VFH+ Based Local Path Planning for Unmanned Surface Vehicles

Abstract

In the field of marine engineering, the path planning problem of unmanned surface vehicles (USVs) is particularly important, especially in complex marine environments. Path planning for USVs is the process of regulating them to find an optimal or sub-optimal path from the starting point to the target point. It should guarantee that USVs can avoid obstacles based on one or more performance indicators (such as the lowest working cost, the shortest navigation route, the shortest navigation time, etc.). Path planning methods can be divided into two types: global and local ones. Generally, USVs with only global path planning ability cannot adapt to real-time changing marine environments, while local path planning is more effective for real-time path planning. By introducing an improved VFH+method, this paper proposes a local path planning framework for a USV equipped with a laser radar. It improves the USV’s dynamic obstacle avoidance ability from two aspects: (i) Polar obstacle densities are adopted to identify dynamic obstacles quickly; (ii) By considering velocity vectors of the USV and dynamic obstacles, candidate directions are optimized. The effectiveness of the proposed method is verified through an experiment. The experimental results demonstrate that the proposed method can guarantee safe autonomous navigation of a USV in unknown static and dynamic marine environments.