single-rb.php

JRM Vol.10 No.5 pp. 377-386
doi: 10.20965/jrm.1998.p0377
(1998)

Paper:

Mobile Operations Performed by Mobile Manipulators on Irregular Terrain - Torque Compensation Using Neural Networks for Disturbance Torques Produced by Irregular Terrain -

Mamoru Minami*, Masatoshi Hatano** and Toshiyuki Asakura*

*Department of Mechanical Engineering, Faculty of Engineering, Fukui University, 3-9-1 Bunkyo, Fukui, 910-8507, Japan

**Department of Mechanical and Intellectual Systems Engineering, Faculty of Engineering, Toyama University, 3190 Gofuku, Toyama, 930-8557, Japan

Received:
April 13, 1998
Accepted:
September 18, 1998
Published:
October 20, 1998
Keywords:
Mobile Manipulator, Irregular Terrain, Neural Network, Adaptive Control, Torque Compensation
Abstract
In the present study, we propose a control system for mobile operations of mobile manipulators traveling on irregular terrain. Irregularities exist even in structures such as man-made floors of factories and buildings. Since the hand of a mobile manipulator is often required to operate precisely while traveling on irregular terrain and it is subject to disturbance torques caused by traveling on terrain, a method for decreasing control errors caused by disturbances due to terrain must be considered. In the present paper, an adaptive control system including a compensator that uses a neural network, i.e., a neuro adaptive control system, is proposed. In addition, we discuss the control performance of the proposed control system, and show that the control system can decrease control errors occurring on irregular terrain to the levels of errors that occur while traveling on a horizontal plane.
Cite this article as:
M. Minami, M. Hatano, and T. Asakura, “Mobile Operations Performed by Mobile Manipulators on Irregular Terrain - Torque Compensation Using Neural Networks for Disturbance Torques Produced by Irregular Terrain -,” J. Robot. Mechatron., Vol.10 No.5, pp. 377-386, 1998.
Data files:

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Apr. 18, 2024