Time optimal multi-base placement planning for mobile measuring manipulator considering reachable and non-singular constraints

Mobile measuring manipulators have bright prospects in the field of in-situ measurement of large thin-walled components, but research on their planning and control strategies is still in the early stages. Completing scanning tasks for large thin-walled components requires multi-base placement, and the optimization of their placements and quantity is of significant importance for improving the efficiency and quality of the scanning task. To address this issue, this paper proposes a multi-base placement planning framework that satisfies the full coverage requirement with the minimum required placements. This planning framework consists of four steps. Firstly, it generates scanning viewpoints based on the theoretical model of the workpiece. Then, it draws a singularity-avoiding reachability map based on the manipulator parameters. Furthermore, it presents an algorithm for verifying manipulator reachability without computing the inverse kinematics to improve computational efficiency. Finally, it introduces a coverage-adaptive multi-base placement planning algorithm that aims to minimize the total number of placements and the shortest path for the mobile platform's motion, achieving the shortest scanning time for multi-base placement. Experimental validation is conducted to demonstrate the feasibility and superiority of the multi-base placement planning framework.