Title

Robot Motion Planning by Rules and Strategies Based on Reinforcement Learning Scheme

Editor(s)

Dagli, C. H. and Akay, M. and Chen, C. L. P.|Fernandez, B. R. and Ghosh, J.

Abstract

A planning system for robot arm motion planning is proposed in this paper. The system decides its torque output according to a situation. It learns the mapping from the situation to the output by two kinds of control knowledge: the rule as a basic fragmentary motion and the strategy as a combination of the rules to achieve a given task. Computational simulations are carried out to investigate the behavior of the proposed system.

Meeting Name

1995 Artificial Neural Networks in Engineering

Department(s)

Mechanical and Aerospace Engineering

Keywords and Phrases

Computer Simulation; Intelligent Robots; Motion Control; Robot Learning; Robotic Arms; Torque Control

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 1995 American Society of Mechanical Engineers (ASME), All rights reserved.

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