Efficient Re-Planned Path for Autonomous Underwater Vehicle in Random Obstacle Scenario

摘要: Most path planning algorithms consider static environment to determine the optimal target locations. Others obstacle in runtime reorient object towards with minimum cost. Such are extensively studied for surface and there is a need similar study their application underwater sensing data gathering case. The cost parameters of deviation delay important gethering scenario addition traversal alone considered by most algorithms. This paper presents an efficient algorithm Autonomous Underwater Vehicles (AUVs) hierarchical wireless sensor network (HUWSN). proposed estimates dynamically while using local search approach image acquisition segmentation that simple implement. AUV re-plan its respect shortest reference path, deviating re-alligning itself efficiently dynamic conditions comprising obstacles small drifts.