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TSMC
1998

A neuro-fuzzy controller for mobile robot navigation and multirobot convoying

9 years 10 months ago
A neuro-fuzzy controller for mobile robot navigation and multirobot convoying
—A Neural integrated Fuzzy conTroller (NiF-T) which integrates the fuzzy logic representation of human knowledge with the learning capability of neural networks is developed for nonlinear dynamic control problems. NiF-T architecture comprises of three distinct parts: 1) Fuzzy logic Membership Functions (FMF), 2) a Rule Neural Network (RNN), and 3) an Output-Refinement Neural Network (ORNN). FMF are utilized to fuzzify sensory inputs. RNN interpolates the fuzzy rule set; after defuzzification, the output is used to train ORNN. The weights of the ORNN can be adjusted on-line to fine-tune the controller. In this paper, real-time implementations of autonomous mobile robot navigation and multirobot convoying behavior utilizing the NiF-T are presented. Only five rules were used to train the wall following behavior, while nine were used for the hall centering. Also, a robot convoying behavior was realized with only nine rules. For all of the described behaviors—wall following, hall ce...
Kim C. Ng, Mohan M. Trivedi
Added 23 Dec 2010
Updated 23 Dec 2010
Type Journal
Year 1998
Where TSMC
Authors Kim C. Ng, Mohan M. Trivedi
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