International Conference on Transportation and Development 2019
Landmark Assisted Stereo Visual Odometry
Publication: International Conference on Transportation and Development 2019: Innovation and Sustainability in Smart Mobility and Smart Cities
ABSTRACT
In this paper, we consider the positioning technology to facilitate the system services for automatic guided vehicle. Typically, quick response (QR) code is a feasible solution with high accuracy. However, the position information of QR code is discrete and sparse, which leads to uncertainty in position interpolation. To solve this problem, we proposed a positioning system of feature-based stereo visual odometry (VO) by combining some discrete and sparse absolute positioning information. In the proposed system, we adopt stereo cameras to obtain the depth of feature points directly and then apply an algorithm with two parallel threads of tracking and mapping. The mapping thread deals with not only information sent by tracking thread but also those sent by QR code. This proposed system has been tested and verified on our automatic guided vehicle. The measured and computational results suggest that the proposed system has acceptable robustness and relatively high accuracy.
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ACKNOWLEDGEMENTS
This work is supported by the Shenzhen Municipal Science and Technology Innovation Committee under Grant No. JCYJ20170412171044606.
REFERENCES
Bay, H, Ess, A, Tuytelaars, T, et al. Speeded-up robust features (SURF)[J]. Computer vision and image understanding, 2008, 110(3): 346-359.
Cadena, C, Carlone, L, Carrillo, H, et al. Past, present, and future of simultaneous localization and mapping: Toward the robust-perception age[J]. IEEE Transactions on Robotics, 2016, 32(6): 1309-1332.
Engel, J, Schöps, T, Cremers, D. LSD-SLAM: Large-scale direct monocular SLAM[C]//European Conference on Computer Vision. Springer, Cham, 2014: 834-849.
Forster, C, Pizzoli, M, Scaramuzza, D. SVO: Fast semi-direct monocular visual odometry[C]//Robotics and Automation (ICRA), 2014 IEEE International Conference on. IEEE, 2014: 15-22.
Klein, G, Murray, D. Parallel tracking and mapping for small AR workspaces[C]//Mixed and Augmented Reality, 2007. ISMAR 2007. 6th IEEE and ACM International Symposium on. IEEE, 2007: 225-234.
Kümmerle, R, Grisetti, G, Strasdat, H, et al. g2o: A general framework for graph optimization[C]//Robotics and Automation (ICRA), 2011 IEEE International Conference on. IEEE, 2011: 3607-3613.
Lin, Y, Gao, F, Qin, T, et al. Autonomous aerial navigation using monocular visual-inertial fusion[J]. Journal of Field Robotics, 2018, 35(1): 23-51.
Mur-Artal, R, Montiel, J M M, Tardos, J D. ORB-SLAM: a versatile and accurate monocular SLAM system[J]. IEEE Transactions on Robotics, 2015, 31(5): 1147-1163.
Mur-Artal, R, Tardós, J D. Orb-slam2: An open-source slam system for monocular, stereo, and rgb-d cameras[J]. IEEE Transactions on Robotics, 2017, 33(5): 1255-1262.
Ng, P C, Henikoff, S. SIFT: Predicting amino acid changes that affect protein function[J]. Nucleic acids research, 2003, 31(13): 3812-3814.
Pumarola, A, Vakhitov, A, Agudo, A, et al. PL-SLAM: Real-time monocular visual SLAM with points and lines[C]//Robotics and Automation (ICRA), 2017 IEEE International Conference on. IEEE, 2017: 4503-4508.
R. Newcombe, S. Lovegrove, and A. Davison. DTAM: Dense tracking and mapping in real-time. In International Conference on Computer Vision (ICCV), 2011. 2, 3
Rublee, E, Rabaud, V, Konolige, K, et al. ORB: An efficient alternative to SIFT or SURF[C]//Computer Vision (ICCV), 2011 IEEE international conference on. IEEE, 2011: 2564-2571.
Triggs, B, McLauchlan, P F, Hartley, R I, et al. Bundle adjustment—a modern synthesis[C]//International workshop on vision algorithms. Springer, Berlin, Heidelberg, 1999: 298-372.
Zhang, Z. Flexible camera calibration by viewing a plane from unknown orientations[C]//Computer Vision, 1999. The Proceedings of the Seventh IEEE International Conference on. Ieee, 1999, 1: 666-673.
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Published In
International Conference on Transportation and Development 2019: Innovation and Sustainability in Smart Mobility and Smart Cities
Pages: 46 - 53
Editor: David A. Noyce, Ph.D., University of Wisconsin–Madison
ISBN (Online): 978-0-7844-8258-2
Copyright
© 2019 American Society of Civil Engineers.
History
Published online: Aug 28, 2019
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