared with the number of robots, and decide the behavior in real time. The authors propose the following approach: we consider the unit of task (task instance) as the job that should be done in a short time by one robot. Based on the environmental information, task instances are dynamically generated using task templates. The priority of task instances is evaluated dynamically based on the number of robots and the configuration in the workspace. In addition, we avoid generating too many task instances by suppressing object motion. The main part of the architecture consists of two real-time planners: a priority-based task-assignment planner solved by using the linear programming method, and motion planners based on short-time estimation. The effectiveness of the proposed architecture is verified by a cooperative transport simulation in an unknown environment.

In order that robots may achieve tasks in unknown environments, research focusing on the following three points must be conducted: (1) design of commands from the operator to the robots; (2) environmental recognition to show the operator information about the remote work area where robots are working; and (3) interface between a system and the operator and information display of the work area for the operator. For (1), the focus is on the operation of the multiple robots by a single operator. For (2), the problem is divided into two parts; object recognition and self-positioning. As for (3), a graphical user interface is implemented. The operator mainly uses a mouse to input commands, and the operator watches a virtual environment to monitor remote working areas. The virtual environment is constructed with the environment information acquired by the method described in (2) above. After the problems mentioned above are solved, our system will provide a flexible command and monitoring structure and an operator would be able to command the robots appropriately. These are the main advantages of the method we are proposing. We verified the effectiveness of the proposed methods in experiments.

Graspless manipulation is to manipulate objects without grasping by just pushing, tumbling and so on. One of the main difficulties in graspless manipulation is planning. To reduce the load of computation, we adopt a two-step approach: 1) construction and simplification of contact state graph at geometry level; and 2) planning of manipulation at mechanics levels. In this paper, we focus the latter and propose an algorithm to plan mechanically feasible manipulation. It generates digraphs that represent C-subspaces for all the contact states, and unites them into one big graph, which we call a manipulation-feasibility graph. The manipulation plan can be obtained by searching the graph. This algorithm is implemented for planar graspless manipulation by multiple robot fingers, and the planned results obtained are shown.

Adaptation of biological systems can be viewed as decreasing local interaction among subsystems to realize effective cooperation. Conversely, it is important for effective cooperation to evaluate and control local interaction. Based on this idea we present a method of realizing cooperative rope turning by a man and a manipulator. The rotating motion of the manipulator arm for rope turning can be specified by frequency and phase difference between the arm and the rope. The frequency is determined in real-time by rhythm entrainment using a phase-locked loop. The phase difference is related to the quantity of local inter-action, that is, energy transfer from the arm to the rope. Therefore it is controlled to realize desired energy transfer, which is estimated from human demonstration. In the experiment the manipulator can successfully adapt its motion to that of the human partner.

This paper proposes a flexible assembly system that manages production by negotiating with autonomous manufacturing devices. With this mechanism, physical layout of the system is independent of the type of products to be assembled, and the system can asynchronously process multiple parallel production tasks. This system also supports plug and produce: a system function that enables easy reconfiguration. Thus, the system can be quickly accommodated to breakdowns and changes in production quantities. This paper also deals with an index for general evaluation of the manufacturing systems. With this index, we can plan appropriate improvement of the system layouts. Then we reconfigure the system using plug and produce function, in order to accommodate it to the changes in the manufacturing environments.

In this paper, the authors aim at realizing an accurate navigation system of automated guided vehicles (AGV). The authors propose a way of estimating positioning error with magnetic tape, which is widely used in a factory as an external sensor. However, flexibility for path relocation is insufficient, because, in general, the tape should be laid down on the floor from a start point to a goal point so that AGV can reach their target. To overcome this inefficiency, the authors firstly propose a semi-guided navigation methodology by means of two kinds of magnetic tapes based on an error analysis. The semi-guided navigation means that magnetic tapes are only placed at the start and the goal points individually. Therefore, this system enables us to remove most of the magnetic tape. Moreover, the authors attempt a fixed model learning to prevent stationary error while AGV run iteratively. Finally, the authors carry out experiments to evaluate and verify the efficiency of the proposed method.

A control method of robots for human-robot cooperative manipulation is investigated. We propose estimating human motion using the minimum jerk model for smooth cooperation. Using a nonlinear least-squares method, we identify two parameters of the minimum jerk model in real-time. The estimated position of the human hand is used to determine the desired position of the end-effector of the manipulator in virtual compliance control. The effectiveness of the proposed method is verified by experimentation with an industrial 6-degree-of-freedom manipulator. Energy transfer in cooperative manipulation is studied for quantitative evaluation of achieved cooperation from the viewpoint of adaptation theory.

This paper deals with a task-assignment architecture for cooperative transport by multiple mobile robots in unknown environment. The planner should satisfy three features: to deal with the variety of tasks in time and space; do deal with a large amount of tasks; and to decide behavior in real-time. The authors (1999) have proposed the following approach: 1) based on sensor information, tasks will be dynamically generated using task templates; 2) generation of task is tuned in quality by feeding back executed result and in the number by action suppression; 3) main part of the architecture consists of two real-time planner: priority-based task-assignment planner solved by using a linear programming method and motion planners based on short-time estimation. In this paper, we implement our task-assignment architecture on a real robot system and verify the effectiveness of the proposed method by cooperative transport experiment in unknown environment.

A transport module for constructing an efficient and flexible material handling system are proposed in the paper: an AGV (automated guided vehicle) module loaded a conveyer in which it is possible to hand-over operation between two modules. The operation can solve the deadlock problem among AGVs in the process of material handling. Prototype modules are created and hand-over experiments are made to measure motion characteristics of the modules. Transport simulations are made for a model plant layout by using values from former experiments. The results show the effectiveness of the proposed module from the viewpoint of transport efficiency, especially for cellular-type or process-type plant layouts.

We propose a motion planning method for cooperative transportation of a large object by multiple mobile robots in a 3 dimensional environment. This task has various kinds of problems, such as path planning, manipulation and so on. All of these problems can't be solved at once, since computational time is exploded. Accordingly, we divide a motion planner into a local manipulation planner and a global path (motion) planner, and design these two planners respectively, and we integrate two planners. Namely, we aim at integrating a gross motion planner and a fine motion planner. As to the local manipulation planner, we build a manipulation technique, which is suitable for mobile robots by position control. We compute conditions, in which the object becomes unstable during manipulation, and generate each robot's motion considering the robots' motion errors and indefinite factors from the planning stage. As to the global path planner, we reduce the dimensions of the configuration space (C-space) using the feature of transportation by mobile robots. We can find a solution with searching in this smaller dimensional C-space using the potential field defined in the C-space, and constraints of the object manipulation are considered as the potential function. We verify the effectiveness of our proposed motion planning method through simulations and experiments.

Learning approach is effective to design a agent that takes action autonomously. We propose to adopt teaching approach to design autonomous agents for RoboCup soccer tasks. Our teaching system consists of the ceiling CCD camera, SONY legged robots, and a PC for the teaching terminal. As a first step of the teaching process, we realized the self-localization of the robot using BP algorithm of feed forward neural networks.

We propose an architecture to accelerate reinforcement learning by a mobile robot. In order to solve the problem of explosion of learning time in former reinforcement learning methods, we introduce a mechanism to acquire and utilize a set of widely applicable generalized rules into a reinforcement learning system. The mechanism extracts these rules by a statistical analysis of experienced data from the learning process. By applying these rules, the learning process can be accelerated by reducing search space. Simulation results indicate the effectiveness of the proposed method.

Complicated tasks are often difficult to be expressed as single reward systems. In the human learning process, the relation between sensory inputs and action out-puts can be understood to have been acquired before-hand using an internal multidimensional reward system. We introduce reinforcement learning under multidimensional evaluation. The internal reward system includes both immediate evaluation and delayed rewards. The proposed architecture of the learning system is as a two layered Q-Learning system, which is combined with dynamic cell structure. We assume in the pushing task by a manipulator that information from touch sensors and motion detector of the vision system are available. The simulation showed that the acquired knowledge in the lower layer greatly helps to learn the pushing task.

An idea of considering an autonomous mobile robot as a virtual local network system is proposed in developing a remote fault diagnosis system of a mobile robot. Within the developed diagnosis system, a mobile robot is taken as one of the management objects of the network management system for autonomous mobile robots, and the simple network management protocol, which is widely used in network management system, is applied and adapted to the developed system as the communication protocol for exchanging diagnosis information. Moreover, by taking advantage of active moving and sensing ability of autonomous mobile robots, an effective fault inference method is also discussed.

This paper mainly discusses the characteristics of free sliding motion in releasing manipulation. Releasing manipulation is such a manipulation, in which an object is given initial velocities by striking and slides on a surface to stop at the pre-assigned destination under the action of friction. After the properties of releasing manipulation are given out based on our previous work, the trajectory, the relationship of the sliding motion and the object shape, and the motion monotonicity of any one object with arbitrary shape are intensively discussed. Several important results are originally obtained. Finally, a simple and effectual approach of determining the necessary initial velocity of the object is presented with the above obtained results.

Presents a methodology of environmental support for autonomous mobile robots using visual marks with memory storage. The mark makes up for insufficient function of sensing and recognition; self-positioning, positioning of objects, and deciding methods to operate objects. The mark proposed in this paper consists of a landmark part and a memory part. The landmark part is used to estimate the relative position and orientation between robots and the mark, and the memory part gives information about what it is, what tasks there are, and how to conduct the tasks. Task execution using the marks with real robots is described to show the effectiveness of the proposed methodology.

The properties of releasing manipulation are given. To improve the precision of object posture and decrease trial numbers, two iterative learning control schemes, learning control based on convergent condition (LCBCC), and learning control based on optimal principle (LCBOP) are designed in an experiment-oriented way. These two methods are based on a linearized model. The experimental results show that these methods are effective. After discussing the characteristics of these control methods, we postulate that in the case of where the system does not have enough knowledge, LCBCC is the only choice and to learn system knowledge, after enough experience has been acquired, LCBOP is better than LCBCC, form the view point of convergence rate and precision.

We propose a cooperative transportation method by quadruped robots with vibration in a 3-dimensional environment. In the case of cooperative transportation by legged robots, we must solve two problems; (1) how to avoid exerting excessive internal force on an object and how to deal with sensed values, the position and orientation of the object with vibration because the body of the robot vibrates in walking; and (2) how to decide its velocity that depends on several parameters such as step, walking cycle, and so on. Considering these problems, we construct the cooperation method of the transporting system with vibration. Our method consists of three aspects; firstly we decide how to suitably distribute the object's degree of freedom (DOF) to two quadruped robots. Secondly how to decide the robot velocity is described. Thirdly we create the vibration model aimed at the periodic gait of a quadruped robot by filtering the ingredient of the robot vibration from sensed values of the object deviation from its normal position on the robot. The created model enables us to estimate the deviation of object on the robot and the vibration parameters of the other robot. Moreover, we propose the step prevention motion of quadruped robot where its velocity is close to zero. The effectiveness of the step prevention motion and gait based on the vibration model is verified by some experiments.

In this paper, we propose a heterogeneous robot group for cooperative task execution. The "heterogeneous" robot group is composed of robots which have different motion algorithms. In this paper, we investigate behavior of the heterogeneous robot groups by simulations of multi-agent traveling salesman problem, which we hardly solve by centralized algorithms. Then we propose an algorithm, based on reinforcement learning, to adapt mixture ratio of robots driven by different algorithms. We verify the efficiency of the autonomous heterogeneous robot group by simulations.

Deals with a task-assignment method for cooperative transportation by multiple mobile robots in an open and dynamic area. The problem can be divided into three parts. The dynamic change of tasks, the dynamic change of the robot team composition, and the level of difficulty in finding the optimal solution. The authors propose the following approach: (1) by inputting sensor information to a "task template" and a "task-interaction template", tasks will be dynamically generated; (2) the planner consists of two parts, the task-assignment planner and the motion planner (the latter is made independently for each task); and (3) the task-assignment problem is solved by using a linear programming method based on the execution priority described in the "task templates". The effectiveness of the proposed method is verified by a cooperative transport simulation.

In this paper, we propose a method of an object manipulation by multiple mobile robots using sticks as tools. In the conventional cooperative work by multiple mobile robots, manipulation technique based on force-control has been proposed. However, mobile robots are moving by position-control, and motion errors can easily arise. Then, we build the manipulation technique, which is suitable for mobile robots by position-control. We propose the manipulation method without using sensor information, and consider the motion errors of mobile robots and the indefinite element of environment from the planning stage. We compute the conditions in which the object gets unstable during manipulation, and generate the motion of each mobile robot with these analyses. We verify the effectiveness of our proposed motion planning method through simulations and experiments.

This paper focuses on the manipulation of multiple objects, for example, to rake up many objects on a table, lift them up and put them in order, which is difficult to perform for a single manipulator system. This kind of operation becomes possible or much more effective by the cooperation of two manipulators. The lifting up operation of multiple objects by putting them between the two end-effectors is discussed. The use of visual or touch-sensory feedback for the operation, as humans do, cannot prevent the loss of balance for the manipulator system. For the purpose of safe operation, the kinematic analysis and a method of predetermining the pushing force are proposed. The experimental results indicate the effectiveness of the proposed method using simulations with various estimated errors.

We propose an algorithm for unforeseen obstacle avoidance by an autonomous sweeping robot. Sweeping means a motion that a robot covers a 2-dimensional area. When a mobile robot finds an unforeseen obstacle, it not only has to avoid collision but also sweep whole area including around the obstacle. In the proposed algorithm, a robot determines local area where path for sweeping should be arranged according to its limited sensing ability. By connecting the paths inside and outside the local area, the robot obtains a new total path. The local path re-planning saves heavy calculation to generate whole path again at online.

We propose an operation method to control mobile robot groups by a single human user, and build a system in which the human user and robots achieve tasks cooperatively. As for the commanding aspect, we divide orders from the user into four levels and consider the relationship between orders and autonomy of robots required. The main features of our method include: 1) the human user commands not just an individual robot, but groups of robots; and 2) our system has autonomy in proportion to user command levels and complements lack of command for the group (sometimes commands for the group is not sufficient for individual robot control). Regarding the monitoring aspect, we introduce a CCD camera system into our system and display information on a CRT display which shows the image of the work area. The user can monitor a remote environment and simultaneously obtain the information needed during operation. We verify the efficiency of our method and system by experiments.

Service robots are extensively installed with end-effectors, which require high energy to achieve a specific task. Robots require high-power energy sources that can meet several goals simultaneously. Given the technology of today a battery-driven robot cannot work for long on a single charge. To develop a new powerful battery technology may take many years. In this paper we present a dual-energized scheme called Hybrid Power Supply (HYPOS) that integrates the function of batteries and household electric system to supply power to a robot. This technique can be realized by the existing technology and is applicable to a variety of indoor applications. The paper includes the description of the prototype robot and the experiments that illustrate the effectiveness and practicalness of this proposed system.

We are going to analyze on the constraint among contacting points between robots and an object that is manipulated by the robot group. Constraint can be obtained by solving pseudo inverse of matrix filled by force data measured by all robots supporting one object. The result provides additional information for obtaining a relative positioning information to the object to ordinary constraint based on geometrical reasons. This analysis on the constraint has been verified by sensing system. The model explained here can be used for estimating contacting points, fitting coordinate system among robots, and making active sensing strategy for detecting the change of environment.

This paper proposes methods for recognizing three dimensional (3D) shape with range images and intensity images which are measured by multiple robots. Distributed sensing is a key technology for multiple robot systems. As sensory information for the robot system, range images and intensity images are both useful and complementary, and thus fusion of the two images is thought to be effective. In this paper each robot is assumed to have a range image sensor and/or an intensity image sensor. Planar regions, 3D edges and cylindrical regions are extracted by the distributed sensing system as robust features for 3D shape recognition. Methods of the feature extraction which are based on sensor fusion technology, and a prototype of a model matching method with the features are proposed. Experiments are performed to show the effectiveness of the proposed methods of feature extraction and model matching.

This paper deals with motion planning of cooperative transfer with regrasping by a group of car-like mobile robots. In order to realize this transfer task by actual car-like robots, three aspects should be considered: the nonholonomic characteristic of car-like robots, how to control the force and avoid too large a force by position-controlled robots, and control cycle of the system. Based on algorithms from previous works, the authors propose the following approach: 1) designing robot hand mechanism; 2) constructing hybrid planning architecture composed of centralized and decentralized system including an object motion observer. A simple transport experiment by an actual robot system is made to show the effectiveness of this mechanism. Validity of the proposed method is verified by a transport simulation.

In transporting various objects by multiple mobile robots we need to change the formation of robots and posture of an object. This planning depends on the mass and center of gravity of an object. Here we discuss the accuracy of the estimation of the mass and the position of the center of gravity of an object. Particularly we propose a method for estimating the height of the center of gravity which cannot be estimated by only one measurement. Validity of this strategy is verified by means of a real robot system.

This paper presents a novel design methodology of local communication system for cooperation in distributed mobile robot systems. Our goal is to design a local communication system so as to transmit task information to necessary robots in minimum time without excessive propagation. In this paper, we propose a layered methodology, i.e. design from spatial and temporal aspects based on analysis of information diffusion by local communication between robots. The spatial design gives the optimal communication area minimizing transmission time for various cooperative tasks. In the temporal design, we derive the information announcing time to prevent excessive information diffusion. Finally, the simulations and experiments demonstrate that the design methodology is effective in constructing an efficient local communication system.

In this paper, we propose an off-line planning algorithm for cooperative tasks of multiple mobile robots. Sweeping means a motion that a robot covers a 2-dimensional area by its effector. Sweeping of a whole work area is fundamental and essential task of mobile robots. For efficient cooperation, setting appropriate burden onto each robot is very important because interference of robots and overlaps of their effecters make efficiency low. The cost of sweeping depends on both sweeping ability of a robot and a shape of a work area to be swept. Evaluation and distribution of the cost are most important issues. In the proposed algorithm, the cost is evaluated by means of length on which robot should move. We introduce both edges of the configuration space and Voronoi diagram so as to compute paths in the whole area. We generate the a tour for traversing all the paths by applying the algorithm of the Chinese Postman Problem. According to the cost evaluation, appropriate paths of the tour are assigned to each robot. The efficiency of the proposed algorithm is verified by simulations and an experiment.

We aim at handling an unknown object by cooperating multiple mobile robots. The most important problem in this paper is obtaining a weight and mass center position of an object. Another important problem is to determine appropriate grasping points before handling. This method is proposed to avoid bad situations, such as making an object fall down, or some robots overloaded in handling. The algorithm we propose in this paper is a first step of grasping objects, which is "determination of initial grasping points". Initial grasping points are given by only a geometrical shape of an object. The robots are placed where the possibility that robots can lift the object with no trouble. This evaluation is based on the normal distribution model proposed in this paper. We are also going to discuss how to avoid and regrasp when initial grasping has failed. We show a simple numerical example of initial grasping and re-grasping, in planar object model.

This paper presents methods for fusing a range image and an intensity image. The fusion is thought to be an important technology for 3D recognition of an intelligent robot system. In this paper, planar and cylindrical regions are selected as the features from a range image and an edge from an intensity image, and the following methods of fusing the features are proposed and formulated: (1) extraction of planar and cylindrical regions from a range image as the pre-process of the fusion, (2) measurement of 3D edges by fusing a planar region and an edge, (3) update of parameters of a cylindrical region by fusing an edge. Some experiments show the effectiveness of these methods for 3D shape recognition.

We discuss various kinds of manipulation in this paper. Conventional manipulation is made when an object is rigidly grasped by a robot hand. Previously, different kinds of manipulation, in which a manipulated object is not fixed onto a robot hand, were studied. They have dexterity but uncertainty. In this paper, we give a classification of manipulation, and introduce graspless manipulation and releasing manipulation which are some dexterous manipulation methodologies. Finally, we propose a concept of "cost saving manipulation" which aims at a selection of the easiest and the most suitable series of various manipulation methods.

This paper surveys former studies on task planning of multiple mobile robots. Task planning algorithms are categorized into four from two issues: dimensions of tasks demands (point-reaching tasks and region-sweeping tasks), and the number of iteration of the task (one-time tasks and iterative tasks). Individual studies are surveyed based on the above categorization.

This paper is focused on solving the multiple robots motion planning problem in a robust way, whereas we say that a motion plan is robust if it can be used in spite of small variations in the motion context. After a critical review of their previous research on generating multiple robots motion plans (1995), the authors classify several "sources of instability" useful for establishing criteria for robustness. These sources include variations of the environment model, variations in the number of robots and paths, and variations in the motion parameters of the moving items. We define various "impact factors", that evaluate how much a variation affects a given plan. For example, a new path (for a robot) can be associated with a collision impact factor, that estimate how many collisions among moving objects may occur along that path. Hence, to evaluate the motion plan robustness, we define how quality values for motion plans are modified by the impact factors.

In this paper, we propose an off-line planning algorithm for cooperative tasks of multiple mobile robots. Sweeping means a motion that a robot covers a 2-dimensional area by its effector. Sweeping of a whole work area is fundamental and essential task of mobile robots. It is more effective if a robot can move an obstacle during a sweeping task as if we clean our room with relocating chairs. We can also consider that this is the simplest task which includes both point-to-point motion and sweeping. We model sweeping and relocation, and propose an algorithm to find appropriate path for robot and way of relocation of each obstacle. We apply the LT graph to solve the problem, which describes both motions of robots and blockades by obstacles in path-time space. We verify the efficiency of the algorithm through simulations and experiments.

The stability of an object manipulated by multiple robots (serial-link or wire-driven mechanisms) in contact tasks is investigated. We show that resultant force/moment applicable to the object through the contacts is represented as a polyhedral convex region in force/moment space. Then we propose a stability measure and a method of calculating it approximately by linear programming technique. We also present a linear programming-based algorithm to judge the possibility of excessive internal force in contact tasks by position-controlled robots.

This paper deals with an arrangement planning problem of mobile robots for handling unknown objects. To improve the flexibility of multiple a mobile robot system, these systems are now, expected to handle various kinds of objects. The authors propose a closed algorithm to judge whether a group of robots (robot group) can handle an object or not, by means of geometrical data of an object only. For this algorithm we also propose a method to generate a robot arrangement to maximize possibility of grasping an object with no trouble. These methods are based on the quantitative relationships between an arrangement of robots, load data to robots, and unknown mass and mass center of an object. Effectiveness of the proposed method is verified by a simple simulation.

One of the major emerging problems of distributed mobile robotic system is what kind of inter-robot communication to use, because of increasing robots integrated in the system. This paper aims to give an analytical view of this issue. The efficiency of local and global communication is compared based on the analysis of information transmission time to multiple robots. We will show that local communication is effective in environments where cooperative tasks are executed by multiple mobile robots in distributed fashion.

In this paper, first we propose a new kind of manipulation-releasing manipulation, that is, by some means, the manipulator gives the object initial translational and rotational velocities to make the object slide on a surface by its inertia under the action of friction. Second, we give the basic equations and analyze the motion of the object. Third, based on numerical calculation, we summarize the motion characteristics, especially for a rectangle. Finally, we perform experiments to verify the validity of this manipulation.

The authors aim at grasping and handling a large object by cooperating multiple mobile robots with various sizes, moving cost, and load capacity. In this paper the authors focus on the problems of deciding an appropriate grasping arrangement before handling operations. The authors propose this method to avoid bad situations, such as making an object fall down, or some robots overloaded in grasping and handling. The algorithm proposed includes two optimization problems; one is the "decision of initial robot arrangement," the other is the "decision of final robot arrangement." The difference between these optimizations is that the mass center of the object is recognized or not. The penalty index is defined to minimize the energy the system consumes and to maximize an index of stability. The authors have confirmed that the robots moved to the optimal arrangements in computer simulations and experiments.

When many mobile robots should achieve cooperation, a local communication system is considered appropriate from the standpoint of the cost and capacity of communication. This paper presents the optimization of the efficiency of local communication in environments where many mobile robots send out information stochastically. The optimal communication area is derived by minimizing the transmission waiting time calculated using the probability of successful information transmission. Computer simulations have been undertaken to verify the analytical results.

We address the problem of planning the motion of multiple autonomous robots, by analysing their behaviour in space and time. Proper representations have been studied for both domains, with a particular emphasis on the definition of some performance indexes to weight the goodness of a path concerning motion and time performances. Sublinear algorithms have been used for planning in space while reasoning in the temporal domain is based on a proper subdivision of the time axis that leads to polynomial algorithms.

Proposes an algorithm of dividing a work area into small pieces in order to make multiple mobile robots cooperate efficiently. Searching of a whole work area is the most fundamental and the most essential task of mobile robots. The authors expect that the cost of searching is shared by cooperation of multiple robots. In the proposed algorithm, searching motions of robots are represented by paths. Both edges of the configuration space and the Voronoi diagram are introduced so as to compute paths in the whole area. The authors generate a tour of the paths to traverse all the paths using the algorithm of the Chinese postman problem. The cost is estimated as the total length of the paths. By means of the cost evaluation, the appropriate paths are assigned to each robot. The efficiency of the proposed algorithm is verified by simulations.

This paper proposes a new strategy for manipulation of a rigid object by cooperation of multiple position-controlled manipulators using force control devices. The force control device consists of springs and a position-controlled micro-manipulator. Force control is achieved by controlling deflections of each spring by the micro-manipulator. A cooperative control algorithm considering the flexibility of macro/micro manipulators is proposed. After the differential equation of the error vector system is derived, a method of designing feedback gain matrices is shown for linearizing the system. To verify the efficiency of the algorithm, experiments are done on carrying an object by two industrial robots.

This paper deals with a motion planning of mobile robots during transferring a large object cooperatively by a group of multiple mobile robots (a robot group). This problem has the following characteristics: 1) a real time planning is essential because mobile robots move in an open and dynamic area in comparison to articulated robots; 2) both the object and the robot group need to avoid collision against obstacles; and 3) the object needs to be grasped stably by the robot group. The authors propose the following approach to solve this complicated problem: 1) regrasping strategy of the object is introduced in order avoid obstacles and to transfer the object stably; and 2) the motion planning is divided into two steps: the object and that of the robot group. The former step is accomplished by extending the virtual impedance method, which was proposed by authors. The latter step is realized by using nonlinear programming method, that optimizes a penalty index indicating the performance for obstacle avoidance and for stable grasping. Effectiveness of the proposed method is verified by a simulation of transferring a large circle-shaped object with three robots.

Fusion of a range image and an intensity image is a key technology for robot vision. This paper presents (1) strategy for the fusion, and (2) some fundamental algorithms of the fusion. The characteristics of the two images are discussed and the strategy of the fusion: "detect surfaces from a range image, and edges and vertices from an intensity image; and then fuse these features in 2D or 3D space" is insisted. Algorithms of (a) classification of edges, (b) merging of 3D surfaces by an edge, and (c) measurement of 3D edges, are proposed as the fusion algorithms based on the strategy. Experiments with a sparse range image and an intensity image indicate the effectiveness of the algorithms.

Local communication system is considered appropriate when many mobile robots should achieve cooperation, from the standpoint of cost and capacity of communication. This paper presents a design method of the optimal communication range for efficient local communication system. The analyses of optimization are made by minimizing the information transition time, first in the case of transmission to an arbitrary robot, and next, to multiple robots. Computer simulations have been undertaken to verify the analytical results.

This paper proposes a simple method for handling a single object by cooperation of two manipulators controlled by PID position controllers. Flexibility is essential to avoid excessive inner forces caused by the mutual positioning error between two manipulators. First, the way to design these flexible mechanisms is shown. Second, the closed loop structure consisting of two manipulators and the installed flexible mechanisms is kinematically analyzed. As an example, a cooperative system between a 6-DOF robot and a conventional crane is designed and an inverse kinematics algorithm is proposed. The method proposed here is also very effective for cooperation in distributed autonomous robotic systems.>

This paper proposes a strategy for handling a single object by cooperation of multiple robots controlled by PID position controllers. Since such a cooperative system has mechanical closed loops, installation of free joints or flexibility among robots is necessary to avoid excessive inner forces caused by the positioning error of each robot. First, the essential kinematic conditions to achieve the cooperation among position-controlled robots are shown. Second, the relationship between the positioning error of the handling object and that of each robot is analyzed. Finally, a mechanism for the cooperation of three mobile robots is proposed and its kinematic characteristics and statics are analyzed. The strategy proposed here is very effective and practical for cooperation of not only conventional industrial robots but also distributed autonomous mobile robot systems with non-holonomic constraints.>

The manipulability for wire suspended mechanisms is discussed. For kinematics of a wire driven mechanism, we need not only the geometrical constraints of wire lengths but also the force constraints, such as the wire tension which should be always greater than or equal to zero. First, the sufficient and necessary mechanical conditions corresponding to the force constraints are shown. Under these conditions, we can obtain the manipulability of a wire driven mechanism using almost the same methods as for a popular multilink manipulator. Second, a more practical evaluation index "set of manipulating forces" is introduced and the way of calculation of this index is explained. We also derive both manipulability indexes as for wire suspended mechanisms in the gravity field by modeling the gravitational force as a wire having tension corresponding to gravity. Numerical examples are given to explain the proposed indexes and to show their validity. The method is expected to be effective in designing and task planning of wire driven systems including wire suspended mechanisms.>

This paper proposes a distributed and autonomous control method for generating the shape of a group that consists of multiple mobile robots. This control method is called linear autonomous system (LAS). With LAS, the controllability of group shape can be defined. This is because a decision of a shape of the group corresponds to designing a potential field that is spread on a space of relative distance between mobile robots. Since each mobile robot has parameter for designing the spread potential field, a shape of the group can be adapted to various situations by means of changing the parameters with respect to state of environment, for example, the position of wall, a velocity of an obstacle, etc. Effectiveness of this control method is verified by a computer simulation. It means that a mobile robot is captured by a group that consists of multiple mobile robots.>

For the cooperation in a large system with many mobile robots, local communication system is considered appropriate in terms of the cost and capacity of communication. The behavior of robots has a respectable effect on the efficiency of communication in such a local communication system and it is essential to know what kind of behavior robots should take to realize efficient information transmission for cooperative tasks. We introduce a simple group behavior for the purpose of improving the communication efficiency. This paper analyses the effect of group behavior on the communication performance, and derives differential equations describing information diffusion among robot groups. The optimal group size to transmit information to a desired number of robots is obtained front these equations. The effectiveness of the analysis is verified by computer simulation. We also show a self-organization algorithm for group forming designed for local communication system.>

This paper proposes a new algorithm for the manipulation of a rigid object by cooperative control of multiple flexible manipulators. Assuming that the flexibility exists only at the force sensor attached to the tip of the manipulator, each manipulator is modeled as a rigid manipulator with six springs at the tip. A cooperative control algorithm considering the flexibility is proposed. After the differential equation of the error vector of the system is derived, the method of determining the feedback gain matrices is shown for linearizing the system. To verify the efficiency of the algorithm, the experiments are done on carrying an object held by two parallel flexible beams.

A motion planning method for robot groups is presented. First, groups are classified into a group on common partnership (P-group) and a group in shape (cluster) based on types of common factors among members of the same group. The concept of cohesion is proposed to express changeability of clusters. Next, a motion planning method with dynamic grouping, which changes number of cluster in the group based on cohesion, is presented. The approach is implemented using the virtual impedance method. The effectiveness of the method is verified by simulation results.

The dynamics of a robot is highly non- linear because of coupling torques between joints. Since coupling torques result in disturbance to control system of a robot, the elimination of the coupled part of the torques has been studied in robot control. On the contrary, in this paper, we propose a method of utilizing the coupling torques for the the purpose of control of robots. We intro- duce a concept of dynamic redundant degrees of freedom, which can modify characteristics of a robot dynamics task-independently. We utilize dynamic redundant degrees of freedom both to minimize joint torques in the least square sense or to generate great momentary force at the end-effec- tor of a robot. The effectiveness of utilizing dynamic redundancy'' is verified by both simula- tions and experiments.

Detecting three dimensional motion is one of the most important issues on robot vision. In this paper, an essential equation, the motion-range equation, is introduced for detecting 3D motion from 'range images'. The equation is represented in linear form against 3D motion parameters. Using the equation, the motion parameters are directly obtained without detecting the positions of an object. Statistical analysis is made and computational method is established by means of the equation. Analysis of the equation is performed. Experimental results on actual range images prove that the motion detection method described is simple and efficient.>