Dynamic Obstacle Avoidance Method of USV Based on Secure ACO with Hazard Index

Aiming at the problem that basic ants colony optimization (ACO) could not meet the requirements of safe obstacle avoidance for unmanned surface vessels (USV) in dynamic environment, a path planning method combining improved ACO and dynamic windows approach (DWA) was proposed. The improved heuristic information was proposed to solve the problem of low efficiency of basic ACO path search. In order to prevent the potential collision between USV and obstacles during navigation, a hazard index considering the inertia of USV and obstacle distance is designed to improve the probability of ACO. And the fusion of secure ACO and DWA improve the local safety obstacle avoidance ability of USV in dynamic environment. The experimental results show that the improved ACO can effectively improve the searching ability of the global path and ensure the safety of the planned path. The fusion algorithm can realize smooth dynamic obstacle avoidance based on the advantages of global path.