This paper presented a new method to guide and control a space robot for capturing an uncooperative target. The dynamic model of a target is unknown and estimated with the help of vision system. This methodology has three different steps. First, the feature points of a space target were extracted using the vision system, then the pose of the target (position and orientation) relative to the space robot was determined based on Homography method. Second, because of an unknown model of the target, the location of the center of mass is calculated using kinematic equations and Iterative Closest Point (ICP) algorithm. This would help tracking moving target. Third, a new Adaptive Unscented Kalman Filter (AUKF) was introduced to estimate the dynamic state vector (position, orientation, linear and angular velocities) of an arbitrary space target. The error in AUKF estimation was prevented from divergence by using Fuzzy Logic Adaptive System (FLAS). Finally, a new trajectory method for planning the end-effector velocities of the space robot arm was implemented based on the measurement information from the vision system and estimation a target state using AUKF. The results from simulation experiments were presented and discussed.

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Keywords Adaptive Unscented Kalman Filter (AUKF), Machine vision, Space robot, Target capturing
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Journal Journal of Intelligent and Robotic Systems: Theory and Applications
Al-Isawi, M.M.A. (Malik M. A.), & Sasiadek, J. (2018). Guidance and Control of a Robot Capturing an Uncooperative Space Target. Journal of Intelligent and Robotic Systems: Theory and Applications, 1–9. doi:10.1007/s10846-018-0874-9