Automated Rendezvous & Docking Using 3D Vision

Abstract

The robustness and accuracy of a vision system for motion estimation of a tumbling target satellite are enhanced by an adaptive Kalman filter. This allows a vision-guided robot to complete the grasping of the target even if occlusion occurs during the operation. A complete dynamics model, including aspects of orbital mechanics, is incorporated for accurate estimation. Based on the model, an adaptive Kalman filter is developed that estimates not only the system states but also all the model parameters such as the inertia ratio, center-of-mass, and the rotation of the principal axes of the target satellite. An experiment is conducted by using a robotic arm to move a satellite mockup according to orbital mechanics while the satellite pose is measured by a laser camera system. The measurements are sent to the Kalman filter, which, in turn, drives another robotic arm to grasp the target. The results demonstrate successful grasping even if the vision system is blocked for several seconds.

References in corpus (4)

• Automated Rendezvous & Docking Using 3D Vision
• Control and Simulation of Motion of Constrained Multibody Systems Based on Projection Matrix Formulation
• Robust 3D Vision for Autonomous Robots
• Six-DOF Spacecraft Dynamics Simulator For Testing Translation and Attitude Control

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• Visual Servoing for Robotic On-Orbit Servicing: A Survey
• Hybrid Simulator for Space Docking and Robotic Proximity Operations
• Autonomous Robots for Active Removal of Orbital Debris
• On Blocking Collisions between People, Objects and other Robots