A probability adaptive random sampling algorithm based on RRT for collision-free motion planning | |
Mi, Kai1,2![]() ![]() ![]() | |
2019-07 | |
会议名称 | Chinese Control Conference |
会议日期 | 2019.7.27-2019.7.30 |
会议地点 | 中国广东省广州市 |
摘要 | In recent years, with the increasingly complex robot application environments, the research of robotic autonomous obstacle avoidance motion planning is one of the key technologies to improve its intelligence. In this paper, we present an improved algorithm based on Rapidly-exploring Random Tree (RRT) algorithm, which is called Probability Adaptive RRT (PARRT). We analyze the defects of the original algorithm in detail from the perspective of Voronoi diagram. For some complicated occasions, especially when the robot is surrounded by obstacles, the efficiency of the original algorithm will be greatly reduced. For this problem, we proposed an expansion probability adaptive method. By dynamically adjusting the extending probability of nodes near obstacles, the invalid node expansion is reduced effectively and the planning speed is greatly improved. Finally, we experiment in both two-dimensional space and the joint space of manipulators. The planning results show the improved effect of the proposed algorithm. |
收录类别 | EI |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/39197 |
专题 | 智能制造技术与系统研究中心_智能机器人 |
通讯作者 | Zheng, Jun |
作者单位 | 1.中国科学院自动化研究所 2.中国科学院大学 |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Mi, Kai,Zheng, Jun,Wang, Yunkuan. A probability adaptive random sampling algorithm based on RRT for collision-free motion planning[C],2019. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
A probability adapti(302KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论