Path Planning Method for Unmanned Surface Vehicle Under High Temporal and Spatial Dynamic Characteristics of Marine Environment

To address the problem of collision avoidance for Unmanned Surface Vehicles (USVs) in highly dynamic spatiotemporal marine environments, this paper proposes a USV path planning method that integrates the Velocity Obstacle (VO) approach with an improved Multi-Objective Particle Swarm Optimization (MOPSO) algorithm. The method creates a velocity obstacle area by combining environmental disturbances, USV dynamics, encounter scenarios, and the International Regulations for Preventing Collisions at Sea (COLREGS), resulting in a set of feasible avoidance strategies. Based on this, a multi-objective path planning model is developed with the dual optimization goals of minimizing energy consumption and collision risk. To address the limitations of traditional MOPSO, such as poor adaptability and susceptibility to local optima, this paper introduces improvements to particle encoding, update strategy, and external archive mechanism to improve convergence and solution diversity. Simulation results demonstrate that the proposed method can provide safe and energy-efficient autonomous collision avoidance paths for USVs in complex dynamic marine environments, demonstrating its practicality and intelligence.