This paper describes a heuristic search technique carrying out collision avoidance for autonomous underwater vehicles (AUVs). Fuzzy relational products are used as the mathematical implement for the analysis and synthesis of relations between obstacles that are met in the navigation environment and available candidate nodes. In this paper, we propose a more effective evaluation function that reflects the heuristic information of domain experts on obstacle clearance, and an advanced heuristic search method performing collision avoidance for AUVs. The search technique adopts fuzzy relational products to conduct path-planning of intelligent navigation system. In order to verify the performance of proposed heuristic search, it is compared with A* search method through simulation in view of the CPU time, the optimization of path and the amount of memory usage.
['Young-Il Lee', 'Yong-Gi Kim', 'Ladislav J. Kohout']
An intelligent collision avoidance system for AUVs using fuzzy relational products