A Novel Navigation Method for Autonomous Mobile Vehicles
Journal of Intelligent and Robotic Systems
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
Probabilistic fuzzy logic system: a tool to process stochastic and imprecise information
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
A probabilistic fuzzy logic system: learning in the stochastic environment with incomplete dynamics
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Autonomous robot path planning based on swarm intelligence and stream functions
ICES'07 Proceedings of the 7th international conference on Evolvable systems: from biology to hardware
Real-Time global optimal path planning of mobile robots based on modified ant system algorithm
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part II
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In this paper, an alternative training approach to the EEM-based training method is presented and a fuzzy reactive navigation architecture is described. The new training method is 270 times faster in learning speed; and is only 4% of the learning cost of the EEM method. It also has very reliable convergence of learning; very high number of learned rules (98.8%); and high adaptability. Using the rule base learned from the new method, the proposed fuzzy reactive navigator fuses the obstacle avoidance behaviour and goal seeking behaviour to determine its control actions, where adaptability is achieved with the aid of an environment evaluator. A comparison of this navigator using the rule bases obtained from the new training method and the EEM method, shows that the new navigator guarantees a solution and its solution is more acceptable