Acceleration-Level Multi-Criteria Optimization for Remedying Joint-Angle Drift of Redundant Manipulators on Complex Path Tracking

• Main Authors: Zhaoli Jia, Xilong Qu, Siyuan Chen, Nan Zhong, Pengchao Zhang, Fan Ouyang
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Access
• Subjects: Multi-criteria optimization motion planning; joint-angle drift; acceleration-level; redundant manipulators; physical constraints; physical experiment
• Online Access: https://ieeexplore.ieee.org/document/8754767/

In this paper, to remedy the joint-angle drift problem of redundant manipulators at the acceleration level, a multi-criteria optimization motion planning (MCOMP) scheme is proposed and investigated for redundant manipulators. In addition, the proposed scheme considers physical constraints and guarantees values of the joint-velocity and joint-acceleration to approach zero at the end of the path-tracking task. The proposed scheme is reformed into one standard quadratic program problem, which is then solved by the simplified linear variational inequalities-based primal-dual neural network (S-LVI-PDNN). Furthermore, three tracking path computer simulations (i.e., “Nut line” pattern, “Peach” pattern, and Chinese character “tu” pattern) are illustrated, which verify the validity and advantage of the proposed scheme. Finally, the physical experiment based on the JACO² manipulator further verifies the practicability of the proposed scheme for solving the joint-angle drift of redundant manipulators.