A Novel Path Planning Approach for USV Based on Optimization and Motion Modulation Obstacle Avoidance
Rui Zhu, Xiangyuan Jiang · 2024
Effective path planning and obstacle avoidance control are essential for ensuring the safe and efficient operation of Unmanned Surface Vehicle (USV) during maritime operations. This paper proposes a Particle Swarm Optimization-based Energy-Efficient Motion Modulation Obstacle Avoidance algorithm (PSOEMMOA) tailored for USV path planning. Considering the kinematic and dynamic characteristics of USV, the PSO algorithm is employed to globally optimize the navigation path, ensuring the USV can maintain optimal navigation performance during obstacle avoidance and the global optimality of the path. Additionally, a novel obstacle avoidance strategy based on motion modulation is designed. This strategy locally adjusts the navigation path of USV according to environmental information, facilitating effective obstacle avoidance. Through simulation experiments, the effectiveness of using PSOEMOOA for path planning in complex environments has been validated.