Design of Real-Time Obstacle Avoidance and Race Path Planning System for Unmanned Vehicle
Zhaohong Mai, Qingyong Zhang, Juan Li, Fuchan Chen · 2023
Nowdays the local path planning has received considerable attention and achieved good effect in known environment. However, obstacles avoidance is a huge challenges in some unstructured environments and other factors. Meanwhile, the service efficiency of unmanned vehicle is greatly limited by the path planning efficiency. To solve these problems, a real-time obstacle avoidance and racing planning system for unmanned vehicles based on multi-sensor fusion is proposed which has a good balance between the success rate of driving safety and decision-making efficiency of unmanned vehicles in unknown environments. Combining the advantages of virtual force field and velocity obstacle, an obstacle avoidance model is applied to design a PID controller with subsection control for Ackerman chassis structure, which realizes efficient obstacle avoidance and high speed driving of unmanned vehicles. Finally, a dynamic weighted A* algorithm path planner with corner penalty is proposed for path planning in this work. Simulations and experimental results show that the obstacle avoidance ability of the unmanned vehicle which maintain a high speed is improved compared with the traditional tracking algorithm. And the path planning efficiency is improved compared with the traditional A * algorithm.