动态风险场引导RRT*算法的无人车辆路径规划研究OA

To address the issues of low efficiency and ineffective mobile obstacle avoidance of the RRT* algorithm in dynamic environments,an adaptive dynamic risk-propagating RRT star(ADRP-RRT*)algorithm is proposed.This algo-rithm constructs a risk field to quantify the threat of dynamic obstacles,utilizes a risk field guided dynamic artificial poten-tial field to rapidly generate an initial path,and constrains the search within a dynamic elliptical sampling area built upon the initial path.Within this area,iterative optimization is performed by combining a risk aware RRT* optimization mecha-nism with a dynamic step-size strategy.Simulation results indicate that,compared with algorithms such as RRT* and APF-IRRT*,the proposed algorithm significantly improves convergence speed and operational efficiency while ensuring path safety and optimality,and is capable of effectively planning safe paths that avoid dynamic obstacles.