Comparison of fuzzy BK-product and A* search algorithm for optimal path finding in unsupervised underwater environment

摘要

The article addresses comparison of fuzzy BK-product approach with A* search algorithm for optimal path finding for the autonomous underwater vehicles (AUVs). The technique is designed to accomplishing two missions: obstacle avoidance using ARTMAP and fuzzy BK-product and comparison optimal path finding with A* search algorithm. In the first mission, underwater obstacle avoidance technique has already implemented [1]. This paper mainly focuses on optimal path finding using fuzzy BK-product and A* search algorithm. AUV gets information about the surroundings through active sonar. An on-line reinforcement learning method is introduced which adapts the performance of the fuzzy units continuously to any changes in the environment and make decision for the optimal path from source to destination. Fuzzy BK product approach and hardware-in-the-loop simulations have been developed to verify the effectiveness of the proposed technique.