Comparison of fuzzy BK-product and A* search algorithm for optimal path finding in unsupervised underwater environment
Arif Reza Anwary · 2008
Abstract—The article addresses comparison of fuzzy BK-product approach with A * search algorithm for optimal path finding of the autonomous underwater vehicles (AUVs). The technique is designed to accomplish two missions: obstacle avoidance using ARTMAP and fuzzy BK-product and comparison of 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 sensors. An on-line reinforcement learning method is introduced to adapt 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. Keywords—Fuzzy relation, BK-product, path planning, obstacle avoidance, Autonomous underwater vehicles (AUVs), A * search algorithm I.