A Novel Method for Selecting Inverse Kinematic Solutions Based on Configuration Space Partition for 6R Noncuspidal Manipulators

被引:1
|
作者
Zhang, Xiaofeng [1 ,2 ]
Li, Gongfa [1 ,2 ,3 ]
Xu, Manman [1 ,2 ,3 ]
Jiang, Du [1 ,2 ,3 ]
Yun, Juntong [1 ,2 ]
机构
[1] Wuhan Univ Sci & Technol, Key Lab Met Equipment & Control Technol, Minist Educ, Wuhan 430081, Peoples R China
[2] Wuhan Univ Sci & Technol, Res Ctr Biomimet Robot & Intelligent Measurement &, Wuhan 430081, Peoples R China
[3] Wuhan Univ Sci & Technol, Hubei Key Lab Mech Transmiss & Mfg Engn, Wuhan 430081, Peoples R China
基金
中国国家自然科学基金;
关键词
Noncuspidal robot; Inverse kinematics; Uniqueness domain; Singularity; Configuration space analysis; OPTIMIZATION;
D O I
10.1007/s10846-023-02029-4
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The selection of an optimal solution from multiple inverse kinematics solutions (IKSs) is a fundamental task in manipulator motion. However, the conventional minimum joint motion criterion (MJM) method suffers from drawbacks such as high computational time and the inability to ensure configuration invariance. With the prevalence of noncuspidal structures in commercial manipulators, a novel IKS selection methodology is exigent. This paper analyzes the limitations of the MJM method by geometric representations of the IKS formal and proposes a novel IKS selection method based on configuration space decomposition. The configuration space of noncuspidal manipulators is partitioned into independent subdomains called uniqueness domains (UD). Subsequently, a bijection between configuration, UD, and IKS is established for selecting IKS, and three important related theorems are proven. The proposed method offers low computational cost, and allows configuration invariance in continuous trajectory tracking or point-to-point planning. Finally, the physical experiment results demonstrate the effectiveness of the proposed method.
引用
收藏
页数:20
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