Learning in a neuro-fuzzy navigator for robotic manipulators

Kaspar Althoefer, Lrkmal Seneviratne, Bart Krekelberg

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Presents a fuzzy-based navigation system for robotic manipulators. The fuzzy rules combine a repelling influence, related to the distance between the manipulator and nearby obstacles, with an attracting influence produced by the angular difference between the actual and final manipulator configurations, in order to generate the actuating motor commands. The use of fuzzy logic leads to a transparent system that can be tuned by hand or by a learning algorithm. The proposed learning algorithm can be adapted to the particular requirements of a given manipulator, as well as to the environment it operates in. The navigation method has been successfully applied to robot arms in different environments, giving encouraging results.

Original languageBritish English
Title of host publicationICONIP 1999, 6th International Conference on Neural Information Processing - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages347-352
Number of pages6
ISBN (Electronic)0780358716, 9780780358713
DOIs
StatePublished - 1999
Event6th International Conference on Neural Information Processing, ICONIP 1999 - Perth, Australia
Duration: 16 Nov 199920 Nov 1999

Publication series

NameICONIP 1999, 6th International Conference on Neural Information Processing - Proceedings
Volume1

Conference

Conference6th International Conference on Neural Information Processing, ICONIP 1999
Country/TerritoryAustralia
CityPerth
Period16/11/9920/11/99

Fingerprint

Dive into the research topics of 'Learning in a neuro-fuzzy navigator for robotic manipulators'. Together they form a unique fingerprint.

Cite this