Experimental simulation of satellite relative navigation using computer vision

This paper presents a general description of a mechatronics experimental testbed developed to simulate relative autonomous navigation between satellites using computer vision. Since the experimental tests of relative navigation is not feasible in real systems for the costs and risks that implies, it was decided to construct an experimental platform that simulates the spatial mission scenario. The mission to simulate deals with the recognition and inspection of a satellite by means of another autonomous satellite (Chaser), which approaches its target and verify its actual state. Both relative navigation of the chaser and inspection of the target are based on computer vision. The experimental testbed will be used for the simulations of service missions of satellites to test the performance of the developed vision and navigation algorithms and techniques under space dynamics laws. The system uses a 3D model of the object to achieve the estimation of its position and orientation (pose), and to perform tracking by means of images sequences. The pose estimation and feature correspondence determination are to be solved by algorithms that are capable of achieving them simultaneously. The paper presents and discusses the initial results of the two algorithms that are being used in the simulation testbed.

[1]  Ronen Basri,et al.  Recognition by Linear Combinations of Models , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Gerd Hirzinger,et al.  Registration of CAD-models to images by iterative inverse perspective matching , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[3]  Emil M. Petriu,et al.  Vision-based sensing and control for space robotics applications , 1999, IEEE Trans. Instrum. Meas..

[4]  Chi-Chang J. Ho,et al.  Automatic spacecraft docking using computer vision-based guidance and control techniques , 1993 .

[5]  Samuel Hollander.  Autonomous space robotics - Enabling technologies for advanced space platforms , 2000 .

[6]  Steven B. Skaar,et al.  Camera-Space Manipulation , 1987 .

[7]  Robert M. Haralick,et al.  Analysis and solutions of the three point perspective pose estimation problem , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[8]  Joseph E. Riedel,et al.  Demonstration of Autonomous Orbit Determination Around Small Bodies , 1995 .

[9]  Philip David,et al.  SoftPOSIT: Simultaneous Pose and Correspondence Determination , 2002, ECCV.

[10]  Eric Mjolsness,et al.  New Algorithms for 2D and 3D Point Matching: Pose Estimation and Correspondence , 1998, NIPS.

[11]  P. Jasiobedzki,et al.  Model based pose estimation for autonomous operations in space , 1999, Proceedings 1999 International Conference on Information Intelligence and Systems (Cat. No.PR00446).

[12]  Michel Dhome,et al.  Determination of the Attitude of 3D Objects from a Single Perspective View , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Roger Y. Tsai,et al.  Real time versatile robotics hand/eye calibration using 3D machine vision , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[14]  David G. Lowe,et al.  Fitting Parameterized Three-Dimensional Models to Images , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Yoshiaki Ohkami,et al.  Satellite capturing strategy using agile Orbital Servicing Vehicle, Hyper-OSV , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[16]  Joseph S.-C. Yuan.  A general photogrammetric method for determining object position and orientation , 1989, IEEE Trans. Robotics Autom..