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.

从多个逆运动学解决方案（IKS）中选择最佳解决方案是机械臂运动的一项基本任务。然而，传统的最小关节运动准则（MJM）方法存在计算时间长、无法保证配置不变性等缺点。随着非尖角结构在商业机械臂中的流行，迫切需要一种新颖的 IKS 选择方法。该文通过IKS形式的几何表示分析了MJM方法的局限性，提出了一种基于配置空间分解的IKS选择方法。非尖角操纵器的配置空间被划分为称为唯一性域（UD）的独立子域。随后，建立了配置、UD和IKS之间的双射来选择IKS，并证明了三个重要的相关定理。所提出的方法计算成本低，并且允许连续轨迹跟踪或点对点规划中的配置不变性。最后，物理实验结果证明了该方法的有效性。