Optimization-Based Motion Planning Method for a Robot Manipulator Under the Conditions of Confined Space and Heavy Load

Tianyu Zhang, Hongguang Wang, Peng Lv, Fanxu Kong, Daqian Wang, Xinan Pan

Abstract: The current aircraft refueling method relies heavily on manual labor, resulting in high labor intensity, a cumbersome refueling process, and low efficiency. Therefore, extensive research is crucial to explore the use of robot manipulators for autonomous refueling. However, implementing robot arms encounters challenges such as confined workspace and the heavy weight of fueling tools. This paper proposes a motion planning method for a robot manipulator operating within confined areas to address these issues. The method considers obstacle avoidance constraints, dynamic joint torque allocation, and physical limitations. To characterize the dynamic transmission performance between joint torque output and end force while considering joint torque limitations, we introduce the Inertia Matching Index (IMI). The IMI and minimum joint angles serve as cost functions in our approach. Given the confined environments and various types of refueling equipment, we incorporate collision distance as a constraint to avoid collisions between the robot arm and other objects. To ensure effective resolution, we reformulate these non-convex objectives and constraints to solve them using the ADMM algorithm. The experimental results demonstrate the effectiveness of our proposed motion planning method in improving IMI while ensuring safe trajectories and optimal joint torque allocation. This study has significant theoretical and practical value for autonomous robot operations and autonomous aerial refueling applications in confined spaces.