Abstract
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.
Projects funded by the European Space Agency (reference numbers AO/1-6512/10/NL/EK, 4000103357/11/NL/EK, 4000111213/14/NL/PA).
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References
Matthies, L., Maimone, M., Johnson, A., Cheng, Y., Willson, R., Villalpando, C., Goldberg, S., Huertas, A., Stein, A., Angelova, A.: Computer Vision on Mars. International Journal of Computer Vision 75(1), 67–92 (2007)
Howard, T.M., Morfopoulos, A., Morrison, J., Kuwata, Y., Villalpando, C., Matthies, L., McHenry, M.: Enabling continuous planetary rover navigation through FPGA stereo and visual odometry. In: IEEE Aerospace Conference (2012)
Johnson, A., Goldberg, S., Cheng, Y., Matthies, L.: Robust and efficient stereo feature tracking for visual odometry. In: IEEE International Conference on Robotics and Automation, ICRA 2008, pp. 39–46, May 2008
Poulakis, P., Joudrier, L., Wailliez, S., Kapellos, K.: 3DROV: a planetary rover system design, simulation and verification tool. In: Proc. of the 10th Int’l Symposium on Artificial Intelligence, Robotics and Automation in Space (i-SAIRAS-08) (2008)
Woods, M., Shaw, A., Tidey, E., Pham, B.V., Artan, U., Maddison, B., Cross, G.: SEEKER-autonomous long range rover navigation for remote exploration. In: Int’l Symp. on Artificial Intelligence, Robotics and Automation in Space, Italy (2012)
Furgale, P., Carle, P., Enright, J., Barfoot, T.D.: The Devon Island Rover Navigation Dataset. Int’l Journal Robotics Research 31(6), 707–713 (2012)
George, L., Diamantopoulos, D., Siozios, K., Soudris, D., Rodrigalvarez, M.A.: Hardware implementation of stereo correspondence algorithm for the exomars mission. In: 2012 22nd International Conference on Field Programmable Logic and Applications (FPL), pp. 667–670. IEEE (2012)
Szeliski, R.: Computer Vision: Algorithms and Applications. Springer (2010)
Scaramuzza, D., Fraundorfer, F.: Visual odometry [tutorial]. IEEE Robot. Automat. Mag. 18(4), 80–92 (2011)
Bay, H., Ess, E., Tuytelaars, T., Van Gool, L.: Speeded-Up Robust Features (SURF). Comp. Vision and Image Understanding 110(3), 346–359 (2008)
Harris, C., Stephens, M.: A combined corner and edge detector. In: Proceedings of the 4th Alvey Vision Conference, pp. 147–151 (1988)
Rosten, E., Porter, R., Drummond, T.: Faster and better: A machine learning approach to corner detection. IEEE Trans. Pattern Anal. Mach. Intell. 32(1), 105–119 (2010)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int’l Journal of Computer Vision 60(2), 91–110 (2004)
Calonder, M., Lepetit, V., Strecha, C., Fua, P.: Brief: binary robust independent elementary features. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part IV. LNCS, vol. 6314, pp. 778–792. Springer, Heidelberg (2010)
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Lentaris, G. et al. (2015). SPARTAN/SEXTANT/COMPASS: Advancing Space Rover Vision via Reconfigurable Platforms. In: Sano, K., Soudris, D., Hübner, M., Diniz, P. (eds) Applied Reconfigurable Computing. ARC 2015. Lecture Notes in Computer Science(), vol 9040. Springer, Cham. https://doi.org/10.1007/978-3-319-16214-0_44
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DOI: https://doi.org/10.1007/978-3-319-16214-0_44
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