基于时间弹性带的移动机器人路径优化方法

传统的路径规划并未明确地纳入运动的时间和动力学方面,因此忽略了运动或动态运动模型在有限的速度和加速度下施加的约束。针对这种情况,将时间弹性带算法引入局部路径优化,有效地优化了机器人轨迹的动力学约束,同时明确纳入时间信息以确保在最短时间内到达目标点,确保了移动机器人导航的快速性。将基于噪声的密度聚类算法(DBSCAN)引入地图转换,将局部代价地图层的点障碍物聚类为凸多边形,使得障碍物约束部分计算量大大减少,总体上减少了机器人导航所需时间,提升了导航的快速性。在仿真环境和真实场景下的实验都验证了上述改进的有效性。

Path optimization method for mobile robot based on timed elastic band

The temproal and dynamic aspects of motion are not explicitly included in traditional path planning, so the constraints imposed by motion or dynamic motion models under limited speed and acceleration are ignored. In response to this situation, the timed elastic band algorithm is introduced into local path optimization. The dynamic constraints of the robot trajectory are effectively optimized by this algorithm, and at the same time time information is incorporated explicitly to ensure that the target point is reached in the shortest time and the rapidity of mobile robot navigation. The Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is introduced into the map conversion, and the point obstacles in the local costmap layer are clustered into convex polygons. The calculation of the obstacle constraint part is greatly reduced by the map conversion. In general, the time required for navigation is reduced and the speed of path planning is improved. The effectiveness of the above improvements is verified by experiments in a simulation environment and real scenarios.