Acceleration-Level Repetitive Motion Planning and Its Experimental Verification on a Six-Link Planar Robot Manipulator

摘要

To solve nonrepetitive problems, this brief proposes and investigates a novel repetitive motion planning (RMP) scheme (termed acceleration-level RMP scheme), which is resolved at the joint-acceleration level rather than at the joint-velocity level. The scheme is then reformulated as a quadratic program (QP) subject to equality and bound constraints. For the purposes of experimentation, a discrete-time QP solver is developed for the solution of the resultant QP. In addition, the global convergence of such a discrete-time QP solver is presented and analyzed. Comparisons between the nonrepetitive motion and repetitive motion planning validate the effectiveness and superiority of the proposed scheme. More importantly, the proposed scheme and the corresponding discrete-time QP solver are implemented on a six-link planar robot manipulator. The experimental results further substantiate their physical realizability, efficiency, and accuracy.