Recent algorithms for fuzzy and neurofuzzy path planning and navigation of autonomous mobile robots

Tzafestas, CS; Tzafestas, SG

dc.contributor.author	Tzafestas, CS	en
dc.contributor.author	Tzafestas, SG	en
dc.date.accessioned	2014-03-01T11:45:42Z
dc.date.available	2014-03-01T11:45:42Z
dc.date.issued	1999	en
dc.identifier.issn	01371223	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/37574
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-0039185603&partnerID=40&md5=66814b61455920f72a39fb34ba4e8e7f	en
dc.title	Recent algorithms for fuzzy and neurofuzzy path planning and navigation of autonomous mobile robots	en
heal.type	other	en
heal.publicationDate	1999	en
heal.abstract	This paper reviews a number of recent algorithms for mobile robot path planning, navigation and motion control, which employ fuzzy logic and neurofuzzy learning and reasoning. Starting with a discussion of the structure of fuzzy and neurofuzzy systems, two fuzzy obstacle avoidance path planning algorithms are presented followed by a 3-level neurofuzzy local and global path planning scheme. Then the motion planning and control problem is considered. A fuzzy path tracking strategy is outlined, followed by a fuzzy navigation algorithm among polygonal obstacles and a learning-by-doing neurofuzzy motion planning scheme. The paper ends with a hybrid robust motion control technique which combines the minimum interference and sliding mode control principles with fuzzy inference. A representative set of examples are included which illustrate the performance of the algorithms under various realistic conditions.	en
heal.journalName	Systems Science	en
dc.identifier.volume	25	en
dc.identifier.issue	2	en
dc.identifier.spage	25	en
dc.identifier.epage	39	en