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Fuzzy Sensor-Based Motion Control among Dynamic Obstacles for Intelligent Rigid-Link Electrically Driven Arm Manipulators

Authors
  • Wei, Wu1
  • Mbede, Jean Bosco1
  • Zhang, Qisen2
  • 1 Intelligent Control and Robotics Laboratory, Department of Control Science and Engineering Huazhong University of Science and Technology, Wuhan, 430074, P. R. China , Wuhan
  • 2 Changsha Communications University, Department of Highway and Bridge Engineering, Changsha, 410076, P. R. China , Changsha
Type
Published Article
Journal
Journal of Intelligent & Robotic Systems
Publisher
Springer-Verlag
Publication Date
Jan 01, 2001
Volume
30
Issue
1
Pages
49–71
Identifiers
DOI: 10.1023/A:1008190612246
Source
Springer Nature
Keywords
License
Yellow

Abstract

An intelligent motion planning based on fuzzy rules for the idea of artificial potential fields using analytic harmonic functions is presented. The purpose of the combination of a fuzzy controller and a robust controller is to design a realistic controller for nonlinear electromechanical systems such as an electric motor actuating an arm robot. This control algorithm is applied to the three basic navigation problems of intelligent robot systems in unstructured environments: autonomous planning, fast nonstop navigation without collision with obstacles, and dealing with structured and/or unstructured uncertainties. To achieve this degree of independence, the robot system needs a variety of sensors to be able to interact with the real world. Sonar range data is used to build a description of the robot's surroundings. The proposed approach is simple, computationally fast, and applies to whole-arm collision avoidance. The stability of the overall closed loop system is guaranteed by the Lyapunov theory. Simulation results are provided to validate the theoretical concepts, and a comparative analysis demonstrates the benefits of the proposed obstacle avoidance algorithm.

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