Robot manipulator hybrid control for an unknown environment using visco-elastic neural networks

K. Kiguchi, T. Fukuda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Robot manipulators are expected to perform more sophisticated tasks under unlimited environment. In order to realize these tasks, the robot manipulators have to be flexible enough to work in an unknown environment. In this paper, we propose an effective adaptive neural network feedback controller for hybrid position/force control of robot manipulators for an unknown environment by applying new types of neurons which possess visco-elastic properties. The unexpected overshooting and oscillation caused by the unknown and/or unmodeled dynamics of a robot manipulator and an environment can be decreased efficiently by the proposed visco-elastic neurons. The effectiveness of the proposed visco-elastic neural network controllers is evaluated by simulation with the model of a 3-DOF direct-drive planar robot manipulator.

Original languageEnglish
Title of host publicationProceedings - 1998 IEEE International Conference on Robotics and Automation, ICRA 1998
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1447-1452
Number of pages6
ISBN (Print)078034300X
DOIs
Publication statusPublished - 1998
Externally publishedYes
Event15th IEEE International Conference on Robotics and Automation, ICRA 1998 - Leuven, Belgium
Duration: May 16 1998May 20 1998

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
Volume2
ISSN (Print)1050-4729

Other

Other15th IEEE International Conference on Robotics and Automation, ICRA 1998
Country/TerritoryBelgium
CityLeuven
Period5/16/985/20/98

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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