Aquatic environment establishment and USV path planning simulation analysis using the ROS framework

Abstract

Comprehensive, accurate, and timely cognition of navigation situation is a prerequisite to make safe, efficient, and scientific decisions for Unmanned Surface Vehicles (USVs). The autonomous path planning problem for USVs operating in complex aquatic environments was addressed. A hybrid path planning algorithm integrating A* and Dynamic Window Approach (DWA) is proposed, and its performance under diverse environmental conditions is systematically validated through simulation experiments. A virtual aquatic environment was constructed to conduct path planning simulations under three distinct scenarios: still water without wind, constant wind conditions, and variable wind speeds, thereby comprehensively evaluating the algorithm's adaptability, safety, and optimization capability. The results demonstrate that within a certain wind speed range, the optimization capability of the hybrid path planning algorithm significantly strengthens as the experimental aquatic environment scales up, leading to further enhancement of USV navigation safety. Under constant wind disturbance of 5 m/s, the USV successfully navigates to the target point while maintaining a safety distance exceeding 0.5 m from obstacles throughout the voyage, exhibiting robust anti-interference capability and planning stability. Quantitative analysis of simulation results under varying wind conditions was performed using an evaluation function. By optimizing this evaluation function based on an improved DWA motion model, the navigation path length is reduced by 4.12% and navigation time decreases by 7.66%, while simultaneously increasing the safe clearance between the USV and obstacles. These improvements substantially enhance both path optimality and navigation safety of the USVs.