E-RRT*: Path Planning for Hyper-Redundant Manipulators

IF 5.3 2区计算机科学 Q2 ROBOTICS

IEEE Robotics and Automation Letters Pub Date : 2023-10-18 DOI:10.1109/LRA.2023.3325716

Hongcheng Ji;Haibo Xie;Cheng Wang;Huayong Yang

引用次数: 0

Abstract

A hyper-redundant manipulator(HRM) can flexibly accomplish tasks in narrow spaces. However, its excessive degrees of freedom pose challenges for path planning. In this letter, an ellipsoid-shape rapidly-exporing random tree (E-RRT*) method is proposed for path planning of HRMs in workspace, particularly those with angle limits. This method replaces line segments with ellipsoids to connect adjacent nodes. Firstly, an analysis of angle constraints of the HRM is conducted, providing restrictions on node selection during path planning. Secondly, a slow-speed informed guiding approach is introduced to optimize the sampling process. Finally, the obtained path is enhanced by adding control points and applying cubic polynomial interpolation to achieve path smoothing. Simulations demonstrate that the proposed E-RRT* method effectively solves the path planning problem for HRMs. Especially in narrow environments, appropriate informed guiding speeds enable E-RRT* to outperform other methods.

查看原文本刊更多论文

E-RRT*:超冗余机械手的路径规划

超冗余机械手可以在狭窄的空间内灵活地完成任务。然而，其过大的自由度给路径规划带来了挑战。本文提出了一种椭球形快速扩展随机树(E-RRT*)方法，用于hrm在工作空间中的路径规划，特别是有角度限制的路径规划。该方法用椭球体代替线段连接相邻节点。首先，对人力资源管理的角度约束进行了分析，给出了路径规划时节点选择的约束条件。其次，引入慢速信息引导方法对采样过程进行优化。最后，通过添加控制点和三次多项式插值对得到的路径进行增强，实现路径平滑。仿真结果表明，所提出的E-RRT*方法有效地解决了hrm的路径规划问题。特别是在狭窄的环境中，适当的导向速度使E-RRT*优于其他方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

IEEE Robotics and Automation Letters Computer Science-Computer Science Applications

CiteScore

9.60

自引率

15.40%

发文量

1428

期刊介绍： The scope of this journal is to publish peer-reviewed articles that provide a timely and concise account of innovative research ideas and application results, reporting significant theoretical findings and application case studies in areas of robotics and automation.