For generating interactive behavior of robot to build a long-term relationship between humans and robots, we focus on the difference in familiarity of the human behaviors during conversation. It is difficult to extract interaction motion features correlated to such familiarity as a model in manual. Therefore, we use a machine learning technique: convolution neural network to learn and generate interaction behavior with different familiarity. In the evaluation experiment, we generated interaction behavior using a convolution neural network, which learned from the behaviors of friendship and unknown relationship, who have high and low familiarity respectively. We evaluated how much such interaction behavior affect the human impression by questionnaire survey.

In micromanipulation, lots of methods have been developed to manipulate objects in microscale. However, few of them can be applied in both the transportation and the rotation of the micro objects. In this paper, we present a novel method to realize the non-contact transportation and rotation of the micro objects based on the vibration-induced swirl flow. A piezo actuator is set between the glass needle and a metal rod. The sine wave with controlled frequency and amplitude is input into the piezo actuator to drive the glass needle to move circularly, which is caused by resonance of the actuator and the metal rod. We place the glass needle under water and keep a limited distance to the bottom. The circular vibration of the glass needle can generate a swirl flow and low pressure around it. The low pressure can trap and transport the micro objects vertically to the glass needle, and the swirl flow can rotate the objects continuously. Finally, we realize the trap and rotation of micro object with only one piezo actuator. Experiments of transportation and rotation of microbeads are carried out, and the results demonstrate it is a simple, low-cost, effective micromanipulation method.

Recently, manipulation and observation of the cells are actively conducted in order to analyze the biological phenomena. Since the micro hand is usually fixed to the work environment, grasping target point of the cell on the opposite side of the micro hand by using a micro hand is limited by narrow workspace. If we move the micro hand in vertical direction to grasp the target point of the cell on the opposite side of the micro hand, we cannot focus the micro hand and the object in the microscopic field of view at the same time. In order to overcome the limitations of the limited workspace of micro hand, we assist the target point of the cell grasped by translation and rotation of the automatic stage. In this paper, we propose an automatic stage system for support the operation of the micro hand. Our automatic stage system can detect the object in the microscopic field of view by the template matching using Hu moment invariant and determine the grasping convex part of the object. by convex hull. Additionally this system can do 2d path planning considering convex part of the object to want to grasp and obstacles, and lead the micro hand to the object.

The paper describes a method of fault-tolerant adaptive gait generation based on CPG controller with interlimb coordination for multi-limbed working robot. Multi-limbed robot is expected to work in dangerous, complicated narrow spaces, where human workers cannot reach. However, if one of the limbs is broken in the dangerous/narrow working space, human operators cannot go to the space to repair it. Even in these situations, the proposed method generates a new gait adaptively using the remaining usable limbs depending on the current situation of the multi-limbed robot. This fault-tolerant ability is effective for multi-limbed robots working in dangerous/narrow space. The method is implemented to a model of a multi-limbed robot “ASTERISK” in a dynamical simulator (ODE). Experimental results show effectiveness of the proposed method.

The reliable manipulation of micro-objects has been a still difficult work in scientific and technical field due to scale effects. This paper presents two types of release methods, using local stream and inertia force generated by 3D high speed motion of an end effector, for releasing and accurate positioning of biological cells. Two-fingered microhand driven by DC motors for both end effectors and PZT actuators for right end effector is employed. A parallel mechanism controlled by three PZT actuators generates 3D high speed motions to release cells adhered to one of the end effector. The local stream and inertia force created by high speed motion of the right end effector detach the cells adhered to the left end effector and right end effector, respectively. To generate the necessary external forces for separation of the attached cells, the vibration having high frequency and suitable amplitude is applied. For accurate positioning of the object, circular motions are proposed. To verify the advantage of the proposed motion, we compare five motions, three 1D motions and two circular motions. Experiments were conducted employing 16μm NIH3T3 cells. From these analyses of experiments, we conclude that the proposed motions can detach micro objects (100%) with high position accuracy (3±0.7μm) on desired position after release.

Visual tracking of objects subjected to non-linear motion and appearance changes has shown to be a difficult task in computer vision. While research in visual object tracking has progressed significantly in terms of robust tracking of objects subjected to non-linear motion and appearance changes, these algorithms has shown limited capability for long term tracking of handheld objects during human-object interactions. The failure in tracking is a consequence of abrupt changes in the handheld object motion resulting in tracker drifting off the optimal object space. In this paper, we present a novel 3 layer RGB-D image model formulated with Bayesian filters that tracks handheld object using near constant velocity motion model. Our method divides the image into three layers of abstraction where each encodes visual information of environment, human, object and contributes toward precise localization of the handheld object during tracking. A boundary re-alignment step is introduced during tracking such that the tracker predicted object region is re-aligned to the optimal object region, therefore reducing the likelihood of tracker drifting off the object space. This compensation of the tracker prediction offset enables our algorithm to robustly track handheld object subjected to abrupt changes in motion during manipulation.

Single cell analysis has attracted much attention for revealing detailed and localized biological information. A local environmental control technique is desired when analyzing the detailed and localized properties of single cells. In this paper, we propose a local environmental stimulation system with micro dual-pipettes to stimulate the local reagent concentration dynamically, freely and automatically. When the local environment is controlled with chemical stimuli, the chemical solution is diffused and affects other objects. The local environment stimulation system with micro dual-pipettes can solve this problem by using spout pipette and suction pipette. As a cell analysis system, system quantification is necessary, so we try to realize it using a fluorescent substance. First step, we try to measure and control the light intensity. As an application of the system, the system can construct two-dimensional cell-organization by peeling off certain area of cell-sheet. Therefore, we try to control the area of peeling off cells using the system.

Recently micro manipulation techniques for cell or microorganism has attracted attention in life sciences. In this paper, non-contact manipulation method using water stream is proposed. Water stream is generated by a glass needle vibration that is actuated by a piezoelectric actuator. The stream is controlled by changing input voltage or frequency to the actuator. An accuracy of the motion of a piezoelectric actuator is in nano-meter order, so the stream is considered to be controlled precisely. The manipulator works in 3 dimensional space, that means water stream is generated in 3d space. We focused on the rotational stream generated by the glass needle 2-dimensional circular vibration. By using the resonance in a structure of the manipulator and the actuator's vibration, circular vibration can be generated by only one actuator. There is no need to use two actuators for generating circular vibration, so the structure of the manipulator is quite simple. In this paper rotational stream around the glass needle is also analyzed in 3d space using micro beads. This manipulator has the similar characteristics to the existing research of contact manipulation, so we think our method also have the capability to conduct contact manipulation.

This paper presents an active release method of microobject for the improvement of the position accuracy after releasing by using 3D high speed motions of an end effector. In the micro manipulation, the release task is the challenge work due to adhesion forces. To overcome the adhesion force and to place microobject accurately on the desired location, in this paper, we propose a high speed motion by analyzing dynamic model of manipulated end effector and attached microbeads. Two fingered microhand driven by DC motors and PZT actuators is utilized for this paper. Parallel mecahnism with three PZT actuators was used for making 3D motion at high speed. To generatge high acceleration of end effector, many researchers applied simple vibration by using an additional PZT actuator. In our research, 3D high speed motion with large amplitude was achieved by only using a compacted parallel mechanism. To verify the advantage of the proposed motion, we compare five motions, 1D motions (X, Y, and Z direction) and circular motions (clockwise and counterclockwise direction), by changing the frequency and moving distance of the end effector. From these results of experiments, we conclude that the circular motion can detach microobjects with high placing accuracy after release.

In the field of medicine and biology, many studies to be related to regenerative medicine are accomplished. In particular, the purpose of helping the operation of the cells under a microscope, many research related to micro manipulation techniques with robotic technology has been proposed. In such background, we studied two finger micro hand that realized control of the sub-micro order size object. The accurate operation of the end effector against the object by the micro hand is demanded to users. To reduce the burden, we focus on making the manipulation easy. User can perform micro manipulation with rough operation by using the actuator that varies in size. Since the actuator fills space between the end effectors and the object. Then we focus on the gel that varies in size. In this paper, we evaluate the gel that varies in size. Then we propose the manipulation that take advantage of the gel.

In this paper, a dynamic releasing method for high-speed biological cell manipulation is proposed. A compact parallel mechanism, used for grasping and releasing microob-jects, was utilized for generating controllable vibration to overcome the strong adhesion forces between the end effector and the manipulated object. To reach the required acceleration of the end effector, which is necessary for the detachment of the target object, vibration in the end effector is generated by applying sinusoidal voltage to the PZT actuator of the parallel mechanism. For the necessary acceleration, we focus on the frequency of the vibration, while keeping the amplitude of the PZT actuator vibration small (14 nm) to achieve precise positioning. Releasing of microbeads and biological cells is conducted and results are compared for the first time. The effect of the air and liquid environments are also investigated. Successful releasing (97.5%) of biological cells proves that the proposed active releasing method is an appropriate solution for the adhered biological cells during the releasing task.

Robots operating in human environments must have the ability to autonomously acquire object representations in order to perform object search and recognition tasks without human intervention. However, autonomous acquisition of object appearance model in an unstructured and cluttered human environment is a challenging task, since the object boundaries are unknown in prior. In this paper, we present a novel method to solve the problem of unknown object boundaries for handheld objects in an unstructured environment using robotic vision. The objective is to solve the problem of object segmentation without prior knowledge of the objects that human interacts with daily. In particular, we present a method that segments handheld objects by observing human-object interaction process, and performs incremental learning on the acquired models using SVM. The unknown object boundary is estimated using sequential back-tracking via exploitation of affine relationship of consecutive frames. The segmentation is achieved using identified optimal object boundaries, and the extracted models are used to perform future object search and recognition tasks.

Single cell analysis has attracted much attention to reveal the localized biological information in detail. Local environmental control technique is developed to analyze the localized detail properties of single cells. In this paper, we propose the local environmental chemical stimulation system with micro dual pipettes to stimuli the local reagent concentration dynamically and automatically. Local environmental chemical stimulation by dual pipettes is applied to the rotational speed control of bacterial flagellar motor, which is a rotary molecular machine. Here, we show quick response and rotational speed control of Na-driven flagellar motor in both accelerating and relaxing directions was demonstrated by automatic switching the local spout between Na-containing and Na-free solutions with dual pipettes. It was shown that the rotational speed could be maintained by automatic controlling the spouting velocity of Na-containing and Na-free solution with multiplying the applied DC voltage. Furthermore, it was confirmed that by applying the P-control, rotational speed of flagellar motor could be controlled more stably.

Brain Machine Interface systems provide ways of communication and control of a variety of devices that range from domestic appliances to humanoid robots. Most BMI systems are designed exclusively to control devices using low-level commands, or high-level commands when devices with pre-programmed functionalities are available. In this paper, we build on our previous work on BMI-based Learning System in which we presented a different approach for designing BMI systems that incorporate learning capabilities that relieve the user from tedious low-level control. In this work, we extend the capabilities of our framework to allow a user to be able to teach and evaluate a robotic system by using a BMI. We provide general system architecture and demonstrate its applicability in new domains such as teaching a humanoid robot object manipulation skills and evaluating its performance. Our approach consists of 1) tele-operating robot's actions while robot's camera collects object's visual properties, 2) learning manipulation skills (i.e. push-left, lift-up, etc.) by approximating a posterior probability of commonly performed actions when observing similar properties, and 3) evaluating robot's performance by considering brain-based error perception of the human while he/she passively observes the robot performing the learned skill. This technique consists of monitoring EEG signals to detect a brain potential called error related negativity (ERN) that spontaneously occurs when the user perceives an error made by the robot. By using human error perception, we demonstrate that it is possible to evaluate robot actions and provide feedback to improve its learning performance. We present results from five human subjects who successfully used our framework to teach a humanoid robot how to manipulate diverse objects, and evaluate robot skills by visual observation.

This paper presents a chip containing a flexible scaffold which facilitates the construction of tissues with different shapes. The chip, entirely made of Polydimethylsiloxane (PDMS), has 2 main components including actuator and channel layers. The actuator layer consists of a 6×6 array of membrane actuators, with round shapes. The channel layer has a single layered structure due to the simplicity in chip assembly and the ability to observe seeded cells via a microscope. The actuator array offers a flat surface, like a normal cell culture dish, in the rest state, while it temporarily offers a scaffold structure when actuators are activated. By changing the actuation pattern, formation of many scaffold structures is possible. To demonstrate the utility of this chip in biological application, a syringe pump is connected to all actuators to produced 2 different scaffolds, enabling the fabrication of multiple flat round and lattice shaped tissues. NIH3T3 cells with the amount of 5×106were seeded on the scaffold and kept inside the incubator for 24 hours. The 25 round shaped tissues with an average diameter of 623.87 μm were simultaneously fabricated when a scaffold with large deformed actuators was used. The lattice shaped tissue with a line width of about 300 μm was also fabricated with a different scaffold structure which has less actuator displacement. Results suggest the potential usage of this chip for the preparation of many building units with different structures, without the necessity of making a new mold for a new tissue shape.

Single cell analysis has attracted much attention for revealing detailed and localized biological information. A local environmental control technique is desired when analyzing the detailed and localized properties of single cells. In this paper, we propose a local environmental stimulation system with micro dual-pipettes to stimulate the local reagent concentration dynamically, freely and automatically. When the local environment is controlled with chemical stimuli, the chemical solution is diffused and affects other objects. The local environment stimulation system with micro dual-pipettes can solve this problem. By using spout pipette and suction pipette, it is possible to use local stimuli without affecting other objects. For evaluating the locality of the system, we use a fluorescent substance and measure the diffusion of the spouted solution.

This paper addresses the problem of mental fatigue caused by prolonged use of Brain Machine Interface (BMI) Systems. We propose a system that gradually becomes autonomous by learning user preferences and by considering error perception feedback. As a particular application, we show that our system allows patients to control electronic appliances in a hospital room, and learns the correlation of room sensor data, brain states, and user control commands. Moreover, error perception feedback based on a brain potential called error related negativity (ERN) - that spontaneously occurs when the user perceives an error made by the system - was used to correct system's mistakes and improve its learning performance. Experimental results with volunteers demonstrate that our system reduces the level of mental fatigue, and achieves over 90% overall learning performance when error perception feedback is considered. Note to Practitioners - This paper suggests a new approach for designing BMI systems that incorporate learning capabilities and error perception feedback in order to gradually become autonomous. This approach consists in learning the relationship between sensing data from the environment-brain and user actions when controlling robotic devices. After the system is trained, can predict control commands on behalf of the user under similar conditions. If the system makes a mistake, user's error perception feedback is considered to improve the learning performance the system. In this paper, we describe the methodologies to design and build hardware and software interfaces, acquire and process brain signals, and train the system using machine learning techniques. We then provide experimental evidence that demonstrates the effectiveness of this approach to design BMI systems that gradually become autonomous.

In this work, we present a high-speed pick-and-place method for cell-assembly applications. Besides range of motion and accuracy, rapidness of a manipulation system is an important parameter, which is so far underrated in related studies. To achieve high-speed micromanipulation, obtaining 3D positions of both the target microobject and the end effector rapidly is necessary. In addition, controlling the vibration of the end effector, which is greater at high speed, is another arduous task. We propose a new fast detection algorithm for both the target microobject and the end effector for achieving high-speed control of the system. Moreover, to realize the stable control for very fast movements, the vibration of the system is compensated. High-speed control of the microhand system is demonstrated with preliminary experiments consisting of pick-and-place actions of 40 to 60 μm microspheres; we aimed at performing a manipulation task in 1 second. Comparison with similar studies shows the merit of the proposed automated high-speed micromanipulation system.

In this research we present a non-invasive Brain-Machine Interface (BMI) system that allows patients with motor paralysis conditions to control electronic appliances in a hospital room. The novelty of our system compared to other BMI applications is that our system gradually becomes autonomous by learning user actions (i.e. turning on/off window, lights, etc.) under certain environment conditions (temperature, illumination, etc.) and brain states (i.e. awake, sleepy, etc.). By providing learning capabilities to the system, patients are relieved from mental fatigue or stress caused by continuously controlling appliances using a BMI. We present an interface that allows the user to select and control appliances using electromyogram signals (EMG) generated by muscle contractions such as eyebrow movement. Our learning approach consists in two steps: 1) monitoring user actions, input data from sensors distributed around the room, and Electroencephalogram (EEG) data from the user, and 2) using an extended version of the Bayes Point Machine approach trained with Expectation Propagation to approximate a posterior probability from previously observed user actions under a similar combination of brain states and environmental conditions. Experimental results with volunteers demonstrate that our system provides satisfactory user experience and achieves over 85% overall learning performance after only a few trials.

Recently, with the development of life science field, micromanipulation technology has attracted attention. A two-fingered microhand system, that has been developed as a micro manipulator, can perform dexterous cell manipulation such as grasping, rotating, and transferring using two end effectors in a chopstick-like motion. The automated manipulation uses processing results based on all-in-focus (AIF) images and depth map obtained from the vision system; however, errors in the results still reduce the efficiency of the system. In this study, we introduce an automated grasping system that corrects the image processing error using the reaction force from the target object during grasping maneuvers. In our improved microhand system, micro force sensors that comprises strain gauge are attached to the two fingers of microhand. The two fingers with micro force sensor are set to be able to measure the horizontal and vertical forces to detect grasping state, precisely. Using the sensor information and the image processing results, we demonstrate that this system improves the accuracy and success rate of automated grasping.

In the fields of medicine and biology, it is essential to realize fine manipulation. Therefore, micromanipulation techniques and micromanipulators such as microgrippers and optical tweezers have been developed. We have developed a two-fingered microhand which is using the parallel mechanism to realize precise and stable micromanipulation. However, the previous microhand has problems about workspace and vibration. In this paper, the development of a new microhand which solves problems of previous microhand. The characteristic of new microhand is to enlarge the workspace utilizing the singularity of the parallel mechanisms. Inverse kinematics and structural analysis are used to analyze the workspace, and we show that results of two analyses match. Vibration analysis simulates transportation task and grasping task for manipulation. The new microhand has a potential to reduce the vibration by vibration analysis results.

Keyframe selection is the process of finding a representative frame in an image sequence. Although mostly known from video processing, keyframe selection faces new challenges in the lifelog domain. To obtain a keyframe that is close to a user-selected frame, we propose a keyframe selection method based on image quality measurements and excitement features. Image quality measurements such as contrast, color variance, sharpness, noise and saliency are used to filter high quality images. However, high quality images are not necessarily keyframes because humans also use emotions in the selection process. In this study, we employ a biosensor to measure the excitement of humans. In previous investigation, keyframe selection using only image quality measurements yielded an acceptance rate of 79.70%. Our proposed method achieves an acceptance rate of 84.45%.

We propose a social navigation model that allows a robot to navigate in a human environment according to human intentions, in particular during a situation where the human encounters a robot and he/she wants to avoid, unavoid (maintain his/her course), or approach the robot. Avoiding, unavoiding, and approaching trajectories of humans are classified based on the face orientation on a social force model and their predicted motion. The proposed model is developed based on human motion and behavior (especially face orientation and overlapping personal space) analysis in preliminary experiments. Our experimental evidence demonstrates that the robot is able to adapt its motion by preserving personal distance from passers-by, and approaching persons who want to interact with the robot. This work contributes to the future development of a human-robot socialization environment.

In this article, we aim to discover the important factors for determining the psychological safety of humanoids and to develop a new psychological scale to measure the degree of safety quantitatively. To discover the factors that determine the psychological safety of humanoids from an ordinary person's perspective, we studied 919 Japanese, who observed movies of 11 humanoids and then freely described their impressions about what the safety of each humanoid was for them. Five psychologists categorized all of the obtained descriptions into several categories and then used the categories to compose a new psychological scale. Then, 2,624 different Japanese evaluated the same 11 humanoids using the new scale. Factor analysis on the obtained quantitative data revealed six factors of psychological safety: Performance, Humanness, Acceptance, Harmlessness, Toughness, and Agency. Additional analysis revealed that Performance, Acceptance, Harmlessness, and Toughness were the most important factors for determining the psychological safety of general humanoids. The usability of the new scale is discussed.

In order for robots to be a part of human society, their social accceptance is an important issue if smooth interaction with humans is to be achieved. We propose a modified social force model that allows robots to move naturally like humans, based on estimated human motion and face pose. We add to the previous model the effect of the force due to face pose, in order to predict human motion and compute the robot motion itself. Our approach was implemented and tested on a real humanoid robot in a situation in which a human is confronted with a robot in an indoor environment. Experimental results illustrate that the robot is able to perform human-like navigation by avoiding the human in a face-to-face confrontation. Our system provides accurate face pose tracking that allows a robot to have a more realistic behaviour compared to the original social force model.

This study identifies the basic general perspectives that ordinary people use to evaluate humanoids (Study 1). In addition, it develops a new psychological scale to quantify general impressions regarding humanoids based on these basic perspectives (Study 2). In Study 1, to discover the basic perspectives toward humanoids, we used 11 humanoids and collected data from 919 Japanese people ranging from teenagers to people in their 70s in three big cities. We asked people to describe their impressions in free text about the robots. Five psychologists analyzed the qualitative data to categorize all the descriptions into several categories. Then, we made the items based on the obtained descriptions to construct a new psychological scale for evaluating general impressions regarding humanoids. In Study 2, we asked 2,624 Japanese who did not participate in Study 1 to evaluate 11 humanoids on the developed scale. Factor analysis showed that nine factors should be used for evaluating the general impressions regarding humanoids: Familiarity, Repulsion, Performance, Utility, Motion, Sound, Voice, Humanness, and Entitativity. The factor structure is clear and its reliability as a psychological scale is satisfactorily high. Finally, we discuss the usability of the new scale.

For an object recognition task in an unknown environment, we propose a novel approach for illumination recovery of surface with cast shadows and specularities by using the object spherical spaces properties. Robust objects recognition in complex environment is fundamental to robot intelligence and manipulation. The proposed method is done for reducing the illumination effects on the objects detection and recognition processes. In this work, objects reference images are regenerated to match the scene lighting environment to increase the success rate of the recognition process. First, a database is generated by computing the albedo and surface normals from captured 2D images of the target objects. Next, the scene lighting direction and illumination coefficients are estimated. Finally, by using the calculated spherical spaces properties we regenerate objects reference data to match the search area illumination condition. In this work, practical real time processing speed and small image size were considered when designing the framework. In contrast to other techniques, our work requires no 3D models for the objects training process and takes images from a single camera as an input. Using our proposed 2D Spherical Spaces experimentally showed noticeable improvements in an objects identification task performed by an autonomous robot in a harshly illuminated environment.

We present our method for learning object categories from the internet using cues obtained through human-robot interaction. Such cues include an object model acquired by observation and the name of the object. Our learning approach emulates the natural learning process of children when they observe their environment, encounter unknown objects and ask adults the name of the object. Using this learning approach, our robot is able to discover objects in a domestic environment by observing when humans naturally move objects as part of their daily activities. Using speech interface,the robot directly asks humans the name of the object by showing an example of the acquired model. The name in text format and the previously learnt model serve as input parameters to retrieve object category images from a search engine, select similar object images, and build a classifier. Preliminary results demonstrate the effectiveness of our learning approach.

The aim of this study was to compare a robot designed using a virtual reality (VR) system (termed VR robot) with a real robot by using a psychological evaluation to investigate whether the VR robot can be used in the same manner as a real robot. To make the direct comparison between a VR and real robots possible, the same designed robots in both VR and real are used in the experiment. For evaluating the robots on a psychological basis, we focused on six basic dimensions (Utility, Clumsiness of motion, Possibility of communication, Controllability, Vulnerability, and Objective hardness) that ordinary people generally use to perceive robots. Sixty-one participants observed and evaluated a real and VR humanoid robots using a psychological scale. Results show that the real robot was evaluated to have higher scores for Utility, Possibility of communication, and Objective hardness and lower ones for Controllability as compared to a VR robot. The Vulnerability scores of the real robot and the VR robot were not significantly different. The usability of a VR robot is discussed in the paper.

The ability to recognize novel items in complex environment is fundamental to robot intelligence and manipulation. In this work, we consider the issue of segmenting visual and physical aspects of novel objects of interest, specifically ones that are being seen for the first time and located in the proximity of unidentified obstacles. Illumination at different wavelengths and angles are projected by a robot, thus acquiring additional information about the scene and exploiting it for successful novel objects segmentation. By analyzing shades and reflections of a scene's objects, we were able to form and identify true edges and visually separate items of interest. In order to recognize the physical characteristics of segmented objects, we introduce a novel material classification technique which utilizes static electricity charge sensing. Our proposed methods do not require predefined models of target objects and assume no previously assigned targets' pose. Using extracted object visual and physical aspects, an autonomous robot manipulator successfully performed a trash separation task.

In the field of bioscience, such as regeneration medicine and cloning, the manipulation and analysis for cells are performed by many researchers. However, manual operation for such micro objects is not feasible and practical for beginner operators. As for the problem, we have developed a two-fingered microhand supporting manual operation. Using the microhand, we can manipulate cells i.e., grab, rotate, carry, and so on - like when using chop sticks. The stiffness measurement of a cell is a key approach in single cell analysis techniques. It is important in indicating cell condition, because the stiffness of a cancer cell is lower than that of a normal cell as an example. However, measuring stiffness is very difficult, because deformations of cell are plasticly, and many researches to measure the stiffness of cell don't deal with plastic deformation. So, in this paper, the cell hardness is calculated instead of cell stiffness by measuring the reaction force caused in the process of cell deformation via a micro force sensor attached to the end-effector of the microhand. Our results point out that this can be one efficient measurement method for acquiring cell hardness. In this paper, three topics are discussed. First one is the fabrication of the end-effector with micro force sensor. Second one is the method of measuring hardness of cell. As a last one, the hardness of the fibroblastic cell is measured by proposed method and the effectiveness of the proposal technique is shown.

For potential applications in bioscience, a two-fingered microhand with dexterous manipulation capability was developed. This microhand system could perform dexterous tasks such as cell rotation, single cell pick-and-place, cell patterning, and measurement of mechanical properties of living cells. However, it is a tedious task to manipulate micro objects manually. In order to improve the efficiency of the system, automated micromanipulation is required. This paper describes how to automate micromanipulation for this two-fingered microhand so that it can perform desired tasks more efficiently, more accurately, and faster. By integrating an All-In-Focus imaging system to the microhand system, 3D positions of the two microfinger tips and micro target objects can be obtained. These 3D positions are necessary for the microhand to handle the target object automatically. We demonstrate this capability by a pick-and-place task with multi-sized microspheres. Short time for object grasping and success rate over 70% for all cases could be achieved.

In this study we explored basic dimensions used to perceive humanoid robots and developed a scale to evaluate perception of humanoid robots, PERNOD. Previous studies of perception of humanoid robots used psychological scales created for interpersonal perception between humans. This study clarified the basic dimensions of perception of humanoid robots and developed PERNOD by means of psychological methodology. The results revealed six basic dimensions of perception of humanoid robots: Utility, Clumsiness of motion, Possibility of communication, Controllability, Vulnerability, and Objective hardness. The 6 dimensions of PERNOD were originally developed for humanoid robots. Thus, these dimensions represent the organization of knowledge used in the recognition of humanoid robots. Usability of PERNOD was discussed.

New gait planning using a nonholonomic model with difference equation constraints is proposed for biped robot walking. A model of a pivoting telescopic segment is used as the kinematic foothold selection model of a bipedal robot. The repetitive and discontinuous constraints of pivoting, expanding, and contracting make up the set of walking trajectory data. The k-step reachable region is defined as the set of the k-th state that the system can reach from the initial state, and the motion planning is solved using the Jacobian matrix of the state with regard to the input series. The difference equation constraints can be discussed as a digital control of continuous-time nonholonomic systems. The gait planning is modified based on the limiting condition for the HRP-2 humanoid robot. Energy consumption is evaluated based on the linear-pendulum model and the gait planning is optimized. The feasibility of the proposed walking planning is demonstrated through a numerical simulation and an experiment involving the HRP-2 humanoid robot.

A new method for bipedal walking on rough terrain by using ZMP criteria map is proposed. The rough terrain walking is classified to “step up” and “step down” by landing timing of a swing leg. The walking pattern is modified in real-time according to the difference between the ideal timing and the measured timing by a force sensor on the foot. In the case of “step up”, the landing timing is faster than the ideal, and the swing leg trajectory should be change to follow the step so that the ZMP based balance of the sudden caused double support phase is kept. In the case of “step down”, the landing timing is later than the ideal, and the swing leg trajectory should be change to seek the ground so that the balance of the unknown future double support phase is kept. The modified walking pattern is decided based on the ZMP criteria map. The ZMP criteria map can indicate a safe landing timing and landing position of a swing leg. By referring the ZMP criteria map, the robust walking pattern can be planned. The proposed method is implemented to HRP-2, and the effectiveness is confirmed through experiments.

Finding objects and tracking their poses are essential functions for service robots, in order to manipulate objects and interact with humans. We present an approach for object detection and 3D pose estimation for autonomous mobile robots, that is suitable for general uses in a modularized robot control system. Our approach extracts local features from the input images, searches for the reference pattern, and then produces the 3D pose in camera coordinate system, using only a single reference image and the 6-DOF pose in it. We have created an RT (Robot Technology) component that can be used in any RT-based system, and developed an algorithm that can extend the range of detection and produce robust pose estimation. For evaluation, we have integrated our vision component in an autonomous robot system with a search-and-grasp task, and tested it with several objects that are found in ordinary domestic environment. We present the details of our approach, the design of our modular component design, and the results of the experiments in this paper.

A two-fingered micro hand has been available for use for years and allows dexterous manipulation of a single cell: grabbing, positioning, rotating and releasing. The end-effector of this micro hand consists of two glass needles; however, the glass tips must be finely adjusted and the micro hand must be calibrated prior to use. Because these initial procedures require highly skilled human operators and a great deal of time, a fine adjustment module (FAM) has been developed for assisting with the fine adjustment work and was successfully shown to make the initial setup easier. However, problems with the calibration process and with the dependence on a user of the FAM control are still present. One means of improving the system for users is to automate the initial setup. The detection of the glass tips in a wide range of Z directions from a microscopic image having a small depth of focus requires robust calibration and must be possible using an automated FAM control. From this perspective, the tip position detection algorithm using the evaluation function, Image Quality Measurement (IQM), is proposed in this paper. Based on this algorithm, the automated initial setup method is explained and its effectiveness is experimentally evaluated.

In this paper, we propose a sensor for detecting particles flowing in a micro channel fabricated with polydimethylsiloxane (PDMS) chip. A light source placed at one side of a micro channel irradiates the micro channel through plastic optical fibers (POF), and a detector placed at the opposite side of the micro channel receives light transmitted through the POF. Since this sensor simultaneously detects plural particles with a diameter of around 100 ¿m flowing in a micro channel, it can be implemented in automatic measurement systems of cells in desktop bio plant, on which automated embryonic cell manipulation is achieved using micro robotics technology.

A new convergence calculation method of the normal distributions transform (NDT) scan matching for high resolution of grid maps is proposed. NDT scan matching algorithm usually has a good effect on large grids, so it is difficult to generate the detailed map with small grids. The proposed method employs interactive closest point (ICP) algorithm to find corresponding point, and it also enlarges the convergence area by modifying the eigenvalue of normal distribution so that the evaluation value is driven effectively for the pairing data. In addition, outlier elimination process is implemented to the scanning for sub-grid scale object. The scanning data from laser range finder (LRF) have error but its set of detected small object can be clustered to determine the center of mass (CoM) and the outlier data. The outlier commonly locates behind true points and it can be eliminated when the robot observes from other point. Experimental result shows the effectiveness of the proposed convergence algorithm and outlier elimination method.

In this paper, we presented a design for an automated cell supply system that can be used with complex microfluidic applications requiring single cell loading such as the current nuclear transplantation method. The aim of the system is to automatically transfer mammalian donor (~15 ¿m) or egg (~100 ¿m) cells one by one from a container to a PDMS micro-channel and then transport them to other modules. The system consists of two main parts; a single cell suction module, and a PDMS-based microfluidic chip controlled by an external pump. The desired number of vacuumed cells can be directed into the microfluidic chip and stored in a docking area. From the batch, they can be moved to next module by activating pneumatic pressure valves located on two sides of the chip.

Recently, human-friendly robots such are mainly focused on their functions. And, based on these functions, many researchers have tried to realize good applications for convenient human life. While, a mental safety and affinity for human are also important topics to co-existence with robots. The evaluation techniques of robot motion and design are necessary to consider the above things. However, the costs of real robot are very expensive. So, it is difficult to evaluate human impression for several real robot. So, to solve this problem, we have focused on the evaluation techniques by using virtual reality. In the previous work, several types robot design were evaluated on virtual reality by using meta model, which is abstraction model of robots. When researchers want their robot to reflect an evaluation result on virtual reality, there are some relationships between virtual robot and real one. If there is no relation from real robot and virtual one, we cannot do any feedback to real robots based on virtual one's results. In this paper, we evaluate the relationships between virtual robot and real one based on human impressions through several experiments.

New robotic systems will be playing an essential role in the future dismantling service for renewing office interiors facilities in buildings. In our study, the dismantling task would be achieved by proper collaboration between human workers and robots utilizing mobile arms, interface devices and software. This paper describes an overview of the proposed dismantling system as well as its requirements. The real experiments presented are focused on the disassembling task of a ceiling lamp panel (LP). In the disassembling task, a robot arm collaborates with the human worker holding the LP, accomplishing an assisting function. At first, in order to approach the robot to the holding position, the worker controls the robot using interface devices which are also evaluated in their usability aspect. Then, a laser pointer fixed at the robot’s tip is used both as a guidance in the teleoperation process and as a first indicator of the holding position. As a second step toward the target, the control program applies model-based 3D object recognition techniques to calculate the final position. At this stage the information of an stereo camera, configured as an eye-in-hand system, is necessary. On the last part of the task, the robot reaches the estimated position automatically by using the results of its kinematic analysis. The experimental results show the effectiveness of the proposed methodology.

A ladder climbing motion for limb mechanism robot “ASTERISK” is proposed. This robot has six legs. The upper three legs hold on the upper rung from its both sides alternately, just like pinching it. The lower three legs hold on the lower rung in the same way. Hence the robot can climb the ladder stably. Depending on the posture of the robot, when it lifts up its body, the robot automatically selects the legs supporting the robot’s weight and distributes the weight to these legs based on their force margins. The legs which cannot support forces are controlled to always contact with the rungs so that the robot holds the ladder firmly. The advantages of proposed gait and control method are verified by the analysis of the supporting range and the torque, and by experiment on force distribution.

The paper presents a new convergence calculation method of the Normal Distributions Transform (NDT) scan matching for high resolution grid map. The proposed method employs Interactive Closest Point(ICP) algorithm to find corresponding point, even if the input scan points are in the outside of the reference grid area. It also enlarges the convergence area by modifying the eigenvalue of normal distribution so that the evaluation value can be driven effectively by all the pairing data for improving convergence speed. In the normal NDT scan matching algorithm, the grid size especially has much effect on the capability of convergence area and speed. Thus, it is difficult to generate the detailed map with small grids. The proposed convergence approach can solve the problem by the phased adjustment of convergence area. Experimental result shows the feasibility of the detailed environmental map generated by the NDT grid mapping.

This paper describes research and development of a compact vision system for real-time cell detection and manipulation in a capillary in order to apply on the “Automated Nuclear Transplantation” project which will achieve sort of cell manipulation tasks such as positioning, cutting, sizing, and so on, automatically between different interconnected modules. Here, we propose a vision system boarded on a PDMS based silicon chip, which can be utilized in a complex network for continuous monitoring of mammalian egg and donor cells of sizes in the range of 10 to 100 micron. The developed prototype has sufficient resolution and is accompanied with a robust detection method for cell-based microfluidic applications.

In the renewal process of office interiors, a robotic system is needed in order to assist the human workers engaged in this kind of job. Regarding the items in the ceiling side, after the dismantling task of the ceiling panels, it is necessary to remove carefully the screws that once held these boards to the Light Gauge Steel (LGS), with the purpose of reusing. The proposed methodology to achieve the task consists at first of the LGS detection. Such detection is useful as a first approach to detect the screws because a trajectory under and near of that metal-ceiling structure can be generated for a scanning process. In both tasks, a stereo camera configured as an eye-in-hand system is necessary. During the motion under the structure, the screws are detected by applying a multi-template matching process to every caught image. A multi-frame integration increases the robustness in the screw detection process. The results of all the processed images along the trajectory are analyzed in order to measure both the true and the false positive detection rates of the screws attached to the LGS and to measure the 3D position of each one.

We tackle a fish-catching task under a visual feedback hand-eye system with catching net. The fishes change escaping trajectory or speed up when being threatened as the net attached at hand approaches to them. Furthermore, as the time of tracking and catching process flows, the fish can somewhat get accustomed to the hand motion pattern and gradually find out new strategies on how to escape from the bothering net. For example, the fish can swim slowly along the pool edge where the net is forbidden to enter or keep a reasonable distance from the net as if it knows the visual servoing system bears steady state error by constant speed escaping. For the sake of such innate ability being widely existed in animal's behavior, the catching operation becomes tough and some effective intelligent method needs to be conceived to go beyond the fish's intelligence. The purpose of this research is to construct intelligent system to be able to exceed the fish's intelligence to survive. Then we embed chaotic motion into the hand motion of robot, and we have shown the chaotic net motion can overcome the fish escaping strategies

This paper presents a method to estimate the 3D pose of a human's head using two images input from stereo cameras. The proposed method utilizes an evolutionary search technique of genetic algorithm (GA) and a fitness evaluation based on a stereo model matching. To improve the dynamics of recognition, a motion-feedforward method is proposed for the hand-eye system. The effectiveness of the method is confirmed by the experiments where the motion of the hand-eye camera compensated for the relative motion of the object in camera frame, resulting robust recognition against the hand-eye motion.

This study is intended to build a controller of redundant manipulator with the simultaneous ability of trajectory tracking and obstacle avoidance without any preparation of path planning to achieve full automation even for one production of one kind, while keeping the avoidance ability high and keeping its shape away from obstacle to reduce the possibility that the manipulator crashes to the obstacle. To evaluate the avoidance ability of the intermediate links, a scalar value of avoidance manipulability shape index (AMSI) was proposed, which is independent of the obstacle's shape. On the other hand, the danger to crash to the obstacle is depending on the shape of the obstacle, which could be evaluated by the potential field set around the obstacle. This paper just proposes a control method of the manipulator's shape based on avoidance manipulability shape index with potential (AMSIP) to simultaneously avoid obstacle and keep the avoidance ability high while tracking the hand trajectory

Force and torque induced by traveling motion of a mobile robot effect dynamically to the objects being carried on it. If the induced force and torque should be bigger than the static friction force and torque exerting between the carrying objects and the mobile robot, the carrying objects start to slip on it. Since this slipping motion causes increasing the acceleration of the mobile robot, then the slipping of one object leads to a dangerous collapse of all carrying objects. Furthermore it interferes with accurate traveling motions. Then we propose a fastest guidance control method with acceleration restriction of power wheeled steering (PWS) mobile robot to prevent slipping of carrying objects. The performances have been examined by simulations and experiments

On the basis of an analysis of the interaction between a manipulator for grinding process and a working object in the task space, motions of the constrained dynamics of the robot is modeled first in this paper. In the model, the constrained forces are expressed as an algebraic function of the state and input generalized forces by using the equation of constraints. Using this result, a new sensorless force control law is proposed by taking the advantage of the redundancy of input generalized forces to the constrained forces. A controller for a grinding robot is then constructed according to this control law and without involving any force sensors. Grinding experiments have been done for evaluating the feasibility of the controller by taking an articulated planar two-link manipulator as an example. Results show that the constrained force is explicitly controlled by proposed control law. The effectiveness of the controller for real grinding task has been verified.

This paper proposes trajectory tracking and obstacle avoidance control using avoidance manipulability of redundant manipulators. We propose two evaluation indexes of whole shape of the redundant manipulators. First one is sum of singular value of avoidance matrix. Second one is sum of the volume of avoidance manipulability ellipsoid. We evaluate whole manipulator's shape by two indexes and compare the ability. We found the second one is better than the first. We call the second index avoidance manipulability shape index (AMSI). Finally, by using AMSI, we construct trajectory tracking/obstacle avoidance control system. And we confirm the performance of trajectory tracking by simulations.

This paper proposes a gait control algorithm for limb-mechanism robot on rough terrains and slopes. The concept of the "limb-mechanism" is to integrate functions of legged locomotion and arm manipulation. A limb can be used as a leg and an arm according to different situations. Each limb radiates out in six directions and the robot has a symmetrical configuration in horizontal and vertical directions. The robot can walk into any direction using a simple motion planning where the same trajectory is assumed in each leg. This trajectory is generated on a cylindrical volume which is defined in the leg workspace. The robot has a touch sensor at the tip of each leg. The sensor can detect the contact with the ground, and the legs can stay on the ground stably. When the robot walks on a rough terrain, the body is inclined in parallel to the virtual plane defined by leg supporting points in order to use the leg workspace effectively. The stability margin of the robot can be also improved easily by changing the leg trajectory.

When robots coexisting with humans are designed, it is important to evaluate the influence of the shape and size of the robots and their motions on human sense of security. For this purpose, an evaluation system of human sense of security for coexisting robots using virtual reality is discussed. Virtual robots are visually presented to a human subject through a head mounted display; the subject and the robots coexist in the virtual world. Some kinds of physiological indices of the subject are measured, he answers the questionnaire about his impression of the robots, and his sense of security is evaluated. Because of using virtual reality technique, the shape and size of the robots and their motions can be easily changed and tested. In the present report, pick and place motion of humanoid robots is evaluated. As a result of analyzing the questionnaire, it is found that turning the body coordinating with the arm gives good impression on humans.

An integrated visual and haptic display using translucent and flexible sheet such as rubber is proposed. This display varies the compliance of the sheet in the normal direction by changing the bias tension of the sheet: tightly stretched sheet feels hard, and loosely stretched sheet feels soft Hence a user can feel compliance of various virtual objects when he pushes the sheet. This sheet is also used as a rear projection screen; an LCD projector projects the image on the sheet from its back. When the user's finger pushes the sheet, the position and deformation of the pushed point are measured by stereo vision. The deformation of the virtual object is calculated by FEM, and the graphical model of the deformed object is generated. The user sees both the image of the object projected on the sheet and his own finger pushing the image. As a result, the proposed visual and haptic display allows users to feel like pushing virtual soft objects with their fingers directly. It is ascertained that the developed display can generate variable compliance and simulate the compliance of a real soft object. Human subjects feel like seeing and pushing a virtual object directly.

This paper proposes a method of building a 3D map composed of static objects for localization of mobile robots using recognition of human actions. In the monitoring systems with fixed cameras and also moving cameras, high-precision localization of moving cameras is required for measuring human actions in detail and precisely. A 3D map of the environment composed of static objects such as walls, desks and shelves is useful for high-precision localization of moving cameras in 3D space, because salient features in the environment are used as landmarks. Furthermore, the 3D map is required for generation of monitoring motion of the moving cameras and recognition of human actions in the relation of the environmental objects. In order to generate a 3D map automatically by measuring 3D points in an environment, points on static objects have to be selected from measured points, because there are dynamic objects such as chairs, books, and other mobile things in the environment. The proposed method generates a 3D map for localization by selecting points on static objects from measured 3D points based on recognition of human actions. Experimental results show feasibility of our proposed method.

Mobile manipulation control method for humanoid robots provides good manipulability and stability on manipulation tasks. This method leads whole body motion and locomotion, when the manipulator tip trajectory is decided. For the dexterous manipulation, the robot has to cope with the unexpected forces acting to the hands. By assuming the statistical balance, we define the projection of the CoM as "complement zero moment point (CZMP)", when the external forces act to the end-effectors. We propose to use the CZMP for the modification control of CoM with balancing control. The method is implemented to the mobile manipulation control method and the effectiveness is confirmed by the experimental results.

We propose "marionette system" as a master slave teleoperation. The operation/display device which presents form and posture equivalent to the remote robot is named "marionette device". In the system, it is possible, making exact discrimination, to control flexibly the remote robot by using marionette device. Marionette system is the operation/presentation technique which not only enables to operate flexibly all movable joints but to discriminate correctly by checking the marionette device. Since the condition of the marionette device is made almost equivalent to the remote robot, the operator can check and operate the device as treating a doll for judgments of operation. Thus, we named the control system "marionette system." In this paper, we develop the humanoid-robot (HR) type device as an example of the remote control of the humanoid robot. When a humanoid robot is set as an operation target, it becomes easy to transpose and image a robot pattern from human motion. HR type device used as operation/display equipment enables intuitive approach in operation. In order to verify the validity of the proposed system, we have carried out various experiments comparing two types of device. One is conventional the method employing graphic simulators and a joystick, the other is a proposed control/display device employing humanoid type device. The effectiveness of the proposed system is confirmed by the experimental results.

A control method for humanoid robots of mobile manipulation is proposed: this method allows accurate manipulation using hands, even when the robots move around. A robot controls its body pose and steps so that manipulabilities of both arms and robot stability can increase, coordinating with the motion of both hands for performing objective tasks. Because of the vibration caused by the impact of foot landing and the slip of the feet, the accuracy of the hand positions and robot stability decrease. For this problem, the robot measures real hand positions and body orientation with its camera and gyroscope. Then the hand positions errors are transformed to correcting joint angles of the arms using arm Jacobian matrices. Adding the calculated joint angles to the desired joint angles of the arms, the arms can compensate the hand positions. New desired joint angles of the legs are calculated by inverse kinematics from real foot positions and desired shoulder position. Adding the correcting joint angles to the desired joint angles of the legs, the legs can compensate the shoulder position, thus increasing robot stability. The effectiveness of the proposed method is ascertained by simulations.

A control method for humanoid robots of mobile manipulation is proposed. A robot autonomously steps or controls its body pose while performing various manipulation tasks with its hands; that enables dexterous and stable manipulation. Two hands always move along their desired trajectories by impedance control for carrying out a given task. Coordinating with this motion of the hands, the robot controls its body and legs so that arm manipulability and robot stability may increase. It determines the next foothold by evaluating manipulabilities of both arms, shape of stable region and moving direction. An evaluation function consisting of manipulabilities of both arms and static stability of the robot is defined, and the robot steps if the new double support state is better than the current one. Both in double and single support states, the robot controls its body pose using the support leg(s) so that this evaluation may be optimal. Various motions of a humanoid robot by the proposed method are simulated.

Calibration methods and parameter estimation analyses of a class of parallel mechanisms are discussed in order to achieve a nano-modon stage applied in the machining of high quality optical devices. The paper includes mechanical structure of Delta type parallel mechanism, its kinematics analyses for calibration, two calibration methods and their comparisons in the aspects of parameter errors, final achieved accuracy and simple procedure. Exclusion of orientation data will be also discussed for the simplicity of measurements in the calibration procedure.

The optimal posture of a humanoid robot for generating large desired force at its hands is discussed. The robot is required to stand stably and to support the force and its weight under the constraint of maximum joint torques. Furthermore, it is important to keep the robot controllable against sudden change in the force. From this point of view, an evaluation function for the task with large force based on statics is proposed; we focus on Jacobian matrices of two arms and legs to give the robot adaptability to force change. Then the method of obtaining the optimal posture, footholds and joint torques of the robot is described. Effectiveness of the method are verified through computer simulations.

An automated calibration for micro-hand is proposed to obtain high quality micromanipulation system. The calibration is based on automatic focusing of micro-object and its position detection in the microscope frame using microscope images. The automatic focusing works well even in the tracking of moving target using chromatic aberration. The finger position can be detected automatically by integrating focusing and identification of the micro-hand finger wherever it is in the microscope view. These automated processes are implemented in the actual system. The experiment shows the system can attain around 2[/spl mu/m] in absolute positioning accuracy.

We propose a method of relocating storage devices attached to the environment for sharing knowledge efficiently among multiple robots. If a robot stores acquired knowledge into the storage device, other robots can achieve the task by using the knowledge. Since the memory size of the storage device is limited, usefulness of the knowledge is evaluated with respect to the reducible cost. A memory unit containing useless knowledge is removed from the storage device and added to the device where more useful knowledge is required. Then, the robots can store useful knowledge for the whole environment and the memory units are flexibly relocated according to the change of a series of the tasks. The simulation results of multiple robots navigation for repetitive transportation tasks show the effectiveness of our method.

This paper describes a method of analyzing the error of dead reckoning of multilegged robots. In dead reckoning of multilegged robots, the body posture and contact positions of legs are alternately estimated. The estimated error is accumulated in locomotion. We derive the basic equations for estimation of the error of body posture and the contact positions based on the small displacement analysis. The 3D distribution of the error is analyzed by singular value decomposition.

Proposes a method of object recognition using appearance models accumulated into a RFID (radio frequency identification) tag attached to the environment. Robots recognize the object using appearance models accumulated in the tag on the object. If the robot fails in recognition, it acquires a model of the object and accumulates it to the tag. Since robots in the environment observe the object from different points of view at different time, various appearance models are accumulated as time passes. In order to accumulate many models, eigenspace analysis is applied. The eigenspace is reconstructed every time robots acquire the model. Experimental result of object recognition shows effectiveness of the proposed method.

A real-time control method for a humanoid in mobile manipulation, doing tasks with its arms while moving, is proposed. The arm tips always follow their desired position with external force applied by impedance control, for carrying out a given task with the arms. An evaluation function consisting of not only stability but also arm manipulability-both are important for mobile manipulation-is defined; the humanoid controls its body and legs so that this evaluation may be optimal. As a result, the humanoid autonomously steps or keeps standing, coordinating with the arm tips motion. The effectiveness and usefulness of the proposed method are ascertained by computer simulations on a humanoid of human-size and experiments using a small experimental robot.

There has been always a workspace problem with parallel mechanisms. This paper discusses the workspace of the parallel mechanisms and its enlargement by adjusting their link parameters. The basic idea is to cover a whole required range of workspace with small pieces of one. A fixed linear type mechanism is selected to analyze and to evaluate its adjustable workspace. The analyses of simple 2 DOF plane model show that additional spaces are obtainable, which cannot be reached by the conventional mechanism due to its singularity. More detailed analyses and evaluations are discussed based on a 6 DOF spatial model.

The concept of virtual operating environment (VOE) used for teleoperation of various machines is proposed. A virtual cockpit for each machine is constructed within a computer: it consists of virtual input devices such as switches and joysticks, meters or indicators, and TV monitors displaying the images from the machine-mounted cameras. The cockpit is displayed to an operator through a head-mounted display. In the real world, a manipulator presents the virtual input devices by turns; the operator handles the end-effector of the manipulator, regarding it as the input device. VOE can provide different types of operating environment for various machines simply by switching softwares. One of the most important techniques for VOE is the simulation and presentation of various input devices with a manipulator. The manipulator simulates the switch using the obtained impedance model. It is ascertained by experiment that the manipulator can present two different switches.

A hybrid cylinder/cable drive parallel arm and its motion control are discussed. The basic idea of the hybrid parallel arm is to make the best use of the mixture of the high power cable drive and the cylinder actuation to obtain a heavy-duty manipulator in construction and ship building applications. A prototype arm has been designed and built based on the analysis and the comparative study of several types of hybrid drive mechanisms, the Stewart platform, and a wire drive mechanism. The tension of wire has to be maintained properly in the hybrid mechanism during its motion. The proposed hybrid arm is a kind of actuation-redundant mechanism and its internal force can be freely controlled. The proposed control algorithm is to give wires proper tension during its motion by exploiting the internal force, The required tension and cylinder force can be obtained by compensating each link position command based on its compliance. The repeatability tests show the effectiveness of the proposed algorithm in maintaining the overall stiffness of the arm.

The research aim is to apply locomotive robots to rescue tasks, such as searching for sufferers and removing obstacles to save sufferers. The paper discusses the exploitation of arm and leg integrated robots and basic experiments of infrared probing sensor, in the application of rescue tasks. First, the limb mechanism is introduced and discussed in the aspect of locomotion capability and stability in rough terrain of disaster area. Then, the probing sensor is evaluated in the aspect of its detection range and capability. Assuming the sensor is mounted on the tip of robot arm for probing, the probing algorithm is proposed to find quickly and locate precisely a sufferer. The basic experiments have been carried out using a parallel arm to confirm the applicability and the usefulness of the proposed rescue system.

In order to develop a high performance working robot, we design and develop a new robot based on the concept of "limb mechanism " for integration of legged locomotion and arm manipulation. The robot developed has six limbs which can be used for both locomotion and manipulation. The six limbs are set on vertices of regular hexagonal body so that this robot can have omnidirectional manipulability and mobility. We evaluate the stroke and the stability margin in all walking directions on six-legged and four-legged locomotion. As a result, this robot has higher omnidirectional mobility than conventional mechanisms.

This paper describes mobile manipulation of humanoid robots. A humanoid robot is a kind of integrated machines: two arm and two leg mechanism. It could be well applied to mobile manipulation in nonroutine task automation. The main objective of the mobile manipulation is to obtain versatile and efficient manipulation by the arms. In this respect the legs are required to assist the arms obtaining their high manipulability by changing step length and timing of step motion. Accordingly, the required motion of the legs in mobile manipulation is different from conventional biped locomotion. From this point of view, the relationship between manipulability of the arm and various leg motions is analyzed and evaluated by computer simulations.

A real-time robot arm control method for obstacle avoidance is proposed. If links are close to and approaching obstacles, the end-effector velocity is modified so that collision is avoided and the error between the desired and modified end-effector velocity can be minimized. For this purpose, a new matrix called the "collision Jacobian", which relates the approaching velocity of the links to the obstacles with the end-effector velocity, is proposed. Because the modified velocity can be calculated without an iterative algorithm, the proposed method is effective for real-time obstacle avoidance. This method is applied to collision avoidance between the links of a parallel arm.

A compact and economical 3-DOF finger module for micro manipulation is developed; it is designed for a two-finger micro manipulator which can manipulate micrometer-size objects dexterously like chopsticks. A 3-DOF parallel mechanism for this finger is proposed, and its inverse kinematics between the end effector position and the actuator displacements is formulated. The design parameters are determined so that its workspace volume may be as large as possible. A prototype using three piezo-electric actuators and two types of flexure joints, which are proposed for realizing a compact finger, is developed. The Jacobian matrix used for calculating the actuator displacements corresponding to the given end effector position is obtained by experiments. The repeatability and absolute positioning accuracy-about 2.0 /spl mu/m-of this prototype are evaluated.

A new hybrid cylinder/wire drive parallel arm (simply called "a hybrid arm") for manipulating heavy materials in construction and ship building works is proposed. Various hybrid arms with different combination of cylinders and wires are compared with the conventional Stewart platform and a multiwire drive mechanism. Their workspaces considering orientation are evaluated. The most suitable hybrid arm for heavy material handling is the mechanism with three cylinders, four wires, and one connecting rod between the cylinders and the end plate. This hybrid arm is modified into a mechanism with a variable length rod for the application of manipulating a precasting concrete board with a size of 3/spl times/6/spl times/0.2 m/sup 3/ and a weight of 10 t which is used in automatic building construction systems; a prototype of this arm has been designed and developed.

This paper describes a method of extracting a moving object in a 3D space in a cluttered background by integrating optical flow and edges. The method extracts objects even if their appearance change and the flow vectors of the objects are not uniform. We segment the image into regions so that the motion of each region may be approximated by the 3D motion of a plane. In order to represent the whole contour of the regions even in a cluttered background, the brightness edges near the motion boundary are accumulated over frames. The contour of the region is composed of the motion boundary and the accumulated edges. The object is composed of adjacent regions which have similar 3D motion parameters. Experimental results for synthetic and real images show that this method extracts objects even if the appearance of the objects change drastically.

This paper describes a method of determining contours of moving objects in a cluttered scene by integrating optical flow and edges. If the motion of an object is similar to that of the background, the contour is not determined only by optical flow. If the background of a scene is cluttered, the contour is not determined only from edges because many edges may be extracted in the background and no edges may be extracted on some parts of the contour. In the proposed method, the contour is determined by using optical flow and edges in a long sequence. The whole contour of a moving object is eventually obtained by accumulating edges near motion boundaries over an image sequence. The method can also determine the occlusion relation of two overlapping objects by checking if edges exist on the predicted contours of objects. Experimental results for synthetic and real images show the usefulness of the method.

This paper describes real time object tracking by extracting optical flows from a sequence of images. Optical flows are calculated based on the generalized gradient model. Our method detects a moving object, and tracks it from the optical flow data. Assuming that pixels corresponding to the same object have similar flow vectors, we extract a connected region with similar flow vectors. We apply this method to multiple object tracking. When two objects overlap, foreground object is recognized, and each object is tracked without confusion. Optical flow extraction and object tracking are executed in realtime by a special image processor.