We develop a novel hall-effect-based six-axis force/torque (F/T) tactile sensor integrated into the fingertip of robotic hands. When the robotic hands performs the grasping tasks in an unstructured environment, the visual information plays a main role in sensing the external properties of the objects. However, the various intrinsic properties of the objects such as softness, roughness, mass distribution, and weight cannot be measured properly only with the visual information. To detect the various force information in performing diverse tasks, we aim to implement the six-axis F/T fingertip tactile sensor with hall-effect-based principle. The experimental results demonstrate that the proposed sensor can measure the six-axis F/T with average errors of about 3.3%. In addition, it is observed that the effect of stray field can be shielded by applying a soft magnetic shielding film to the sensor.

EtherCAT has been widely adopted in industrial automation and motion control owing to its real-time performance and flexible topology. However, an EtherCAT network with devices from different vendors requires extensive software modification which eventually increases development costs and effort. To address this issue, this paper presents a real-time control architecture focusing on a software-defined approach to easily reconfigure EtherCAT devices with minimal user intervention. This is achieved by simplifying the integration of EtherCAT slaves while exposing required parameters in a configuration interface through an API based on open-source EtherCAT master. We also provide a real-time variation of the POSIX library for a hard real-time multi-tasking environment considering task synchronization. Moreover, the real-time publish-subscribe protocol is also utilized to ensure seamless communication with devices outside of the EtherCAT network. To validate feasibility, practical example involving control of multi-axis robots and real-time performance analysis has been conducted.

We develop a miniature suction-gripper with the goal to realize the novel robotic surgical instrument that can grip slippery and flexible peripheral nerves. In developing the instrument, we place a priority on devising the method that can robustly grip the nerve bundles during the surgical operation for the peripheral nerve. Also, we concentrate to investigate the working principle being able to minimize nerve damages that might be caused when manipulating the nerve. In this study, as the most suitable method to achieve the goal, we scheme to utilize the suction mechanism. Because it can non-invasively grip the nerve based on negative pressure, no external force is applied to the nervous tissues. Therefore the peripheral nerve can be manipulated without serious nerve damage (e.g. crush injury and stretch injury). To improve the gripping ability of the proposed suction gripper, two different types of microneedle arrays are applied to the suction-tips: passive-microneedle (PMN) arrays and active-microneedle (AMN) arrays. Since the most outer membrane of the nerve can be anchored by the penetrated PMN and AMN, the gripper can grip the nerve more robustly. The designed suction-gripper is fabricated as a functional prototype, and its working performances are assessed with in-vitro and in-vivo animal experiments. The experimental results well demonstrate the practical effectiveness of the proposed method and its applicability to the neurosurgical robot for the peripheral nerve.

We develop a novel cube-shaped finger-wearable haptic interface named as HaptiCube. With the aim of implementing the tactile device with improved functionality and wearability, we focus on designing the device to have two characteristics: multi-DOF force feedback displayability and large force capability with compact and lightweight structure. In designing the device, we mainly consider the type and configuration of actuator and driving mechanism, since both have a great effect on the size, weight, and output force of the device. As the actuator, we select the shape memory alloy exhibiting high energy density. And, as the driving mechanism, two different types of compliant mechanism are designed for two important functions: to convert contraction of the SMA to the desired motion as a motion guide and to apply bias-force to the SMA as a bias-spring. The device is designed as the miniature interface that can display 3-DOF pressure and 2-DOF shearing force to user's fingerpad. And, it is implemented as the functional prototype with the total weight of 26 g including actuators and all mechanical components. The experimental results on working performances (e.g. stroke, output force, and bandwidth) demonstrate that the device has superiority in terms of multi-DOF displayability, compact-sizability and wearability.

This paper presents preliminary results of a handheld device to assist the insertion of intra-fascicular planar electrodes into a peripheral nervous system. The developed device consists of two units, a nerve holder and an electrode inserter. We introduce design considerations, features, and underlying mechanisms of the device. User tests and animal experiments show that users can easily and accurately adjust the insertion position and direction of nerve electrodes while manipulating the device in 3D, and that planar electrodes are successfully inserted into sciatic nerves of rats. We hope that the proposed device will help neural engineering researchers and scientists to simplify the surgical process and produce consistent experimental results.

When a robotic manipulator is controlled, computing gravity force of the robot is the primary issue. Exact model parameters are not easy to be known in the practical robot system due to the uncertainty of the robot dynamics. Hence, the gravity force is presented by a combination of gravity regressor and robot dynamic parameters and is compensated by the estimation of uncertain robot dynamic parameters. Previous researches conducted estimation by using transpose of gravity regressor and full form of dynamic parameters which is not general form however this paper estimates the gravity force using the generalized gravity regressor which is regardless of the dimension and structure of the robot under the quasi-static state. Once the estimation is completed, the estimated value can be used to compute the gravitational force and control the robot. It is shown that the generalized decomposition of gravity regressor and estimation process. The results are validated through an experiment by implementing the algorithm on an upper-body dual arm robot.

In this paper, a novel sEMG decoder was proposed for estimating the detailed human intentions. For the use in practical applications, an sEMG decoder needs to have a high decoding performance, a robustness to the changes of electrode positions, and a capability to extract detailed and continuous intentions behind human motions. The new decoder satisfies all these needs by using a new supervised feature extractor, which was originally designed for discrete output values but modified to deal with the continuous values while maintaining the high performance and the robustness to the change of input variables resulting from the change of electrode positions. Experiments for decoding detailed human intentions, i.e. the angle between phalanges in a single finger, confirms that the high performance of the proposed decoder and that this performance is maintained when the electrode position changes.

In this paper, we present a real-time motion and force capturing system for tele-operated robotic manipulation that combines surface-electromyogram (sEMG) pattern recognition with an inertia measurement unit(IMU) for motion calculation. The purpose of this system is to deliver the human motion and intended force to a remote robotic manipulator and to realize multi-fingered activities-of-daily-living (ADL) tasks that require motion and force commands simultaneously and instantaneously. The proposed system combines two different sensors: (i) the IMU captures arm motion, (ii) and the sEMG detects the hand motion and force. We propose an algorithm to calculate the human arm motion using IMU sensors and a pattern recognition algorithm for a multi-grasp myoelectric control method that uses sEMG signals to determine the hand postures and grasping force information. In order to validate the proposed motion and force capturing system, we used the in-house developed robotic arm, K-Arm, which has seven degrees-of-freedom (three for shoulder, one for elbow, and three for wrist), and a sixteen degrees-of-freedom robotic hand. Transmission Control Protocol Internet Protocol (TCP/IP)-based network communication was implemented for total system integration. The experimental results verified the effectiveness of the proposed method, although some open problems encountered.

This paper addresses a control method for friction-existing robot manipulators and safe motion with its environment. In order to control the robot manipulator with unknown effects, a time-delay control(TDC) method that eliminates the nonlinear effects is used to control the joint torque servo. Although the TDC is very adaptive in nonlinear systems, there is limitation of the TDC in a high friction robot manipulator; hence, a friction model is considered. A collision detecting method is proposed to secure safety for human and robot-interacting environment. Using the torque sensor attached at the joints of the robot arm, the collision is detected more effectively. After detecting collision, a safety reaction method is applied. A torque sensor based 3-joints robot arm is used to verify the performance of the proposed methods.

When one uses a hand-held tool, the fingers often make the tool to be in contact with the palm in the form of multi-contact manipulation. Multi-contact manipulation is useful for object-environment interaction tasks because it can provide both powerful grasping of the object body and dexterous manipulation of the object end-effector. However, dealing with the internal link contact with the object is not trivial. In this paper, we propose Reactional Internal Contact Hypothesis that regards the internal contact force as a reaction force so that the desired finger force can be reduced. By taking a handwriting task as an example, optimal configuration search and grasping force computation problems are addressed based on this hypothesis and validated via dynamic simulation.

This paper proposes an integrated control method including learning with an ellipsoid function and impedance controller for rehabilitation using power-assisted robotic devices. The proposed controller consists of two parts of a primary algorithm, which are ellipsoid regression method for re-designing trajectory and impedance controller with pseudo mass/inertia. The ellipsoid regression method generates reference impedance profiles though acquiring motion and force trajectories during rehabilitation tasks assisted by therapists. The assisted force is controlled by impedance controller during execution of rehabilitation task using a concept of pseudo mass/inertia. The proposed method offers the power-assisted rehabilitation as guided by therapist, without consistent help from the therapist or other assisters. The proposed control method is validated by experiments throughout a 2-DOF rehabilitation robot, KULEX-2DOF(KIST Upper Limb Exoskeleton - 2DOF).

In this paper, the grasping force control of a robotic hand based on a torque to velocity transformation using force/torque (F/T) sensors with gravity compensation is addressed. The force controller is designed and the task force is transformed into command torque. Then, the torque is converted into command velocity for the velocity servo control through torque to velocity transformation. Inner velocity controller is modeled, and the additional torque due to the gravity effect is augmented using superposition principle; then, the analysis of the overall system and controller is conducted through the grasping experiment. As a result of this, competent results are obtained.

Human's action strategy is a good source of robot controller design. For there is no decisive criterion on balance control during manipulation tasks, human motion data are obtained and analyzed in this paper. Based on the observation of the center of mass (CoM) being proportional to target object distance but limited inside the supporting polygon, the bound-proportional CoM planner is proposed. Along with the CoM planner, whole-body balance and grasping controller for a dualarm robot is suggested in a simple and computationally efficient structure. Dynamic simulation is conducted for validation, and showed competent results.

This paper proposes a strategy for grasp and manipulation of unknown objects. In order to derive force relations of fingers, the groped shape of soft fingers is introduced. The groped shape is not equal to the real object shape, but is tightly related to the force equilibrium of fingers. By considering contact forces of the groped shape, a simple control parameters can be derived. The manipulation of an object is easily accomplished by embedding the concept of virtual centroid into the grasp control to redistribute internal forces. With these concepts, an object can be easily translated, rotated, and manipulated by relocating fingers. The proposed method is verified with experiments.

There are many difficulties in dexterous object manipulation by multi-fingered hands, due to redundant degree-of-freedom of the entire system and uncertainties in interaction with the object. In this paper, however, 3D object manipulation without any external sensors are attempted. Under the assumption of point contact without rolling, the object position and orientation are computed in relative sense and used as the feedback for object manipulation. Overall system dynamics including two cone-shaped finger robots and an arbitrary object is modeled, and the closed-loop system stability is analyzed based with the proposed controllers for stable grasping and object position/orientation control. In order to validate the proposed method, dynamic simulation is conducted, and showed complacent results.

In this study, we evaluated a fast training algorithm to decode human hand configuration from sEMG signals on the forearms of five subjects. Eight skin surface electrodes were placed on the forearm of each subject to detect the sEMG signals corresponding to four different hand configurations and relax state. The preamplifier, which has 100 - 10000 times amplification gain and a 15 - 500 Hz bandpass filter, was designed to amplify the signals and eliminate noise. In order to enhance the performance of the classifier, feature extraction using class information was developed. The randomly assigned non-update learning method guarantees high speed classifier learning. The algorithm has been verified by experiments with five subjects.

This paper presents a development of an anthropomorphic robot hand, `KITECH Hand' that has 4 full-actuated fingers. Most robot hands have small size simultaneously many joints as compared with robot manipulators. Components of actuator, gear, and sensors used for building robots are not small and are expensive, and those make it difficult to build a small sized robot hand. Differently from conventional development of robot hands, KITECH hand adopts a RC servo module that is cheap, easily obtainable, and easy to handle. The RC servo module that have been already used for several small sized humanoid can be new solution of building small sized robot hand with many joints. The feasibility of KITECH hand in object manipulation is shown through various experimental results. It is verified that the modified RC servo module is one of effective solutions in the development of a robot hand.

Since bio-electric signals such as surface EMG are easily influenced by undesired artifacts and experimental environments including various electrical noises by peripheral devices, the amplifier is an issue of great importance. Although most commercial surface EMG amplifier systems provide high performance in acquiring electric bio-signals, they are not convenient for myoelectric control applications because they usually use wet-type electrodes that should be attached to the skin individually and there are also some limitations to possible modifications. In this study, we propose and develop a surface EMG interface that employs dry-type electrodes, a single supplied circuit for reduced weight, two voltage followers to improve input impedance, and a modified driven-right-leg circuit using a virtual ground circuit. By adapting a wearable band-type interface. The EMG electrodes can be reused while offering high performance corresponding to that of commercial products. The developed surface EMG system was successfully applied to decode human motion intentions of eight different configurations and a rest condition by using a fast training algorithms in a non-targeted manner.

This paper addresses a torque control method in a high friction robot manipulator. A stiction feed-forward compensator is proposed to eliminate the control problem caused by the nonlinear friction and disturbance. In order to control a robot manipulator with unknown effects, a time-delay control method is used to control the torque. One degree of freedom flexible joint robot manipulator with a joint torque sensor is used to show the performance of the proposed control method.

For a robot to learn complex movement skills, programming by demonstration and/or learning by trial and error is necessary. Measuring the complexity of such movement skills is important to decide the appropriate learning model, and the required size of dataset and additional prior knowledge. To deal with measuring the complexity of movement skills for robots, we propose an information-theoretic complexity measure. By modeling proprioceptive as well as exteroceptive sensory data as a multivariate Gaussian distribution, movement skills can be modeled as a probabilistic model. Next, complexity of the movement skills is measured by using neural complexity. In addition to the original neural complexity measure, endogeneous changes in time of the movement skills are modeled by sampling in time and modeling as individual random variables. To evaluate our proposed complexity measure, several experiments are performed on real robotic movement skills.

In recent, control approaches for the human-like behavior in the field of service robotics have been attracting considerable attention, since most humans or animals perform various tasks uncomplicatedly. Hence simple control methods based on gaining a physical insight into human reaching movement in redundancy of DOFs have been proposed. In comparison with the conventional approaches, the proposed method tries to control directly robotic systems in task-space with the control signal composed of linear superposition of three terms 1) joint-damping, 2) virtual spring, and 3) virtual damper in task-space. In particular, our work contains a muscle tension effect of a human under the gravity. This give birth to energy efficient natural motions avoiding problems on repeatability of the motion and ill-posedness problems emerged in most of redundant DOF systems. Thus, this paper exhibits expendability of the position control into the orientation control and compliant behavior. It is verified with a real robotic arm that satisfies human-like movements and motion repeatability under kinematic redundancy of joints.

Redundant manipulator control usually brings about a lot of complexity. This paper proposes a quite simple approach for concurrent set-point regulation of position and orientation of a redundant manipulator using the virtual spring-damper hypothesis, which offers human-like movements without solving the inverse dynamics. For orientation, quaternion representation is applied to give singularity-free orientation control. Augmenting quaternion feedback to the state vector of the system, the stability is analytically proved, and dynamic simulation is conducted for validation of the method. Competition between position and orientation control is also briefly discussed based on the simulation results.

This paper proposes a novel fast classification system consisting of feature extraction and classifier to decode human hand configurations from multi-channel surface electromyogram (sEMG) signals that allows real-time classification of human movement intention as well as prothesis control. In order to enhance the learning speed and the performance of the classifier, we used a supervised feature extraction method (called class-augmented principal component analysis) and a fast learning classifier (called extreme learning machine). Experimental results show that the proposed classification system quickly learns and decodes the human hand configuration with about 92% accuracy.

In this paper, we have developed a novel control law to exhibit human-motion characteristics in redundant robot arm-trunk systems for reaching tasks. This newly developed method nullifies the need for the computation of pseudo-inverse of Jacobian while the formulation and optimization of any artificial performance index is not necessary. The time-varying properties of the muscle stiffness and damping as well as the low-pass filter characteristics of human muscles have been modeled by the proposed control law. The newly developed control law uses a time-varying damping shaping matrix and a bijective joint muscle mapping function to describe the human-motion characteristics for reaching motion like quasi-straight line trajectory of the end-effector and symmetric bell shaped velocity profile. The aspect of self-motion and repeatability, which are inherent in human-motion, are also analyzed and successfully modeled using the proposed method. Simulation results show the efficacy of the newly developed algorithm in describing the human-motion characteristics.

There are many difficulties in operating a humanoid which has high degree-of-freedom and instability in balancing its body. In addition, due to the shape of a humanoid, it is expected to have motions like a human. In order to overcome its operational difficulties and to provide a humanlike motion, a teleoperation with the motion imitation is studied in this paper. Specifically, a framework for online generation of a footprint from a human walking motion is proposed. The human walking motions acquired from a motion capture device are parameterized and normalized to give a human independent foot motion. The normalized parameters are restored by a humanoid considering its hardware limit. The restored footprints generate a walking trajectory of a humanoid, which imitates the human walking motion in terms of the footprint. Experiments are conducted with MAHRU-R, a humanoid robot developed in KIST.

Recently, biologically inspired control approaches for robotic systems that involve the use of central pattern generators (CPGs) have been attracting considerable attention owing to the fact that most humans or animals move and walk easily without explicitly controlling their movements. Furthermore, they exhibit natural adaptive motions against unexpected disturbances or environmental changes without considering their kinematic configurations. Inspired by such novel phenomena, this paper endeavors to achieve self-adapting robotic arm motion. For this, biologically inspired CPG based control is proposed. In particular, this approach deals with crucial problems such as motion generation and repeatability of the joints emerged remarkably in most of redundant DOF systems. These problems can be overcome by employing a control based on artificial neural oscillators, virtual force and virtual muscle damping instead of trajectories planning and inverse kinematics. Biologically inspired motions can be attained if the joints of a robotic arm are coupled to neural oscillators and virtual muscles. We experimentally demonstrate self-adaptation motions that that enables a 7-DOF robotic arm to make adaptive changes from the given motion to a compliant motion. In addition, it is verified with real a real robotic arm that human-like movements and motion repeatability are satisfied under kinematic redundancy of joints.

This paper presents a characterization of the Hokuyo UBG-04LX-F01 laser rangefinder (LRF). The Hokuyo LRFs are suitable for a small mobile robot due to their small size and light weight. In particular, the scan frequency of Hokuyo UBG-04LX-F01 is higher than those of the previous LRFs in its price range. However, there is no research on characterizing this LRF for the convenience of practical use. Therefore, this paper characterizes the Hokuyo UBG-04LX-F01 and analyzes the effect of the target properties, such as incidence angle, color, brightness, and material, by measuring the distance to a target. The experimental results show that the measurement error is strongly influenced by the incidence angle and the brightness of the target surface. From the experimental results, a calibration model is also proposed to measure the accurate distance to a target.

This paper describes and discusses the preliminary results of a behavioural study on robot social acceptability, which was carried out during a public demonstration in South Korea. Data was collected by means of direct observation of people behaviour during interaction with robots. The most interesting result to emerge is that of young people: they tended to react to the robots presence with extreme curiosity and, quite often, to treat them aggressively. In this paper, the word bullying is used to describe any kind of improper and violent behaviour, intended to cause damages or impede the robot operation. It is the authors' opinion that if not tackled appropriately, abuses towards robots may become a serious hindrance to their future deployment, and safety. Hence, the necessity to tackle this issue with dedicated solutions during the early phases of design.

This work presents a methodology to generate dynamically stable whole-body motions for a humanoid robot, which are converted from human motion capture data. The methodology consists of the kinematic and dynamical mappings for human-likeness and stability, respectively. The kinematic mapping includes the scaling of human foot and Zero Moment Point (ZMP) trajectories considering the geometric differences between a humanoid robot and a human. It also provides the conversion of human upper body motions using the method in. The dynamic mapping modifies the humanoid pelvis motion to ensure the movement stability of humanoid whole-body motions, which are converted from the kinematic mapping. In addition, we propose a simplified human model to obtain a human ZMP trajectory, which is used as a reference ZMP trajectory for the humanoid robot to imitate during the kinematic mapping. A human whole-body dancing motion is converted by the methodology and performed by a humanoid robot with online balancing controllers.

There are many difficulties to remotely control a robot over Internet such as transmission time delay, limitation of bandwidth, and packet loss. In this paper, we propose a novel remote control architecture and a communication architecture for Internet-based robots, which is insensitive to the transmission time delay and packet loss. The proposed architecture guarantees enhanced remote control by providing the perfect copy of the status of remote robot at real-time. The communication protocol has a flexible packet format and various packet sizes at runtime for robust and reliable control mechanism. The architecture together with the protocol provides improved control performance. Experiments shows that the effectiveness and applicability of the internet-based robot with the proposed architecture.

We present a novel filtering method for building a grid map using sonar sensors. Recognizing that conflicting information from sonar sensor readings is the main reason of poor map quality, we established a proposition that put the conflicting information in order. Based on the proposition, we effectively filtered sonar readings that cause conflict. In addition, some information of filtered readings were not discarded but reprocessed to enhance the quality of the map. We call this filtering and reprocessing operation the conflict evaluation method. We evaluated the proposed method by experiments under various conditions.

This paper presents an algorithm for visual SLAM based on a visual plane, a reliable grouping of salient visual features along sonar line features. The grouping of visual features improves data association and reduces the number of landmarks against individual visual features. To accomplish this, we propose three techniques: 1) selection of visual features which are invariant to image changes in indoor environment and suitable candidates for the visual plane, 2) extraction of sonar line features with current sensor data, which filters out uncertain outliers efficiently and 3) a scheme on grouping visual features with respect to sonar line features and maintaining database of the extracted visual planes for reliable data association. We integrate above three techniques into one framework and propose a SLAM algorithm for the visual planes. Experimental results in two types of real home environment show that the algorithm can successfully be executed with no human intervention.

Our previous work, SLAM with visual plane, allowed correct data association and computationally feasible solution for vision-based SLAM. In this paper, we propose a scheme of generating a hybrid visual map based on the visual plane framework. The hybrid visual map has two levels of map representations: 1) absolute map representation of distinctive visual planes via EKF-SLAM and 2) relative map representation of dense visual features for each visual plane via sparse information filter update. It can inherit the advantages of the visual plane by maintaining the absolute map. Moreover, the relative map can reconstruct a 3-D map of visual features efficiently without loosing dense visual information. The performance of the proposed method was verified by the experimental results of consistent hybrid visual maps in two real indoor environments.

Humanoids have a large set of basis behaviors and could perform various tasks. Controlling a humanoid with many degrees of freedom and behaviors consumes a lot of resources. By exploring the external service servers on the network, the ability of a humanoid is extendable beyond its resource constrains. This system is named network-based humanoid. In this paper, the network-based humanoid architecture (NBHA) is proposed to provide a core framework to develop this network-based humanoid system. It creates a system where humans, robots, and external service servers can interact without complicated configuration. Using this architecture, behaviors can be created, added and removed dynamically. A number of experiments have been conducted successfully by using JadeLeap middleware, FIPA standard and JESS rule engine on our humanoid. Experimental results show that the proposed architecture provides the extendable behavior control system in the network environment, decreases the development time for adding new services and it decreases the time for network connection of robots and user devices

In this paper, a network-based humanoid architecture (NBHA) is proposed. NBHA is a distributed architecture that based on multi-agent technology to provide a systematic method for developing humanoid software system, external services and coordinating them in an effective manner. Behaviors of these humanoids and their surrounding network environment can be created, added and removed dynamically via a simple scripting method. Some experiments on our network-based humanoid are presented in this paper. Experimental results show that the multi-agent architecture is a good selection for developing this system. It provides an extendable behavior control method in the network environment and it decreases the development time for adding new services. Using this distributed multi-agent architecture, roles of a humanoid, method for coordination and performing scenario can be changed easily

Edges in topological maps have rich information such as shape, numbers of obstacles, locations of obstacles which can be used for a data association. However, no systematic approach on using the edge data for the data association has been reported. This paper proposes a systematic way of utilizing the edge data for data association. First, we explain a Local Generalized Voronoi Angle(LGA) to represent the edge data in 1-dimension. Second, we suggest a key factor extraction procedure from the LGA to reduce the number by 27-28 times for computational efficiency using the wavelet transformation. Finally we propose a way of data association using the key factors of the LGA. Simulations and experiments show that the proposed data association algorithm yields higher probability for similar edges in computationally efficient manner.

In this paper, we present a visual navigation algorithm by combining visual localization with the extraction of valid planar regions from a single camera of an indoor mobile robot. Only two pairs of natural line and point are used for the visual localization to take the advantage of fast detection. To track a given landmark model, Lucas-Kanade optical flow algorithm is applied by using gradient descent. We use the odometer data combined with visual information to determine the height of the landmark features. On-ground image features are used to calculate the homography between two image frames and to detect the planar region for navigation. Experimental results show the robustness of the method with respect to image illumination and noises. The performance in indoor environments shows the feasibility of the proposed visual navigation algorithm in realtime.

Some of manufacturing tasks, such as sawing, often require continuous impulsive motion. In the case of sawing, such impulsive motions can be observed between the teeth of the saw and the object. The amount of the external impulse exerted on the object has been treated as an important control parameter. At the same time, the internal impulses experienced at the joints should be taken into account to avoid serious damage or injury at the joints of robot. The purpose of this paper is to improve the efficacy of sawing by using dual arms. For this, we suggest an external impulse model, and introduce a new concept of effective mass that accounts for the hardness of the object to corroborate the effectiveness of the proposed chip model employed in the derivation of the external impulse model. Closed-form internal impulse models are also proposed for both single and dual arms. Based on these models, the paper proposes a new measure for internal impulse. A normalized impulse ellipsoid reflecting the velocity direction is employed to visualize the impact geometry. Finally, we identify the optimal sawing region, wherein there is a maximum amount of external impulse and a minimal amount of the internal impulse. Simulation and experimentation demonstrate that the dual arm exhibits a better sawing performance than a single arm, in terms of external and internal impulses.

This paper proposes the indirect zero momentum position (ZMP) controller for biped robot systems and proves its disturbance input-to-state stability (ISS). The ZMP control has been used as a standard method for stable walking control of biped robot systems. Since the ZMP information consists of position and acceleration of the center of gravity (COG) for a biped robot system, the ZMP can be indirectly controlled by the motion of COG. In this paper, the reference COG planner is developed by solving the reference ZMP differential equation. The indirect ZMP controller is proposed to derive the desired motion of COG from the reference ZMP trajectory and the COG error (the difference between the reference and real COG). The ISS of the proposed indirect ZMP controller is proved for the simplified biped robot model. The robustness of the proposed indirect ZMP controller is shown in simulation.

Some of manufacturing tasks such as sawing task often require continuous impulsive motion. In case of sawing task, such impulsive motions can be observed between the teeth of the saw and the object being sawn. The amount of the external impulse exerted on the object is treated as an important control parameter in the sawing task. The purpose of this work is to show the efficacy of sawing task by using a dual-arm. For this, a new concept of effective mass is introduced to model the impact phenomenon in the sawing task. Using this concept, the external impulse model of sawing tasks is suggested. The optimal sawing region is identified in which the amount of external impulse is maximized. It is demonstrated through simulation and experiment that the dual-arm exhibits better sawing performance over a single arm in aspects of external impulse.

In this paper, we present a simple method for visual localization of indoor mobile robots based on a natural landmark model. Only two natural lines and an intersection point are used for localization to take the advantage of fast detection. To track the landmark model, Lucas-Kanade optical flow algorithm is applied by using gradient descent. Then, by adopting reasonable assumption for indoor environments, a quick localization method for mobile robots from correspondent landmark is proposed in a linear technique. Experimental results that demonstrate the robustness of the method with respect to image illumination and noises are also presented. The performance in indoor environments shows the feasibility of the proposed localization algorithm in real-time.

This paper deals with modeling and analysis for the landing motion of a human-body model. First, the dynamic model of a floating human body and the impact model are derived and the external impulse exerted on the ground as well as the internal impulse experienced at the joints of the human body model are investigated. Second, a motion planning algorithm exploiting the kinematic redundancy is suggested to ensure stability in terms of ZMP stability condition during a series of landing phases. Four phases of landing motion are investigated. In simulation, the external and internal impulses experienced at the human joints and the ZMP history resulting from the motion planning are analyzed for two different configurations. A desired landing posture is suggested by comparison of the simulation results.

In a humanoid robot system, many human-body motions such as walking, running and jumping require large power. To achieve a high power-to-weight ratio, this paper proposes a new design of the leg mechanism using parallel kinematic chains involving redundant actuators. The kinematics for the leg mechanism is derived and a kinematic index to measure force transmission ratio are introduced. It is demonstrated through simulation that incorporation of redundant actuator into the leg mechanism enhances the power of the mechanism approximately 4 times of the minimum actuation. The leg mechanism is developed and has been integrated into the biomimetic system for the purpose of payload enhancement.

A behavior-based control and learning architecture is proposed, where reinforcement learning is applied to learn proper associations between stimulus and response by using two types of memory called as short Term Memory and Long Term Memory. In particular, to cope with delayed-reward problem, a knowledge-propagation (KP) method is proposed, where well-designed or well-trained S-R(stimulus-response) associations for low-level sensors are utilized to learn new S-R associations for high-level sensors, in case that those S-R associations require same objective such as obstacle avoidance. To show the validity of our proposed KP method, comparative experiments are performed for the cases that:(1) only a delayed reward is used, (2) some of S-R pairs are preprogrammed, (3) immediate reward is possible, and (4) our KP method is applied.

This paper proposes an autonomous motion controller for mobile robots. It combines a biologically inspired motion planner and a nonlinear feedback controller in order to make a simple and practical motion controller in natural unknown environments. The motion planner part is designed in the frame of behavior-based scheme and adopts the biological concept "homeostasis". It plays the role of determining desired temporal target posture and modifying controller's gain parameters. The other nonlinear controller part drives the robot to the given target posture from the planner. As a result, the stable nonlinear feedback controller in ideal obstacle free space becomes practical one in natural environments constrained by obstacles. The proposed controller is simple mainly due to its behavior-based characteristics and stable due to the feedback controller considering robot's physical constraints. Simulated results and some experimental feature for autonomous navigation of the differential drive mobile robot, named "MARI", are shown for the present.

In this paper, an algorithm for hyper symmetric environment simultaneous localization and mapping (SLAM) is developed based on the generalized Voronoi graph. The hyper symmetric environment is a challenging environment for the SLAM and the most difficult problem on this is a data association. To redeem this problem, we propose three techniques. The first one is a breadth first node navigation algorithm which highly reduces the complexity of the data association. The second scheme is an odometry calibration method which converts untrustable odometry into reliable one. The third method is a multi layered data association scheme. We integrate above three techniques into one framework and propose a SLAM algorithm for the hyper symmetric environment. The simulation result shows that the proposed algorithm can successfully cover a large hyper symmetric environment under 20% odometry uncertainty.

In this paper, we present a simple linear method for localization an indoor mobile robot based on a natural landmark model and a robust tracking algorithm. The landmark model is sets of three or more natural lines such as baselines, door edges and linear edges in tables or chairs, to take the advantages of fast landmark detection. Lucas-Kanade optical flow algorithm is applied to track the landmark model by using gradient descent. Then, a quick localization method for mobile robots from correspondent lines is proposed by adopting a linear technique. We present experimental results that demonstrate the robustness of the method with respect to image illumination and noises. The performance in indoor environments shows the feasibility of the proposed localization algorithm in real-time.

Human friendly service robots such as home service robots, cleaning robots, entertainment robots take great attention in order to create new markets for robots since the markets for conventional industrial robots are saturating. It is a step to change the working environments of robots from industries to homes and offices, and to extend markets for robots from industrial markets to commercial home appliance markets. This paper introduces a home service robot 'ISSAC' applicable for vacuum cleaning, home security to find intruders and to transfer captured images of the intruder to the police or security companies, voice-based information service, real-time image transfer through wireless TCP/IP Ethernet and/or CDMA-2000 wireless communication, and a telepresence controllable by mobile computers such as pocket PC's and/or cellular phones. The overall controller is developed as a network-based layered modular controller using CAN (controller area network). The robot is tested in an apartment for a week successfully.

In this paper, a modified two-step compliance control method for robot hands is proposed: resolved interfinger decoupling solver (RIFDS) and resolved interjoint decoupling solver (RIJDS). For this, we first investigate how many fingers are necessary to successfully implement stiffness characteristics in the operational space. RIFDS is then proposed to decompose the desired compliance characteristic specified in the operational space into the compliance characteristic in the fingertip space without interfinger coupling, and RIJDS is also proposed to decompose the compliance characteristic in the fingertip space without interjoint coupling. It is found in the process of RIFDS that some nondiagonal stiffness elements specified in the operational space cannot be planned arbitrarily, due to grasping geometry. Similar to independent finger control, RIJDS aims at independent joint control. This scheme facilitates the joint servo control. To show the effectiveness of the proposed compliance control method, some experimental results are illustrated for a compliant task by using two- and three-fingered hands, which consist of five-bar finger mechanisms. It is concluded that grasping geometry and finger structure are crucial to successfully performing multifingered hands operations.

When a construction company builds a high structure, many piles should be driven into the ground by a hammer whose weight is 7,000 kg in order to make the ground under the structure safe and strong. So, it is essential to determine whether a pile is penetrated into the ground enough to support the weight of the structure since ground characteristics at different locations are different to each other. The paper proposes a visual measurement system for pile rebound and penetration movement including vibration using a high-speed line-scan camera and a specially designed mark to recognize two-dimensional motion parameters of the mark using only a line-scan camera. A mark stacking white and black right-angled triangles is used for the measurement, and movement information for vertical distance, horizontal distance and rotational angle is determined simultaneously. By adopting a line-scan CCD camera whose line rate is 20 kHz, the measurement performance of dynamic characteristics of the pile at impact instant is improved dramatically.

Some of manufacturing tasks such as sawing task often requires continuous impulsive motion. In case of sawing task, such impulsive motions can be observed between the teeth of the saw and the object. The amount of the external impulse exerted on the object has been treated as an important control paramete. Also, the internal impulses experienced at the joints should be simultaneously taken into account to avoid serious damage or injury at the joints. The purpose of this work is to improve the efficacy of sawing task by using dual arm. For this, an external impulse model for sawing task is suggested. Also, the closed-form internal impulse models are proposed for both a single and dual arms. Based on these models, a new measure for internal impulse is proposed. A normalized impulse ellipsoid reflecting the velocity direction is employed to visualize the impact geometry. Finally, the optimal sawing region is identified in which the amount of external impulse is maximized and the amount of the internal impulse is minimized. It is demonstrated through simulation that the dual arm exhibits better sawing performance over a single arm in aspects of external and internal impulses.

Despite that omni-directional mobile robots have been employed popularly in several application areas, effort on optimal design of such mobile robots has been few in literature. Thus, this paper investigates the optimal design of omni-directional mobile robots. Particularly, optimal design parameters such as one or double offset distance of wheel mechanism and the wheel radius are identifed with respect to isotropic characteristic of mobile robots. In addition, the force transmission characteristics and actuator-sizing problem of mobile robots are investigated Analysis has been performed for three actuation sets. It is shown that the redundantly acruated mobile robot with three active caster wheels represents the best performance among them.

In this paper, we describe an online trajectory control scheme for robotic manipulators with dynamic change of the task priority. First, given tasks are reconstructed using a geometric projection on the given index function. Then, the reconstructed tasks are analyzed in the framework of task priority based method. From this analysis, the proposed algorithm is shown to have the property that the task priority is assigned dynamically. Using this algorithm, we easily set the criteria of changing task priority and estimate the performance of the given index function. Considering the measure of manipulability as a index function, the approach is suitable for avoiding kinematic singularities for autonomous operation of, for example, an underwater robot. The result shows a good performance near the singular configurations, as shown by simulation results.

Based on the analysis of the stiffness relation between the operational space and the fingertip space of multifingered hands, this paper provides a guideline of task-based compliance planning for multifingered hands. 2D and 3D examples are illustrated to show the characteristics of the task-based stiffness matrix. It is shown that some of coupling stiffness elements cannot be planned arbitrarily due to grasping geometry. Through the analytical results, it is concluded that the operational stiffness matrix should be carefully specified by considering the location of compliance center and the grasp geometry of multifingered hands for successful grasping and manipulation tasks.

We provide a guideline for specifying compliance characteristics in the operational space of multifingered hands. From the analysis of the stiffness relation between the operational space and the fingertip space of multifingered hands, it is shown that some of the coupling stiffness elements cannot be planned arbitrarily. An independent finger-based compliance control method to achieve the given compliance characteristics is presented. Through the analytical results, it is concluded that the operational stiffness matrix should be carefully specified by considering the grasp geometry of multifingered hands for successful grasping and manipulation tasks, and the three-dimensional compliance control can also be achieved by a five-fingered human-like hand.

For a multi-fingered hand to grasp an object, there are numerous ways to grasp it stably, and thus an optimal grasp planning is necessary to find the optimal grasp point for achieving the objective of the given task. First, we define several grasp indices to evaluate the quality of each feasible grasp. Since the physical meanings of the defined grasp induces are different from each other, it is not easy to combine those indices to identify the optimal grasping. In this paper, we propose a new generalized grasping performance index to represent all of the grasp indices as one measure based on a non-dimensional technique. Through simulations, we show that the proposed optimal grasp planning is resemblant to the physical sense of human grasping.

Underwater robotic vehicles (URV) have been employed for mobility, and robot manipulators attached to the underwater vehicle play the role of manipulation. URV motions are determined by inherent dynamic couplings between active and passive joints. Furthermore, the control problem becomes complex since there should be considered many hydrodynamic terms as well as intrinsic model uncertainties. To cope with these difficulties, we propose a disturbance observer-based robust control algorithm for underwater manipulators with passive joints. The proposed control algorithm is able to treat an underactuated system as a pseudo-active system in which passive joints are eliminated. Also, to realize a robust control method, a nonlinear feedback disturbance observer is applied to each active joint. A four-jointed underwater robotic system with one passive joint is considered as an illustrative example. Through simulation, it is shown that the proposed control algorithm has good position tracking performances even in the presence of several external disturbances and model uncertainties.

For an object grasped by a robot hand to work in the compliance control domain, we first analyze a necessary condition for successful stiffness modulation in the operational space. Next, we propose a compliance control method for robot hands which consist of two steps: the RIFDS (resolved inter-finger decoupling solver) decomposes the desired compliance characteristic specified in the operational space into the compliance characteristic in the fingertip space without inter-finger coupling; and the RIJDS (resolved inter-joint decoupling solver) decomposes the compliance characteristic in the fingertip space into the compliance characteristic in the joint space without inter-joint coupling. According to the analysis results, the finger structure should be biomimetic in the sense that either kinematic redundancy or force redundancy are required to implement the proposed compliance control scheme. Five-bar fingered robot hands are treated as illustrative examples to implement the proposed compliance control method. To show the effectiveness of the proposed compliance control method, simulations are performed for two-fingered and three-fingered robot hands.

This paper proposes a visual serving method based on QR decomposition and disturbance observer. The QR decomposition factorizes the image feature Jacobian into a unitary matrix and an upper triangular matrix. It is shown that several performance indices such as measurement sensitivity of visual features, sensitivity of the control to noise and controllability can be improved for any general image feature Jacobian by OR decomposition and disturbance observer. To show the validities of the proposed approach, visual servoing with stereo cameras is experimented on Samsung FARAMAN 6-axis industrial manipulator.

This paper deals with stiffness analysis for effective peg-in/out-hole tasks using multifingered robot hand without inter-finger coupling. We first observe the fact that some coupling stiffness elements cannot be planned arbitrary. Then, we analyze the conditions of the specified stiffness matrix in the operational space to successfully and more effectively achieve the given peg-in/out-hole tasks. It is concluded that the location of compliance center on the peg and the coupling stiffness element between the translational and the rotational direction play important roles for successful peg-in/out-hole tasks. Simulation results are included to verify the feasibility of the analytic results.

This paper deals with target tracking control of unicycle type mobile robots. Target tracking function is essential for autonomous robots such as guide robots, security guard robots, etc. In the field of mobile robot control, many control schemes for posture stabilization and trajectory tracking problem have been proposed. Target tracking control, however, cannot be achieved using these kinds of control laws. Therefore, a new global asymptotic stable controller for this problem is designed using the backstepping method. The stability of the system is proved using the Lyapunov function. Various simulation results validate the performance and theoretical analysis.

A new parallel gripping mechanism is proposed in this work. This device has a parallelogramic platform which can be flexibly folded. Therefore, this mechanism not only can be used to grasp an object having irregular shape or large volume, but also can be utilized as micro-positioning device after grasping the object. Forward position analysis and platform kinematics are investigated to deal with motion tracking and force control. Pneumatic rotator is employed for actuation and a compact sized, 4/3 way proportional pressure valve is also developed to deal with feedback-based dynamic control. The pressure valve also allows indirect force control by measuring the offset pressure occurring due to contact between the grasped object and the parallel platform. In experimental work, performances of the motion tracking and indirect force control are shown satisfactory.

A compliance control strategy for robot manipulators is proposed by employing a self-adjusting stiffness function. To be specific, each entry of the diagonal stiffness matrix corresponding to task coordinate in Cartesian space is adaptively adjusted during contact along the corresponding axis based on the contact force with its environment. It can also be used for both unconstrained and constrained motions without any switching mechanism which often causes undesirable instability and/or vibrational motion of the end-effector. The experimental results show the effectiveness of the proposed method by employing a two-link direct drive manipulator interacting with an unknown environment.

To improve the visual servoing performance, several strategies have been proposed by using redundant feature points, by using a point with different height, and by a weighted selection of image features. The performance of these visual servoing methods depends on the configuration between the camera and objects. And redundant feature points require much computational efforts. The paper proposes a visual servoing method based on a disturbance observer which compensates the effect of the off-diagonal component of the image feature Jacobian to be null. The performance indices such as measurement sensitivity of visual features, sensitivity of the control to noise, and controllability are improved when an image feature Jacobian is given as a block diagonal matrix. The proposed approach is applied to the PUMA560 and Samsung FARAMAN 6-axis industrial robot manipulators successfully.

We discuss an inherent problem occurring in the former operational-based compliance control scheme. In order to obviate this problem, an independent joint-based compliance control scheme is proposed. This control method requires that for the adjustment of the operational compliance matrix, a manipulator should have at least the same number of joints as the number of independent components of the desired compliance matrix specified in the operational space. Types of robot structures which are appropriate to independent joint-based compliance scheme are addressed. A five-bar finger with redundant actuators is treated as an illustrative example. Our experimental results show that the proposed compliance modulation method gave satisfactory performance. We also consider an additional stiffness effect due to the antagonistic conflict between the controlled-operational force and the equilibrium joint torque vector. It is also experimentally shown that this additional term notably improved the force tracking performance of the given mechanism.

There has been much interests on three-dimensional pose estimation of an object since there are a lot of robotic applications such as intelligent robotic assembly and/or vision-guided control of a humanoid or human-friendly robot. In this paper, there are proposed a simple and fast stereo matching algorithm for real-time robotic applications and an improved scheme for feature matching using three-dimensional information by adopting backprojection as a feedback element measuring the degree of feature matching. The degree of feature matching is determined by checking existence ratio of each feature point in real images after back-projecting an object model into image plane. The proposed pose determination algorithm is applied for a humanoid robot in KIST, whose name is CENTAUR, successfully and determine the pose of several polyhedral objects using 3D information of vertexes on the outline of an object in image plane.

A visual servoing method has been proposed based on a disturbance observer to eliminate the effect of the off-diagonal component of the image feature Jacobian, since performance indices such as measurement sensitivity of visual features, sensitivity of the control to noise, and controllability could be improved when an image feature Jacobian was given as a block diagonal matrix. In this paper, experimental results of disturbance observer-based visual servoing are discussed, where a Samsung FARAMAN-ASI 6-axis industrial robot manipulator is employed. Also, the feature saturator is proposed to stabilize the disturbance observer loop by saturating the differential changes of the image features.

A new stiffness adaptation and force regulation methodology using hybrid system approach for constrained robots is presented. We present the hybrid system model and the hybrid system control synthesis for constrained robots with the stiffness uncertainties is formulated. The hybrid control approach presented has shown to be a very effective strategy to incorporate both the continuous and discrete natures of constraint motion. A nonlinear stiffness function is developed and designed to be hybrid automaton, which consists of some abstracted motion such as increase, decrease, and maintenance of stiffness. The evaluations are evaluated via experimental studies on grinding tasks. The results of experiment are showing the applicability of proposed scheme for constrained tasks.

Proposes a hybrid control architecture which combines the key features of the two well-known robot control architectures; hierarchical and behavioral-based. The overall control architecture consists of three layers, i.e. the high-level planner, the middle plan executor, and the lower level monitor and behavior-based controller. In the planned task, only one behavior module is chosen by the logical coordinator in the plan executor according to the way point bin. In the exceptional situation, the central controller in the plan executor issues an additional control command to reach the planned way point. Several simulations and experiments with an autonomous mobile robot show that the proposed architecture enables the robot controller to achieve the multiple sequential goals even in a dynamic and uncertain environment.

Deals with a sawing task performed by two cooperating arms. The two-arm system under our hand consists of a four degree-of-freedom (DOF) SCARA robot and a five DOF PT200V robot. When the two arms are rigidly grasping a saw, the mobility of the system is three, which is not enough for sawing tasks. Therefore, we deliberately insert a passive joint at the end of the SCARA robot to increase the mobility up to four. A hybrid control method to regulate the force and velocity by the two arms is proposed in this work. The proposed scheme has three typical features; first, the two arms are treated as one arm in a kinematic viewpoint. Secondly, our approach is different from other acceleration-based approaches, in the sense that our hybrid control method is based on a Jacobian and an internal kinematics for a single closed-kinematic chain of the two arms to reflect the nature of the position-controlled industrial manipulator. Thirdly, the proposed scheme is not only able to operate the system even if a passive joint exists, but also is able to utilize the internal loads for useful applications such as pitch motion control. We experimentally show that the performance of the velocity and force response are satisfactory, and that one additional passive joint not only prevents the system from unwanted roll motion in the sawing task, but also allows an unwanted pitch motion to be notably reduced by an internal load control. To show the effectiveness of the proposed algorithms, we perform experimentation under several, different conditions for saw, such as three saw blades, two sawing speeds, and two vertical forces.

A five-bar finger mechanism driven by redundant actuators is given as an illustrative example. It is shown that judicial choice of the location of one redundant actuator greatly enhances the load handling capacity of the system, when compared to those of minimum actuation and more than two redundant actuators. Also, methodologies for stiffness and motion frequency modulations via redundant actuation are investigated. Internal load distribution associated with the stiffness and motion frequency modulations is further discussed. Specifically, the motion frequency of the system is modulated by employing inertial and spring-like impedance properties created by internal loading. The motion frequency as well as the amplitude of oscillation can be actively adjusted during the motion, and the equilibrium position about which the vibration occurs can also be arbitrarily changed during the motion. Furthermore, using the stiffness modulation capability, a point-to-point motion can be accomplished by a progressive movement of equilibrium posture, which is called a virtual trajectory. To show the effectiveness of the proposed algorithms, several simulation results are illustrated.

Focusing on the manipulation tasks to be executed by humanoid robots, principal requirements which are to be satisfied by hardware/software of the control system are considered. In order to meet the requirements, a novel type of hardware structure and software architecture is proposed. Since the target humanoid robot consists of multiple subsystems such as a central controller for brain, a vision controller for eye, and five motion sub-controllers for two arms, two hands, one spine, the on-board hardware control system is designed to have a distributed control structure connected by pseudo real-time Ethernet interfaces. A goal-achieving software architecture is also proposed which meets the requirements of semi-autonomy, reactivity, expandability, and object-orientedness. Specifically, in order to achieve reactivity, a coordination method is proposed to configure three kinds of executive modules, primitive module, flow-control module, and goal module, which have multiple exit states. The control architecture proposed has been implemented for performing toy-block assembly tasks on a humanoid robot as well as on the graphic simulator.

In this paper, a force estimation method is proposed for force control without force sensor. A disturbance observer is applied to each joint of an n degrees of freedom manipulator to obtain a simple equivalent robot dynamics being represented as an n independent double integrator system. To estimate the output of disturbance observer due to internal torque, the disturbance observer output estimator (DOOE) is designed, where uncertain parameters of the robot manipulator are adjusted by the gradient method to minimize the performance index which is defined as the quadratic form of the error signal between the output of disturbance observer and that of DOOE. When the external force is exerted, the external force is estimated by the difference between the output of disturbance observer and DOOE. A force controller is designed for force feedback control employing the estimated force signal. Several numerical examples and experimental results are illustrated for a 2-axis direct drive robot manipulator.

In order to develop a human hand mechanism, a 5-bar finger with redundant actuation is suggested. Optimal sets of actuator locations and link lengths for the cases of minimum actuator, one, two and three redundant actuators are obtained by employing composite design index which simultaneously consider several performance indices such as workspace, isotropic index, and force transmission ratio. Finally, several finger-configurations optimized for special performance indices are illustrated.

We have proposed the collision-tolerant mobile manipulator equipped with a passive trunk (i.e., supporting part). In collision experiments with unknown environments, results show that this mechanism is suitable for the suppression of contact forces which is an important issue for human-robot collaborations. The trunk with mechanical elements such as springs and dampers is passively deformed to deal with physical contacts, while the mobile platform moves around on the horizontal plane in response to friction between the platform and the ground. The end-effector of the manipulator, however, is difficult to track a desired task due to the deformation of the compliant trunk and the mobility of the platform. In order to solve the problem, the desired joint configurations of the manipulator are directly calculated according to the movement of the trunk and the platform, and a feedback control scheme is employed.

Typical biomechanical systems such as human body and mammals possess abundant muscles which are more than required for motion generation of such systems. The purpose of this work is to verify a biological phenomenon, the so called frequency modulation, in a mathematical manner. The frequency modulation represents simultaneous control of force and kinematic redundancies. The phenomenon of frequency modulation is explained through a human-like anthropomorphic robot. A load distribution method for frequency modulation via redundant actuation is also introduced. To show the effectiveness of the proposed algorithms, several simulation results are illustrated.

In this paper we propose a method of determining the local curvature of a three dimensional convex object using the force and torque information obtained from the active touch of a robot finger. A technique for estimating two dimensional curvature of a convex object are introduced and the way of computing the three dimensional curvature from the two dimensional curvature is presented. Also, we develop an experimental system consisting of a finger and verify the effectiveness of the proposed method experimentally.

Addresses the design of hybrid control systems for the motion control of wheeled mobile robot systems with nonholonomic constraints. The hybrid control system has a 3-layered hierarchical structure: digital automata for the higher process, mobile robot system for the lower process, and the interface as the interaction process between the continuous dynamics and the discrete dynamics. In the hybrid control architecture of mobile robot, the continuous dynamics of mobile robots are modeled by switched systems. The abstract model and digital automata for the motion control are developed. The motion control tasks for desired-paths with edges and dynamic path following with various initial conditions are investigated as the applications by simulation studies.

In this work, a parallel-type gripping and micro-positioning mechanism is proposed. This device has a parallelogrammatic platform which can be flexibly folded. Therefore, this mechanism not only can be used to grasp an object having irregular shape or large volume, but also can be utilized as a micro-positioning device after grasping the object. Configuration parameter for configuration control of the proposed gripping mechanism is defined. Grasping force and isotropic characteristic of the mechanism are considered as design indices for optimal design of the gripping mechanism. The proposed mechanism is expected to be used as an adaptable gripping and micro-positioning device by attaching it at the end-point of a robot.

A new concept of a robot manipulator with passive mobile base is proposed which can be safely used in a human-robot cooperation environment. A joint-based control scheme is developed to control the end-effector position of the manipulator which is tolerant to unexpected contact force with the manipulator's environment. The mobility the of base of the manipulator is passively exploited to attenuate the dynamic disturbance of the contact force and the joint configurations are re-adjusted according to the evolution of the position of the base to maintain performance of the given task. Effectiveness of the proposed method is verified by computer simulation and experimental evaluation is currently underway.

Concerns a sawing task by two cooperating arms. To follow a line in a horizontal plane, three directional motions must be controlled, 2 translational and 1 rotational. A certain level of force must be controlled in the vertical direction, to keep contact with the object to be sawn. The two-arm system consists of a 4-DOF SCARA robot and a 5-DOF PT200V robot. When the two arms are rigidly grasping a saw, the mobility of the system is 3, which is not enough. Therefore, we deliberately insert a passive joint at the end of the SCARA robot to increase the mobility to 4. A hybrid control method to regulate force and position is proposed. The proposed scheme has three typical features: First, the two arms are treated as one in a kinematic viewpoint. Second, the hybrid control method is based on a Jacobian and an internal kinematics for a single closed-kinematic chain of the two arms to reflect the nature of the position-controlled manipulator. Third, the proposed scheme is not only able to operate the system even if a passive joint exists, but also is able to utilize the internal loads for useful applications such as pitch motion control. We experimentally show that the performance of the position and force response are satisfactory, and that one additional passive joint not only prevents the system from unwanted roll motion in the sawing task, but also allows an unwanted pitch motion to be notably reduced.

For a 5-bar finger mechanism with redundant actuators, it is shown that judicial choice of the location of one redundant actuator greatly enhances the load handling capacity of the system when compared to that of nonredundant systems, And, it is also shown that excessive redundant actuation enables the system to modulate the end-point stiffness or motion frequency by internal load distributions. Especially, the motion frequency modulation via internal loads in redundantly actuated closed-chain systems is believed to be fairly new. To show the effectiveness of the proposed algorithms, several simulation results are illustrated.

For continuous state space applications, a novel method of Q-learning is proposed, where the method incorporates a region-based reward assignment being used to solve a structural credit assignment problem and a convex clustering approach to find a region with the same reward attribution property. Our learning method can estimate a current Q-value of an arbitrarily given state by using effect functions, and has the ability to learn its actions similar to that of Q-learning. Thus, our method enables robots to move smoothly in a real environment. To show the validity of our method, the proposed Q-learning method is compared with conventional Q-learning method through a simple two dimensional free space navigation problem, and visual tracking simulation results involving a 2-DOF SCARA robot are also presented.

A biologically inspired, novel concept for an actively adjustable frequency modulator is presented. The idea of frequency modulation stems from the human body. The human body is known to be able to modulate the spring-like impedance property in a feedforward fashion using antagonistically fighting muscles. Therefore, the motion frequency of the system can be also modulated by employing the information on the inertial property and the spring-like impedance property of the human body. Based on this concept, a methodology for the motion frequency modulation via redundant actuation is investigated. A five-bar finger mechanism driven by redundant actuators is given as an illustrative example. It is shown that the motion frequency as well as the amplitude of oscillation can be actively adjustable during the motion, and that the equilibrium position about which the vibration occurs can also be arbitrarily changed during the motion. Furthermore, using the frequency modulation capability, a point-to-point motion is accomplished by a progressive movement of equilibrium posture, which is termed a virtual trajectory. To show the effectiveness of the proposed algorithms, several simulation results are illustrated.

An object-oriented approach to behavior-based control architecture for autonomous mobile robots as presented. Instead of traditional implementations of the architecture with proprietary programming languages which resulted in slow execution speed and poor hardware compatibility, the C++ language is used and an optimal scheduling algorithm is proposed for fast and guaranteed response time. Each behavior module is compiled separately and loaded at run-time using dynamic binding to improve modularity and expandability. A vector valued representation of output signals is also proposed to arbitrate conflicting signals properly without losing any information. The proposed method is implemented and applied to control a laboratory developed autonomous mobile robot and tested in real-time.

This paper presents a design experience of a supervisory control system for coordination of multiple robotic devices. To effectively program job commands, a Petri net-type graphical robot language(PGRL) is proposed, where some functions for coordination among tasks such as concurrency and synchronization, can be easily programmed. Each task of PGRL is described by employing formal model languages, which are composed of three modules, sensory, data handling, and action module. It is expected that by using our proposed PGRL and formal model languages, one can efficiently describe a job or task, and hence can easily operate a complex real-time concurrent system. The proposed control system has been implemented by using VME-based 32-bit microprocessor boards and a real-time multitasking operating system (VxWorks), and is shown to successfully work for robotic jobs.

The concept of dynamic tracking line is proposed as the feasible tracking region for a robot in a robot-conveyor system, which takes the variable conveyor speed into consideration. This paper presents an effective method to find the dynamic tracking line in a robotic workcell. The maximum permissible line-speed which is a quantitative measure of the robot capability for conveyor tracking, is defined on the basis of the relation between the end-effector speed and the bounds on the joint velocities, accelerations, and torques. This measure is derived in an analytic form, and some of its properties are established mathematically. The problem of finding the dynamic tracking line is then formulated as a root-solving problem for a single-variable equation, and solved by the use of a simple numerical technique.

A compliance control strategy is proposed by using a new type of self-controlled stiffness function, where no explicit wrist force/torque sensor is employed. Specifically, the stiffness gain is given as the exponential function of the error between virtually given desired trajectory and actual trajectory, where virtual desired trajectory is designed to be inside the surface of the object to be compliance-controlled. And, a motion speed scheduling technique is also proposed to avoid serious damages due to lack of environmental knowledge and to minimally maintain the task performances. It is experimentally shown that the proposed control method is useful for various manipulator motion types such as path following, initial contact with soft impact and force regulation during contact.

In this paper, a fuzzy force control algorithm is suggested for commercialized industrial robots equipped with the position servo drives, where control rules of the proposed fuzzy controller are changed according to the magnitude of environmental stiffness in such a way that good force response is maintained regardless of changes of environmental stiffness. Specifically, some fuzzy control rules are designed for several representative environmental stiffness values, and then a control action for a given arbitrary environmental stiffness value is decided by a fuzzy interpolation method. To show the validity of the proposed fuzzy controller, several experimental results are illustrated, where a 5-axis articulated robot manipulator equipped with the wrist force/torque sensor system and our prototype dual robot controller are employed.>

A force/position control method is proposed for robot manipulators equipped with a wrist force/torque sensor and position servo drives. Especially, fuzzy PI gain tuning rules are suggested to improve the transient force response. To show the validity of the proposed method, a numerical example employing a two-link manipulator is given.>

A visual servoing method is proposed for eye-in-hand robots. It employs a self-organizing fuzzy controller. There is defined a Jacobian that is not a function of a relative position of the object but is a function of the image features. Instead of obtaining an analytic form of the proposed Jacobian, a self-organizing fuzzy controller is then proposed to alleviate difficulties in real-time implementation. To show its validity, the proposed method is applied to a 2D visual servoing task.>

An iterative learning control algorithm for a class of linear periodic systems is proposed in which parameter estimation is performed in the domain of an iterative sequence of operations with the time frozen. A sufficient condition for the convergence of the proposed algorithm is given. It is also shown that the proposed learning controller can be applied to the continuous path control of robot manipulators. It is noted that the proposed algorithm works reasonably well only for the case of small perturbations with respect to a nominal trajectory.>