A Novel Bio-Inspired Path Planning for Autonomous Underwater Vehicle for Search and Tracing of Underwater Target

Underwater search and tracing is a complex engineering problem, due to various factors, such as unpredicted oceanic environment, poor communications, underwater navigations. Therefore, to accomplish a challenging mission an autonomous underwater vehicle (AUV) cooperation is needed. This study focuses on the search and tracing of an underwater target, based on an improved cooperative path planning model. To achieve the possible results, the mission is divided into search and tracing phases aiming to maximize the search space thus reducing terminal error respectively. The developed method is inspired by bio-inspired Improved Whale optimization Algorithm (IWOA) based method, hence modeling improved path for autonomous underwater vehicle followed by simulations of various parameters for experimentation, such as maneuverability and communication ranges between autonomous vehicles, in a distributed or centralized scenarios. For the above process, the IWOA is compared with the improved particle swarm optimization (IPSO) algorithm for different parameters for the search and tracing of the underwater target. The simulated results exhibit that the proposed method presents superior results for the search and tracing phase, which also increases the computational performance together with well-achieved optimization on large-scale complex problems for cooperative path planning.