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.