Path Planning of Unmanned Surface Vehicle Based on A* Algorithm Optimization Considering the Influence of Risk Factors

Abstract

Aiming at the safety problems of unmanned surface vehicle path planning based on A* algorithm in complex environments, a multi-path search method based on A* algorithm optimization considering the influence of risk factors is proposed to obtain the global optimal path. Firstly, extract the marine environment information in the electronic chart, and use the grid method to build the marine environment model of the path search space. Secondly, introduce obstacle interference value to optimize the search of A* algorithm to avoid unmanned surface vehicle approaching dangerous areas. Then, the steering interference value constraint is introduced to optimize the track of the searched path, so that the path track is more in line with the motion rules of the unmanned surface vehicle. Subsequently, introduce similar interference value to optimize the A* algorithm for multi-path search, so as to obtain multiple paths that balance the navigation cost and path similarity. Finally, the risk factor parameters are introduced to comprehensively evaluate the risk and navigation costs of all the paths obtained, and the final route is optimized. The experimental results show that through the optimization of the A * algorithm, the safety of the path planning of the unmanned surface vehicle is improved, and the demand for the global path planning of the unmanned surface vehicle in the complex environment is met.