A novel method for computing self-motion manifolds. (January 2023)

• Record Type: Journal Article
• Authors: Wu, Tong; Zhao, Jing; Xie, Biyun
• Is Part Of: Mechanism and machine theory. Volume 179(2023)
• Publication Date: 2023-01
• Subjects: Redundant robots -- Kinematics -- Motion and path planning -- Self-motion manifolds; Machine theory -- Periodicals; Machinery -- Periodicals; Machines -- Périodiques; Génie mécanique -- Périodiques; Machine theory; Machinery; Periodicals; 621.81
• DOI: 10.1016/j.mechmachtheory.2022.105121
• Languages: English
• ISSNs: 0094-114X

Abstract

Abstract: For kinematically redundant robots, self-motion manifolds that represent all the inverse kinematic solutions for a given end-effector location play a significant role in global motion planning. However, the efficient computation of self-motion manifolds, especially the computation of high-dimensional manifolds, is still a problem that needs to be solved. In this paper, the grid elements modeling criteria are formulated, and the specific modeling method of a grid element in the configuration space is developed. Based on the idea of cellular automata, the problem of computing self-motion manifolds is transformed into a dynamic model searching problem, and an evolution strategy is proposed to realize the efficient computation of self-motion manifolds. Finally, two examples are used to verify the effectiveness of the proposed method in computing high-dimensional self-motion manifolds. The results show that compared to the conventional methods, the proposed method can correctly identify all the self-motion manifolds with 94% reduced computational time on average. Highlights: Grid model is well used for expressing self-motion manifolds with high-dimensional. An efficient manifold computation strategy based on cellular automata is proposed. An intersection criterion and fast intersection estimation method are proposed. A heuristic method for the initial elements determined is proposed.