Dual-arm coordinated capturing of an unknown tumbling target based on efficient parameters estimation

A malfunctioned satellite or other space debris is generally non-cooperative and tumbling, bringing great challenge to capture and remove it. In this paper, we propose a dual-arm coordinated capturing method based on efficient parameters estimation. Firstly, the dynamics model of a tumbling target is deduced in details. Its motion characteristics are then analyzed. Secondly, we design an efficient Hybrid Kalman Filter (HKF) by combining Extended Kalman Filter (EKF) with Unscented Kalman Filter (UKF). It effectively overcomes the shortcoming of low accuracy of EKF and long iteration time of UKF, and improves the speed and accuracy of the Kalman Filter iteration algorithm. Two movement cases of an uncontrolled target are considered: one is rotation around the principal axes of inertia; the other is rotation around arbitrary axes. Thirdly, the estimated motion and inertia parameters are used to plan the trajectories of a dual-arm space robot to capture the tumbling target. Finally, the simulation environment is created and the proposed method is verified. The simulation results show that the proposed HKF algorithm can estimate the attitude quatemion, angular velocity, and the inertia tensor (including I-xx, I-yy, I-zz, I-xy, I-xz, and I-yz) with higher accuracy (compared to EKF) and lower computation cost (compared to UKF); the planned trajectories of the dual-arm space robot are effectively for tumbling target capturing.