基于势场法的无人车局部动态避障路径规划算法

根据无人车动态实时避障的需求，提出一种基于人工势场法的局部避障路径规划算法，通过改进势场环境及势场力来解决传统势场法局部极小值和目标不可达的问题. 考虑车辆碰撞安全性，对侧向动态障碍物和同向动态障碍物工况进行分析，采用动态窗口法进行实时动态避障规划. 同时为保证规划路径的平滑性和可跟踪性，采用贝塞尔曲线对轨迹进行平滑处理. 最后,在CarSim和Matlab/Simulink 联合仿真平台下，对所提出的控制算法进行验证. 仿真结果表明了规划算法的避障有效性、安全性以及可跟踪性. 

Local Dynamic Obstacle Avoidance Path Planning Algorithm for Unmanned Vehicles Based on Potential Field Method

To achieve dynamic real-time obstacle avoidance of unmanned vehicles, a local obstacle avoidance path planning algorithm was proposed based on artificial potential field method. Firstly, improving the potential field environment and the potential field force were arranged in the new method to solve the local minimum value and target unreachable problem of the traditional potential field method. And then, considering the safety of vehicle collisions, the working conditions of lateral dynamic obstacles and the same direction dynamic obstacles were analyzed, and a dynamic window method was used for real-time dynamic obstacle avoidance planning. To ensure path flatness and traceability, a BSL curve was used to smoothing the planned path. Finally, the proposed control algorithm was verified under the co-simulation platform of CarSim and Matlab/Simulink. The simulation results show the effectiveness, safety and traceability of the planning algorithm for obstacle avoidance.