far and proximity maneuvers of a constellation of service satellites applied in rendezvous missions, and autonomous estimation of customer satellite using machine vision
- Paper number
IAC-08.C1.5.2
- Author
Dr. Evandro Marconi Rocco, National Institute for Space Research - INPE , Brazil
- Coauthor
Mr. Gilberto Arantes Junior, ZARM - University of Bremen, Germany
- Coauthor
Dr. Ijar M. Da Fonseca, Instituto Nacional de Pesquisas Espaciais (INPE) - MCT, Brazil
- Coauthor
Dr. Stephan Theil, DLR, German Space Agency, Germany
- Year
2008
- Abstract
Space robotics has a substantial interest in achieving on-orbit satellite servicing operations autonomously, e.g. rendezvous and docking/berthing (RVD) with customer and malfunctionng satellites. An on-orbiter service vehicle requires the ability to estimate the position and attitude in situations whenever the targets are uncooperative. Such situation comes up when the target is damaged. In this context, this work presents a robust autonomous pose system applied to RVD missions. Our approach is based on computer vision, using a single camera and some previous knowledge of the target, i.e. the customer spacecraft. A rendezvous analysis mission tool for autonomous service satellite has been developted and presented, for far maneuvers, e.g. distance above 1 kilometer from the target, and close maneuvers. The far operations consist of orbit transfer using the Lambert formulation. The close operations include the inspection phase (during which the pose estimation is computed) and the final approach phase. In the close operations our approach is based on the Hill equations, used to simulate and analyze the approaching and final trajectory between target and chase during the last phase of the rendezvous. A method for optimally estimating the relative orientation and position between camera system and target is presented in detail. The target is modeled as an assembly of points. The pose of the target is represented by dual quaternion in order to develop a simple quadratic error function in such way that the pose estimation task becomes a least square minimization problem. The problem of pose is solved and some methods of non-linear square optimization (Newton, Newton-Gauss, and Levenberg-Marquard) are compared and discussed in terms of accuracy and computational cost.
- Abstract document
- Manuscript document
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