Guidance and Control of a Robot Capturing an Uncooperative Space Target

Guidance and Control of a Robot Capturing an Uncooperative Space Target 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. Keywords Space robot · Target capturing · http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Intelligent & Robotic Systems Springer Journals

Guidance and Control of a Robot Capturing an Uncooperative Space Target

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Publisher
Springer Netherlands
Copyright
Copyright © 2018 by Springer Science+Business Media B.V., part of Springer Nature
Subject
Engineering; Control, Robotics, Mechatronics; Electrical Engineering; Artificial Intelligence (incl. Robotics); Mechanical Engineering
ISSN
0921-0296
eISSN
1573-0409
D.O.I.
10.1007/s10846-018-0874-9
Publisher site
See Article on Publisher Site

Abstract

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. Keywords Space robot · Target capturing ·

Journal

Journal of Intelligent & Robotic SystemsSpringer Journals

Published: Jun 4, 2018

References

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