A multi‐stage matching algorithm for mobile robot navigation

Industrial Robot - 2007
JianHou1, Nai M.Qi1, HongZhang1
1Harbin Institute of Technology, Harbin, People's Republic of China

Tóm tắt

PurposeStereo vision is an attractive perception technique for mobile robots navigation. Stereo matching is a crucial part of stereo vision and its precision dominates the precision of reconstruction. Based on a geometry constraint applicable to natural terrain, the purpose of this paper is to present a multi‐stage stereo matching algorithm to improve matching accuracy.Design/methodology/approachIn the multi‐stage matching algorithm, points with larger intensity gradient are matched in earlier stages. Using several constraints and statistical means, information from earlier stages is utilized to assist in matching of later stages to improve matching accuracy.FindingsThe multi‐stage matching algorithm improves the matching accuracy of stereo pairs of natural terrain in various conditions.Research limitations/implicationsThe algorithm demonstrates advantages over area‐matching algorithm both in matching accuracy and computation efficiency. However, if used for real‐time navigation, it still needs the assistance of specialized hardware or window selection technique.Practical implicationsThe algorithm is able to produce dense disparity maps of natural terrain with fairly high accuracy and can be used for the navigation of planetary rover or other outdoor mobile robots.Originality/valueThe paper provides a new approach to produce accurate and dense disparity maps of natural terrain, which laid the foundation for its use in outdoor mobile robots navigation.

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Tài liệu tham khảo

Bart, P. and Jules, B. (1980), “A disparity gradient limit for binocular fusion”, Science, Vol. 208, pp. 615‐7.

Desouza, G.N. and Kak, A.C. (2002), “Vision for mobile robot navigation: a survey”, IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 24 No. 2, pp. 237‐67.

Goldbert, S.B., Maimone, M.W. and Matthies, L. (2002), “Stereo vision and rover navigation software for planetary exploration”, Proceedings of Aerospace Conference, IEEE, Vol. 5, pp. 2025‐36.

Kanade, T. and Okutomi, M. (1994), “A stereo matching algorithm with an adaptive window: theory and experiment”, IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 16 No. 9, pp. 920‐32.

Krotkov, E. and Hebert, M. (1995), “Mapping and positioning for a prototype lunar rover”, Proceedings of the International Conference on Robotics and Automation, IEEE, Vol. 3, pp. 2913‐9.

Krotkov, E. and Hoffman, R. (1994), “Terrain mapping for a walking planetary rover”, IEEE Trans. on Robotics and Automation, Vol. 10 No. 6, pp. 728‐39.

Lew, M.S., Huang, T.S. and Wong, K. (1994), “Learning and feature selection in stereo matching”, IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 16 No. 9, pp. 869‐81.

Maurette, M. (2003), “Mars rover autonomous navigation”, Autonomous Robots, Vol. 14 Nos 2/3, pp. 199‐208.

Szeliski, R. and Scharstein, D. (2004), “Sampling the disparity space image”, IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 26 No. 3, pp. 419‐25.

Williamson, T. and Thorpe, C. (1999), “A trinocular stereo system for highway obstacle detection”, Proc. IEEE Int'l Conf. Robotics and Automation.

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