Yasuo Nasu

Control of walking robots based on manipulation of the zero moment point

In this paper, a new application of the ZMP (Zero Moment Point) control law is presented. The objective of this control method is to obtain a smooth and soft motion based on a real-time control. In the controller, the ZMP is treated as an actuating signal. The coordinates of the robot body are fed back to obtain its position. The proposed control method was applied on two different biped robots, and its validity is verified experimentally.

Optimal trajectory generation for a prismatic joint biped robot using genetic algorithms

Abstract In this paper, a prismatic joint biped robot trajectory planning method is proposed. The minimum consumed energy is used as a criterion for trajectory generation, by using a real number genetic algorithm as an optimization tool. The minimum torque change cost function and constant vertical position trajectories are used in order to compare the results and verify the effectiveness of this method. The minimum consumed energy walking is stable and the impact of the foot with the ground is very small. Experimental investigations of a prismatic joint biped robot confirmed the predictions concerning the consumed energy and stability.

Real time gait generation for autonomous humanoid robots: A case study for walking

Abstract As autonomous humanoid robots assume more important roles in everyday life, they are expected to perform many different tasks and quickly adapt to unknown environments. Therefore, humanoid robots must generate quickly the appropriate gait based on information received from visual system. In this work, we present a new method for real time gait generation during walking based on Neural Networks. The minimum consumed energy gaits similar with human motion, are used to teach the Neural Network. After supervised learning, the Neural Network can quickly generate the humanoid robot gait. Simulation and experimental results utilizing the “Bonten-Maru I” humanoid robot show good performance of the proposed method.

A new control method for walking robots based on angular momentum

Abstract In this paper we present an efficient algorithm for controlling the angular momentum of walking robots through the manipulation of the zero moment point (ZMP). A remarkable feature of our control method is that the ZMP is considered an actuating signal of the controller. The proposed method can be applied in real time situations because it does not need an accurate tracking of joint angles. Its application to walking robots results in a smooth and soft motion. Experimental results, based on a theoretical explanation, verify the validity of the proposed method.

Control of a Biped Walking Robot during the Double Support Phase

This paper discusses the control problem of a biped walking robotduring the double-support phase. Motion of a biped robot during thedouble-support phase can be formulated as motion of robotmanipulators under holonomic constraints. Based on the formulation,the walking gait is generated by controlling the position of thetrunk of the robot to track a desired trajectory, referenced in theworld frame. Constrained forces at both feet were controlled suchthat firm contact is preserved between the feet and ground by using asimplified model of the double-support phase. The control scheme wasevaluated experimentally.

Nonlinear feedback control of a biped walking robot

An implementation of a biped robot which is capable of dynamic walking by a simple nonlinear control algorithm is presented. Four DC servo motors actuate the knee and ankle joints of the legs of the robot. The biped is constrained to the sagital plane, and the motion generation is reduced to a problem of controlling the position and velocity of the robots center of gravity. They are controlled by a nonlinear feedback controller, based on a sample feedback linearization method. Several design issues including mechanical structure, leg actuation, and control system of the robot are discussed. Experimental results demonstrate the effectiveness of the algorithm.

A CORBA‐based approach for humanoid robot control

Recently, many control architectures for robots have been proposed. However, in these architectures, it is difficult to add new functions to existing applications or add new applications. Moreover, developing a robot control system using many researchers makes it difficult to cooperate with each other. In order to deal with these problems, we propose a Humanoid Robot Control Architecture (HRCA) based on Common Object Request Broker Architecture (CORBA). The proposed HRCA is organized as a client/server control architecture. The HRCA is implemented as an integration of many humanoid robot control modules, which correspond to CORBA servers and clients. By applying these to “Bonten‐Maru I” a humanoid robot, which is under development in our laboratory, we describe the HRCA modules and the effectiveness of HRCA. We confirmed the effectiveness of HRCA from simulation and experimental results. By using the proposed HRCA, the control of the humanoid robot in a distributed environment such as a Local Area Network (LAN) is possible and thus various humanoid robots in the world can share their own modules with each other via the Internet.

Multi-arm robot control system for manipulation of flexible materials in sewing operation

A new automated sewing system is described, consisting of two robots handling the fabric on the table in a similar manner as does a human operator during sewing. To enable user-friendly operation of the system operation, particularly in the phase of preparing new tasks, the original Multi-arm Robot Control (MRC) system has been developed. It incorporates a task-oriented robot language and graphical user interface to enable easy programming of complex motion such as hands coordination during task execution, fabric tension control, and synchronization with the sewing machine speed. To avoid possible collisions, simulation of the already programmed task can be easily performed. The control of hand coordination and the fabric tension has also been developed and implemented. To control seam path and its deviation from the desired trajectory, visual feedback was adopted. Complete system functioning was verified experimentally by sewing.

Low force control scheme for object hardness distinction in robot manipulation based on tactile sensing

This paper presents an application of a low force interaction method in a control scheme of robot manipulation based on tactile sensing. Our aim is to develop an intelligent control system that can distinguish the hardness of unknown objects so that robotic fingers can effectively explore the objects surface without altering its physical properties or causing damage. Initially we developed a novel optical three-axis tactile sensor system based on an optical waveguide transduction method capable of acquiring normal and shearing forces. The sensors are mounted on the fingertips of the multi-fingered humanoid robot arm. We proposed a new control scheme applying low force interaction to distinguish the hardness of unknown objects in robot manipulation tasks based on tactile sensing. The scheme utilized new control parameters obtained by calibration experiments using hard and soft objects that enable robot fingers to precisely control grasp pressure and define the slippage sensation of the given object. Finally, verification experiments of the proposed control scheme using a humanoid robot arm were conducted whose results revealed that the fingers system managed to recognize the hardness of unknown objects and complied with sudden changes of the objects weight during object manipulation tasks.

Obstacle Avoidance in Groping Locomotion of a Humanoid Robot

This paper describes the development of an autonomous obstacle-avoidance method that operates in conjunction with groping locomotion on the humanoid robot Bonten-Maru II. Present studies on groping locomotion consist of basic research in which humanoid robot recognizes its surroundings by touching and groping with its arm on the flat surface of a wall. The robot responds to the surroundings by performing corrections to its orientation and locomotion direction. During groping locomotion, however, the existence of obstacles within the correction area creates the possibility of collisions. The objective of this paper is to develop an autonomous method to avoid obstacles in the correction area by applying suitable algorithms to the humanoid robots control system. In order to recognize its surroundings, six-axis force sensors were attached to both robotic arms as end effectors for force control. The proposed algorithm refers to the rotation angle of the humanoid robots leg joints due to trajectory generation. The algorithm relates to the groping locomotion via the measured groping angle and motions of arms. Using Bonten-Maru II, groping experiments were conducted on a walls surface to obtain wall orientation data. By employing these data, the humanoid robot performed the proposed method autonomously to avoid an obstacle present in the correction area. Results indicate that the humanoid robot can recognize the existence of an obstacle and avoid it by generating suitable trajectories in its legs.