Kinodynamic Trajectory Optimization of Dual-Arm Space Robot for Stabilizing a Tumbling Target

Abstract

Capturing and stabilizing tumbling targets using dual-arm space robots are very crucial to on-orbit servicing task. However, it is still very challenging due to the complex dynamics coupling and closed-chain constraints between the manipulators, the base, and the target. In this paper, a kinodynamic trajectory optimization method is proposed to generate the motion of a dual-arm space robot for stabilizing the captured tumbling target, which is formulated and solved as a nonlinear programming problem using direct collocation. Instead of optimizing the trajectory of each joint with the dynamics model of space robot, this method optimizes the trajectory of the tumbling target while considering the kinematics and dynamics constraints between the two arms and the target simultaneously. The objective function of the optimization is defined as weighted detumbling time, base disturbance, and manipulability, in order to avoid singularity and save the energy of space robot for further manipulation. Several physical simulations are carried out to validate the proposed method.

Optimum joint and trajectory tracking control of multi-axes space manipulator based on amnesia feedback controller

“…A computational approach for a generalized Jacobian matrix of multi-arm free-floating manipulators was established by Xie et al 31 Yan et al 32 developed a control scheme for a free-flying dual-arm space robot employing position and force control with zero internal force. The benefit of zero internal force control is that it reduces the amount of fuel used during operation.…”

Omnidirectional Continuous Movement Method of Dual-Arm Robot in a Space Station

“…Dual-arm space robots must not only avoid collisions with the complex environment but also achieve self-obstacle avoidance [36][37][38]. Moreover, numerous researchers concentrate on the dynamic characteristics of dual-arm space robots, enabling them to simultaneously meet kinematic and dynamic constraints [39][40][41]. Through the aforementioned motion planning methods, robots can complete complex space tasks, such as assembly [23] and target acquisition [42,43].…”