Design and Analysis of New Obstacle Avoidance Scheme With Dimensionality Reduction for Motion Planning of Redundant Robot Manipulators

IF 5.2 2区 计算机科学 Q2 ROBOTICS
Dongsheng Guo, Qu Li, Naimeng Cang, Yilin Yu, Weidong Zhang, Weibing Li
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Abstract

Obstacle avoidance (OA) is an important issue in the motion planning of redundant robot manipulators. Various effective OA schemes have been reported, but they may suffer from a large amount of calculation for the situation of multiple obstacles and/or complex-shaped obstacles. In this paper, to address the aforementioned limitation, a new OA scheme with dimensionality reduction is proposed and studied for redundant robot manipulators. Specifically, by combining robot kinematics and geometry, a typical inequality criterion for OA is designed, which can reduce the calculation for an obstacle point from the general three dimensions to one dimension. Such an inequality criterion is further aided by (1) the dynamic selection for the situation of a large number of obstacle points, and (2) the feature extraction for the situation of complex-shaped obstacles. With the OA environment optimized and the obstacles' dimension limited, the computational efficiency of generating the inequality criterion for specific scenarios can thus be improved. By incorporating the inequality criterion and the joint physical constraint, the new dimensionality-reduction OA (DROA) scheme is developed for redundant robot manipulators. Such a DROA scheme is depicted as a quadratic program that is solved by the reinforcement learning method. Simulation and experiment results under the PA10 robot manipulator verify the efficacy and applicability of the proposed DROA scheme.

Abstract Image

冗余机械手运动规划的降维避障新方案设计与分析
避障是冗余机械手运动规划中的一个重要问题。各种有效的OA方案已经被报道,但是对于多障碍物和/或复杂形状障碍物的情况,它们可能存在计算量大的问题。针对上述局限性,本文提出并研究了一种针对冗余机械手的降维OA方案。具体而言,结合机器人运动学和几何学,设计了一种典型的OA不等式准则,将障碍物点的计算从一般的三维简化为一维。该不等式准则还需要(1)障碍物点多的情况下的动态选择,(2)形状复杂的障碍物情况下的特征提取。通过优化OA环境,限制障碍物的尺寸,可以提高生成特定场景不平等准则的计算效率。将不等式准则与关节物理约束相结合,提出了一种新的冗余度机械手降维OA (DROA)方案。这种DROA方案被描述为一个用强化学习方法求解的二次规划。在PA10机器人操作臂下的仿真和实验结果验证了所提DROA方案的有效性和适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Field Robotics
Journal of Field Robotics 工程技术-机器人学
CiteScore
15.00
自引率
3.60%
发文量
80
审稿时长
6 months
期刊介绍: The Journal of Field Robotics seeks to promote scholarly publications dealing with the fundamentals of robotics in unstructured and dynamic environments. The Journal focuses on experimental robotics and encourages publication of work that has both theoretical and practical significance.
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