A Novel Navigation Method for Autonomous Mobile Vehicles

This paper presents a novel navigation method for Autonomous Mobile Vehicle in unknown environments. The proposed navigator consists of an Obstacle Avoider (OA), a Goal Seeker (GS), a Navigation Supervisor (NS) and an Environment Evaluator (EE). The fuzzy actions inferred by the OA and the GS are weighted by the NS using the local and global environmental information and fused through fuzzy set operation to produce a command action, from which the final crisp action is determined by defuzzification. The EE tunes the supports of the fuzzy sets for the OA and the NS; therefore, the capability of the navigation method is enhanced. Simulation shows that the navigator is able to perform successful navigation task in various unknown or partially known environments, and it has satisfactory ability in tackling moving obstacles. More importantly, it has smooth action and exceptionally good robustness to sensor noise.