A stereo-vision system for support of planetary surface exploration

In this paper a system will be presented that was developed for ESA for the support of planetary exploration. The system that is sent to the planetary surface consists of a rover and a lander. The lander contains a stereo head equipped with a pan-tilt mechanism. This vision system is used both for modeling of the terrain and for localization of the rover. Both tasks are necessary for the navigation of the rover. Due to the stress that occurs during the flight a recalibration of the stereo vision system is required once it is deployed on the planet. Due to practical limitations it is infeasible to use a known calibration pattern for this purpose and therefore a new calibration procedure had to be developed that can work on images of the planetary environment. This automatic procedure recovers the relative orientation of the cameras and the pan-and tilt-axis, besides the exterior orientation for all the images. The same images are subsequently used to recover the 3D structure of the terrain. For this purpose a dense stereo matching algorithm is used that - after rectification - computes a disparity map. Finally, all the disparity maps are merged into a single digital terrain model. In this paper a simple and elegant procedure is proposed that achieves that goal. The fact that the same images can be used for both calibration and 3D reconstruction is important since in general the communication bandwidth is very limited. In addition to the use for navigation and path planning, the 3D model of the terrain is also used for Virtual Reality simulation of the mission, in which case the model is texture mapped with the original images. The system has been implemented and the first tests on the ESA planetary terrain testbed were successful.

[1]  R. Rieder,et al.  Nanokhod: A miniature instrument deployment device with instrumentation for chemical, mineralogical and geological analysis of planetary surfaces, for use in connection with fixed planetary surface stations , 1995 .

[2]  Jean-Claude Latombe,et al.  Robot motion planning , 1970, The Kluwer international series in engineering and computer science.

[3]  Olivier D. Faugeras,et al.  What can be seen in three dimensions with an uncalibrated stereo rig , 1992, ECCV.

[4]  Ian D. Reid,et al.  Self-calibration of a stereo rig in a planar scene by data combination , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[5]  Reinhard Koch,et al.  Self-calibration and metric reconstruction in spite of varying and unknown internal camera parameters , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[6]  Charles T. Loop,et al.  Computing rectifying homographies for stereo vision , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[7]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[8]  Ingemar J. Cox,et al.  A Maximum Likelihood Stereo Algorithm , 1996, Comput. Vis. Image Underst..

[9]  Reinhard Koch,et al.  Metric 3D Surface Reconstruction from Uncalibrated Image Sequences , 1998, SMILE.

[10]  Reinhard Koch,et al.  Metric 3D reconstruction from uncalibrated image sequence , 1998 .

[11]  Reinhard Koch,et al.  A simple and efficient rectification method for general motion , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[12]  Christopher G. Harris,et al.  A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.

[13]  Klaus Landzettel,et al.  Autonomous Vision-based Navigation of the Nanokhod Rover , 2001 .

[14]  I. Reid,et al.  Metric calibration of a stereo rig , 1995, Proceedings IEEE Workshop on Representation of Visual Scenes (In Conjunction with ICCV'95).

[15]  Thomas S. Huang,et al.  Theory of Reconstruction from Image Motion , 1992 .

[16]  Reinhard Koch,et al.  Automatische Oberflächenmodellierung starrer dreidimensionaler Objekte aus stereoskopischen Rundum-Ansichten , 1997 .

[17]  Shmuel Peleg,et al.  Stereo panorama with a single camera , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).