USV path planning algorithm based on plant growth

Unmanned surface vehicles (USVs) have been widely used in patrol, exploration and military applications, replacing manned vessels in dangerous areas of the sea where humans cannot reach or where there is a high risk. When USVs are used for a variety of tasks in the complex and changing marine environment, autonomous navigation and obstacle avoidance are essential technologies for USVs to be equipped. In response to the current problems of slow search speed, low collision avoidance efficiency and long paths in path planning, this paper proposes a PGR (Plant Grow Route) algorithm. It is based on the principle of phototropism of plant growth, which guides USVs to avoid obstacles and reach target points through the magnitude of light intensity. Experiments show that this algorithm can successfully avoid static obstacles and allow USVs to follow the route with the strongest light intensity to reach the target point safely, and it requires short search time and high efficiency. The improved G-DWA algorithm is used to implement the PGR algorithm for local path planning, and local path planning is used as a key development direction for this experiment in the future. •This paper develops a plant growth based path planning algorithm (PGR). PGR algorithm solves the problems such as slow convergence, low efficiency and multiple inflection points of traditional path planning algorithm. The improved G-DWA algorithm is used to implement the PGR algorithm for local path planning.