融合改进RRT和TEB算法的移动焊接机器人路径规划

Path Planning of Mobile Welding Robot Based on Fusion Algorithms of Improved RRT and TEB

针对移动焊接机器人路径规划中快速遍历随机树(RRT)算法搜索时间较长、易生成曲折且避障性能差的路径,以及时间弹性带(TEB)算法存在速度输出跳变等不足,提出1种改进RRT和TEB的移动焊接机器人路径规划融合算法。引入目的性扩展和关键点提取策略改进RRT算法,提高算法的搜索效率和规划路径的平滑性;引入最小安全距离对速度的约束改进TEB算法,使移动焊接机器人能够有效避开障碍物,同时增加目标点对速度的约束,减少对移动焊接机器人的冲击;融合改进RRT和TEB算法,使移动焊接机器人能够动态规划路径,避免动态障碍物的干扰,且对其进行仿真和实物验证。结果表明:改进RRT算法的路径搜索时间减少了58.84%,路径拐点数减少了73.33%;融合改进的RRT与TEB算法用于移动焊接机器人的路径规划,机器人与障碍物之间的安全距离增加了50%,在到达目标点前可提供足够的速度缓冲时间,极大提高了机器人运行的稳定性和避障能力。

To address the issues of the rapidly-exploring random tree(RRT)algorithm,such as long search times,generation of zigzag paths,and poor obstacle avoidance,as well as the drawbacks of the time-elastic band(TEB)algorithm,such as speed output jumps,a hybrid path planning algorithm for mobile welding robots that improved both RRT and TEB was proposed.A purposeful extension and key point extraction strategies were introduced to improve the RRT algorithm,and to enhance the search efficiency and smoothness of path planning.Furthermore,a minimum safety distance was introduced to improve the TEB algorithm,which enabled the mobile welding robot to effectively avoid obstacles,while increasing the constraint of target points on speed and reducing the impact on the mobile welding robot.By integrating the improved RRT and TEB algorithms,the welding robots could dynamically plan its path,and avoiding interference from dynamic obstacles.Simulations and physical validations of this approach were conducted.The results demonstrate that the path search time with the improved RRT algorithm is reduced by 58.84%,and the number of path inflection points is reduced by 73.33%.The fusion of improved RRT and TEB algorithms can increase the safe distance between the mobile welding robot and obstacles by 50%.It also provides sufficient speed buffer time before reaching the target point,which greatly enhances the stability and obstacle avoidance ability of the mobile welding robot.