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改进RRT算法的采摘机械臂路径规划

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针对采用传统的快速随机扩展树(RRT)算法的采摘机械臂在果园工作环境中搜索路径时间长,最终路径不平滑、拐点多等问题,提出了一种改进的RRT避障算法.改进的算法采用高斯采样策略,减少了采样的随机性,避免产生更多不必要的随机树,增加规划的导向性;再添加A*代价函数去除路径的冗余点,最后使用贪婪算法简化路径,减少拐点,让机械臂可以快速、准确、平稳地沿着最佳路径运动到目标点.仿真表明,改进后的算法有效地减少了路径规划的时间,缩短了路径长度,具有良好的可行性和有效性.
Path planning of picking manipulator with improved RRT
To address the problems that the picking robot arm employing the traditional fast random extended tree(RRT)algorithm requires a long time to search the path in the orchard working environment and the final path is not smooth with many inflection points,this paper proposes an improved RRT obstacle avoidance algorithm adopting Gaussian sampling strategy,which reduces the randomness of sampling,avoids generating more unnecessary random trees,and increases the orientation of programming.Then,A*cost function is added to remove redundant points of the path.Finally,greedy algorithm is used to simplify the path and reduce its inflection points,so that the robot arm can move along the optimal path quickly and locate the target point accurately.Our simulation results show the improved algorithm effectively reduces the time of path planning and cuts the path lengths,demonstrating its fairly good effectiveness and practicality.

manipulatorRRTGaussian samplinggreedy algorithm

赵辉、郑缙奕、岳有军、王红君

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天津理工大学电气工程与自动化学院,天津 300384

天津市复杂系统控制理论与应用重点实验室,天津 300384

机械臂 RRT 高斯采样 贪婪算法

天津市自然科学基金重点项目天津市教委重点基金项目

08JCZDJC186002006ZD32

2024

重庆理工大学学报
重庆理工大学

重庆理工大学学报

CSTPCD北大核心
影响因子:0.567
ISSN:1674-8425
年,卷(期):2024.38(1)
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