摘要
以自动驾驶清扫车为实际应用背景,提出了一种改进的RRT*路径规划算法。该路径规划算法引入了车辆形状约束,并且采用目标偏向的采样策略,提高安全性的同时也保证了算法的实时性。另外对路径加入了最大曲率约束,并采用B样条曲线对路径进行平滑处理,使规划出的路径能够满足车辆运动学和动力学的约束。仿真和实车试验结果表明,该算法能够满足自动驾驶清扫车的实际应用。
Aiming at the application of the autonomous driving sweeper, an improved rapidly-exploring random tree star （RRT） path planning algorithm is proposed. The algorithm combines the constraints of the shape of the vehicle and the goal-biased sampling strategy, which not only improves the security but also guarantees the real time of the algorithm. In addition, a post-processing method based on the maximum curvature constraint and B-spline basic function is presented to guarantee the kinematic and dynamic constraints of the vehicle. Simulation experiments and real intelligent vehicle test verify the algorithm meet the need of the application of the sweeper.
出处
《机电一体化》
2017年第10期15-23,共9页
Mechatronics
基金
上海市科学技术委员会项目"基于北斗导航的低速智能汽车关键技术研究"
研究项目编号为14DZ1104700
