Research on collision avoidance simulation for autonomous underwater vehicles using ant colony optimization algorithm

Abstract

Autonomous Underwater Vehicles (AUVs) are increasingly crucial in exploiting and exploring marine resources. Route building and obstacle avoidance are the core technologies that help this device perform aquatic processes. Collision avoidance methods use acoustic sensors and sonar systems to help detect targets, but these devices have difficulty seeing at short distances. This article proposes a method to simulate the autonomous process of a Remotely Operated Vehicle (ROV) or AUV in a virtual environment based on several path planning and obstacle avoidance algorithms. At the same time, the author used sonar data and optimization algorithms in the route construction process to address the limitations of AUVs and ROVs and the influence of the marine environment. Finally, through Unity 3D software, simulate the underwater operation of the AUV and check the algorithm results.