Neuromorphic sensing and control--Applications to position, force, and impact control for robotic manipulators

Toshio Fukuda, Takanori Shibata, Kazuhiro Kosuge, Fumihito Arai, Masatoshi Tokito, Toyokazu Mitsuoka

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

3 Citations (Scopus)

Abstract

The authors present a neural network (NN)-based approach for sensing and control of a robotic manipulator. They corroborate the effectiveness of the proposed approach for impact control of a robotic manipulator. Collisions are very quick phenomena and have strong nonlinearity. Therefore, it is difficult to sense collisions and to control the robotic manipulator undergoing collisions. The proposed approach has robustness against the impact force. It also has effectiveness in sensing and recognition of collisions by using a proximity sensor. In this case, the NN-based controller can acquire desirable manipulation of its own accord, so as to avoid the impact.

Original languageEnglish
Title of host publicationProceedings of the IEEE Conference on Decision and Control
PublisherPubl by IEEE
Pages162-167
Number of pages6
ISBN (Print)0780304500
Publication statusPublished - 1992 Jan 1
Externally publishedYes
EventProceedings of the 30th IEEE Conference on Decision and Control Part 1 (of 3) - Brighton, Engl
Duration: 1991 Dec 111991 Dec 13

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0191-2216

Other

OtherProceedings of the 30th IEEE Conference on Decision and Control Part 1 (of 3)
CityBrighton, Engl
Period91/12/1191/12/13

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modelling and Simulation
  • Control and Optimization

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