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Experimental Comparison of Odometry Approaches

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Experimental Robotics

Abstract

Odometry is an important input to robot navigation systems, and we are interested in the performance of vision-only techniques. In this paper we experimentally evaluate and compare the performance of wheel odometry, monocular feature-based visual odometry, monocular patch-based visual odometry, and a technique that fuses wheel odometry and visual odometry, on a mobile robot operating in a typical indoor environment.

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References

  1. Konolige, K., Agrawal, M.: Frameslam: From bundle adjustment to real-time visual mapping. IEEE Transactions on Robotics 24(5), 1066–1077 (2008)

    Article  Google Scholar 

  2. Warren, M., McKinnon, D., He, H., Upcroft, B.: Unaided stereo vision based pose estimation. In: Australasian Conference on Robotics and Automation, ARAA, Brisbane (2010)

    Google Scholar 

  3. Sibley, G., Mei, C., Reid, I., Newman, P.: Adaptive relative bundle adjustment. In: Proceedings of Robotics: Science and Systems, Seattle, USA (June 2009)

    Google Scholar 

  4. Pollefeys, M., Van Gool, L., Vergauwen, M., Verbiest, F., Cornelis, K., Tops, J., Koch, R.: Visual modeling with a hand-held camera. International Journal of Computer Vision 59(3), 207–232 (2004)

    Article  Google Scholar 

  5. Olson, C., Matthies, L., Schoppers, H., Maimone, M.: Robust stereo ego-motion for long distance navigation. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 453–458 (2000)

    Google Scholar 

  6. Corke, P., Strelow, D., Singh, S.: Omnidirectional visual odometry for a planetary rover. In: Proceedings of 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2004), Sendai, Japan (September 2004)

    Google Scholar 

  7. Nistér, D., Naroditsky, O., Bergen, J.R.: Visual odometry. In: CVPR (1), pp. 652–659 (2004)

    Google Scholar 

  8. Nistér, D.: An efficient solution to the five-point relative pose problem. IEEE Trans. Pattern Anal. Mach. Intell. 26(6), 756–777 (2004)

    Article  Google Scholar 

  9. Davison, A., Reid, I., Molton, N., Stasse, O.: Monoslam: Real-time single camera slam. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(6), 1052–1067 (2007)

    Article  Google Scholar 

  10. Klein, G., Murray, D.: Parallel tracking and mapping for small AR workspaces. In: Proc. Sixth IEEE and ACM International Symposium on Mixed and Augmented Reality (ISMAR 2007), Nara, Japan (November 2007)

    Google Scholar 

  11. Clipp, B., Lim, J., Frahm, J.M., Pollefeys, M.: Parallel, real-time visual slam. In: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan, pp. 3961–3968 (2010)

    Google Scholar 

  12. Konolige, K., Bowman, J., Chen, J., Mihelich, P., Calonder, M., Lepetit, V., Fua, P.: View-based maps. The International Journal of Robotics Research 29(8), 941–957 (2010)

    Article  Google Scholar 

  13. Lowe, D.: Object recognition from local scale-invariant features. In: IEEE International Conference on Computer Vision, vol. 2, pp. 1150–1157 (1999)

    Google Scholar 

  14. Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: Speeded-up robust features (SURF). Comput. Vis. Image Underst. 110, 346–359 (2008)

    Article  Google Scholar 

  15. Milford, M., Schill, F., Corke, P., Mahony, R., Wyeth, G.: Aerial SLAM with a single camera using visual expectation. In: International Conference on Robotics and Automation, Shanghai, China (May 2011)

    Google Scholar 

  16. Grisetti, G., Stachniss, C., Burgard, W.: Improved techniques for grid mapping with rao-blackwellized particle filters. IEEE Transactions on Robotics 23(1), 34–46 (2007)

    Article  Google Scholar 

  17. Konolige, K., Agrawal, M., Sol, J.: Large scale visual odometry for rough terrain. In: Proc. International Symposium on Robotics Research, Hiroshima, Japan (2007)

    Google Scholar 

  18. Mei, C., Sibley, G., Cummins, M., Newman, P., Reid, I.: A constant time efficient stereo SLAM system. In: British Machine Vision Conference (BMVC), London (2009)

    Google Scholar 

  19. Haralick, R.M., Lee, C.N., Ottenberg, K., Nölle, M.: Review and analysis of solutions of the three point perspective pose estimation problem. Int. J. Comput. Vision 13, 331–356 (1994)

    Article  Google Scholar 

  20. Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24, 381–395 (1981)

    Article  MathSciNet  Google Scholar 

  21. Torr, P.H.S., Zisserman, A.: MLESAC: A new robust estimator with application to estimating image geometry. Computer Vision and Image Understanding 78, 138–156 (2000)

    Article  Google Scholar 

  22. Matas, J., Chum, O.: Randomized ransac with td,d test. Image and Vision Computing 22(10), 837–842 (2004)

    Article  Google Scholar 

  23. Fox, D.: KLD-sampling: Adaptive particle filters. In: Advances in Neural Information Processing Systems, pp. 713–720. MIT Press (2001)

    Google Scholar 

  24. 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, pp. 39–46 (May 2008)

    Google Scholar 

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Correspondence to Liz Murphy .

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Murphy, L. et al. (2013). Experimental Comparison of Odometry Approaches. In: Desai, J., Dudek, G., Khatib, O., Kumar, V. (eds) Experimental Robotics. Springer Tracts in Advanced Robotics, vol 88. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00065-7_58

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  • DOI: https://doi.org/10.1007/978-3-319-00065-7_58

  • Publisher Name: Springer, Heidelberg

  • Print ISBN: 978-3-319-00064-0

  • Online ISBN: 978-3-319-00065-7

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