Research on an Obstacle Avoidance System for Unmanned Vessels Based on Millimeter-Wave Radar

To address the common shortcomings of traditional artificial potential field methods in complex water environments, this paper proposes an improved artificial potential field obstacle avoidance method based on a scoring weighting mechanism. It also designs a real-time obstacle avoidance system for unmanned surface vehicles (USVs) primarily utilizing millimeter-wave radar as the sensing modality. This method utilizes obstacle information from millimeter-wave radar, introducing a scoring mechanism that comprehensively considers distance, azimuth, and motion state to dynamically adjust repulsive weighting within the artificial potential field. This enables adaptive obstacle avoidance decision-making in complex multi-obstacle scenarios. Compared to traditional artificial potential field methods, the proposed approach effectively mitigates local minima and unreachable target issues while enhancing obstacle avoidance path stability and safety without compromising real-time performance. Simulation analysis and real-vessel experiments validate the method’s strong feasibility and engineering applicability in complex environments.