Research on path planning of unmanned vehicle with an improved RRT algorithm
Gaoyang Xie, Liqing Fang, Xujun Su, Deqing Guo, Ziyuan Qi, Yanan Li, Jinli Che · 2024
To address the path planning challenges for unmanned vehicles at varying speeds, this study improves the traditional RRT algorithm, resulting in a path planning approach adaptable to different speed conditions. First, the maximum steering angle corresponding to each vehicle speed is calculated based on the autonomous vehicle's kinematic model. Next, a limit on the maximum steering angle is applied during the adjacent node selection step in the random tree. This ensures that the path generated by the enhanced RRT algorithm meets the maximum steering angle requirements. The algorithm is then simulated in MATLAB, with results demonstrating that the improved RRT algorithm effectively completes route planning for unmanned vehicles at different speeds (30 km/h, 45 km/h, and 60 km/h). This study thus offers a novel solution to the route planning problem for unmanned vehicles across varying speeds.