SPARTAN/SEXTANT/COMPASS: Advancing Space Rover Vision via Reconfigurable Platforms

Targeting enhanced navigational speed and autonomy for the space exploration rovers, researchers are gradually turning to reconfigurable computing and FPGAs. High-density space-grade FPGAs will enable the acceleration of high-complexity computer vision algorithms for improving the localization and mapping functions of the future Mars rovers. In the projects SPARTAN/SEXTANT/COMPASS of the European Space Agency, we study the potential use of FPGAs for implementing a variety of stereo correspondence, feature extraction, and visual odometry algorithms, all with distinct cost-performance tradeoffs. The most efficient of the developed accelerators will assist the slow space-grade CPU in completing the visual tasks of the rover faster, by one order of magnitude, and thus, will allow the future missions to visit larger areas on Mars. Our work bases on a custom HW/SW co-design methodology, parallel architecture design, optimization techniques, tradeoff analysis, and system tuning with Martian-like scenarios.

[1]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[2]  Luc Van Gool,et al.  Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..

[3]  Richard Szeliski,et al.  Computer Vision - Algorithms and Applications , 2011, Texts in Computer Science.

[4]  Y. Kuwata,et al.  Enabling continuous planetary rover navigation through FPGA stereo and visual odometry , 2012, 2012 IEEE Aerospace Conference.

[5]  Tom Drummond,et al.  Faster and Better: A Machine Learning Approach to Corner Detection , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Dimitrios Soudris,et al.  Hardware implementation of stereo correspondence algorithm for the ExoMars mission , 2012, 22nd International Conference on Field Programmable Logic and Applications (FPL).

[7]  Vincent Lepetit,et al.  BRIEF: Binary Robust Independent Elementary Features , 2010, ECCV.

[8]  Mark Woods,et al.  Seeker—Autonomous Long‐range Rover Navigation for Remote Exploration , 2014, J. Field Robotics.

[9]  K. Kapellos,et al.  DROV : A Planetary Rover System Design , Simulation and Verification Tool , 2008 .

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

[11]  Andrew E. Johnson,et al.  Computer Vision on Mars , 2007, International Journal of Computer Vision.

[12]  John Enright,et al.  The Devon Island rover navigation dataset , 2012, Int. J. Robotics Res..

[13]  Friedrich Fraundorfer,et al.  Visual Odometry Part I: The First 30 Years and Fundamentals , 2022 .

[14]  Larry H. Matthies,et al.  Robust and Efficient Stereo Feature Tracking for Visual Odometry , 2008, 2008 IEEE International Conference on Robotics and Automation.