This paper presents the effectiveness of a time-delay compensation method based on the concept of network disturbance and communication disturbance observer for bilateral teleoperation systems under time-varying delay. The most efficient feature of the compensation method is that it works without time-delay models (model-based time-delay compensation approaches like Smith predictor usually need time-delay models). Therefore, the method is expected to be widely applied to network-based control systems, in which time delay is usually unknown and time varying. In this paper, the validity of the time-delay compensation method in the cases of both constant delay and time-varying delay is verified by experimental results compared with Smith predictor.

The purpose of this study is to develop an interactive communication system that communicates with human beings emotionally. Since the face and its expressions are the most important role for natural communication, we have been developing a face robot that can express facial expressions similar to human beings. In this study, we show a new type face robot SAYA. All McKibben pneumatic actuators are distributed to the surface of the face like a human muscle in order to improve the structure of the face robot and facial muscle movement (Action unit) for natural facial expressions. Since the bending manner of coil spring might be similar to human cervical vertebra, we developed the new head motion mechanism by using coil spring for realizing human like head motion. In this paper, we describe the structure of face robot SAYA and the way of constructing new neck mechanism. We have confirmed that SAYA has ability to express fine facial expressions

Robots are required to autonomously respond to changing situations. Imitation learning is a promising candidate for achieving generalization performance, and extensive results have been demonstrated in object manipulation. However, cooperative work between humans and robots is still a challenging issue because robots must control dynamic interactions among themselves, humans, and objects. Furthermore, it is difficult to follow subtle perturbations that may occur among coworkers. In this study, we find that cooperative work can be accomplished by imitation learning using bilateral control. Thanks to bilateral control, which can extract response values and command values independently, human skills to control dynamic interactions can be extracted. Then, the task of serving food is considered. The experimental results clearly demonstrate the importance of force control, and the dynamic interactions can be controlled by the inferred action force.

Contact-rich tasks, wherein multiple contact transitions occur in a series of operations, have been extensively studied for task automation. Precision assembly, a typical example of contact-rich tasks, requires high time constants to cope with the change in contact state. Therefore, this letter proposes a local trajectory planning method for precision assembly with high time constants. Because the non-diagonal component of a stiffness matrix can induce motion at high sampling frequencies, we use this concept to design a stiffness matrix to guide the motion of an object and propose a method to control it. We introduce reinforcement learning (RL) for the selection of the stiffness matrix because the relationship between the desired direction and the sensor response is difficult to model. An architecture with various sampling rates for RL and admittance control has the advantage of rapid response owing to a high time constant of the local trajectory modification. The effectiveness of the method is verified experimentally on two contact-rich tasks: inserting a peg into a hole and inserting a gear. Using the proposed method, the average total time needed to insert the peg in the hole is 1.64 s, which is less than half the time reported by the best of the existing state of the art studies.

This paper proposes a tactile-sensing mechanism for a robot. The mechanism is composed of a force-sensor device and an end-effector of shell shape. Since the end-effector plays the role of an outer shell, a force can be sensed at any position on the body. Due to the aspect of its intrinsic contact sensing, position of the single contact point is calculable without any sensor array. Another advantage is that the six-axis resultant force is measurable. This paper shows that the mechanism is also available for the end-effector with an angulated shape. The only condition for the shape is to be a convex hull. Some experimental results evaluate sources of error in practical measurement and show the validity of the proposed mechanism.

[出版社版](c)2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.Smith predictor is a well-known method for compensating time delay in control systems. Therefore, it has been applied to many systems with time delay so far. However, delay time should be estimated precisely in this method. So, if time delay is fluctuant and unpredictable, like the communication delay over the Internet, performance of Smith predictor deteriorates. This paper proposes "Communication Disturbance Observer". It regards the error caused by time delay as disturbance torque (or acceleration), then it can observe and compensate the error. Furthermore, it doesn't need to estimate the value of delay time; therefore it can be applied to control systems with fluctuant and unpredictable time delay. It can be said that control system with "Communication Disturbance Observer" is robust to time delay and fluctuation of that. Effectiveness and robustness of proposed method is shown by result of simulation and experiment. In experiment, master-slave manipulator was used over the Internet. We were able to get the sense of touch from the environment of remote site