Task-Specific Optimal Trajectory Planning of Dual-arm Space Robot Based on Convex Optimization

Space robotic systems are essential for on-orbit servicing missions, including satellite refueling, in-space assembly of large structures, and active debris removal. This paper presents a robust, task-specific optimal trajectory planning framework for dual-arm space robots. The method unifies two key problems—point-to-point grasping and continuous trajectory tracking—within an efficient optimization framework. For point-to-point grasping, the objective is to maximize the gradient of the distance between the predicted and target end-effector positions, yielding a time-optimal trajectory. For continuous trajectory tracking, the approach minimizes spacecraft base attitude disturbance while ensuring bounded end-effector tracking error. Additional objectives, such as manipulability and energy efficiency, are incorporated as weighted terms. Physical constraints on joint angles, velocities, accelerations, and self-collision avoidance in both planning problems are formulated as linear constraints. Task-specific constraints are also integrated: an approaching cone constraint for grasping and trajectory relaxation error bounds for tracking. Both problems are cast as convex optimization formulations, enabling efficient real-time solutions. The robustness of the method is demonstrated under challenging conditions, including high initial momentum in grasping and gravity-gradient-induced momentum in tracking. Extensive comparative simulations on a highly redundant 14-degree-of-freedom (14-DoF) dual-arm space robot validate the superior effectiveness, efficiency, and robustness of the proposed approach.