Abstract
Visual Teach and Repeat (VT&R) allows an autonomous vehicle to repeat a previously traversed route without a global positioning system. Existing implementations of VT&R typically rely on 3D sensors such as stereo cameras for mapping and localization, but many mobile robots are equipped with only 2D monocular vision for tasks such as teleoperated bomb disposal. While simultaneous localization and mapping (SLAM) algorithms exist that can recover 3D structure and motion from monocular images, the scale ambiguity inherent in these methods complicates the estimation and control of lateral path-tracking error, which is essential for achieving high-accuracy path following. In this paper, we propose a monocular vision pipeline that enables kilometre-scale route repetition with centimetre-level accuracy by approximating the ground surface near the vehicle as planar (with some uncertainty) and recovering absolute scale from the known position and orientation of the camera relative to the vehicle. This system provides added value to many existing robots by allowing for high-accuracy autonomous route repetition with a simple software upgrade and no additional sensors. We validate our system over 4.3 km of autonomous navigation and demonstrate accuracy on par with the conventional stereo pipeline, even in highly non-planar terrain.
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References
Barfoot, T., Furgale, P.: Associating uncertainty with three-dimensional poses for use in estimation problems. IEEE Trans. Robot. (T-RO) 30(3), 679–693 (2014)
Bay, H., Ess, A., Tuytelaars, T., Gool, L.V.: Speeded-up robust features (SURF). Comput. Vis. Image Underst. (CVIU) 110, 346–359 (2008)
Choi, S., Joung, J., Yu, W., Cho, J.: Monocular visual odometry under planar motion constraint. In: Proceedings of the International Conference on Control, Automation and Systems (ICCAS), pp. 1480–1485 (2011)
Davison, A.J., Reid, I.D., Molton, N.D., Stasse, O.: MonoSLAM: real-time single camera SLAM. IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI) 29(6), 1052–1067 (2007)
Eade, E., Drummond, T.: Scalable monocular SLAM. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2006)
Farraj, F., Asmar, D.: Non-iterative planar visual odometry using a monocular camera. In: Proceedings of the International Conference on Advanced Robotics (ICAR), pp. 1–6 (2013)
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(6) (1981)
Furgale, P., Barfoot, T.D.: Visual teach and repeat for long-range rover autonomy. J. Field Robot. (JFR) 27(5), 534–560 (2010)
Goedemé, T., Nuttin, M., Tuytelaars, T., Gool, L.V.: Omnidirectional vision based topological navigation. Int. J. Comput. Vision (IJCV) 74(3), 219–236 (2007)
Holmes, S.A., Murray, D.W.: Monocular SLAM with conditionally independent split mapping. IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI) 35(6), 1451–1463 (2013)
Kidono, K., Miura, J., Shirai, Y.: Autonomous visual navigation of a mobile robot using a human-guided experience. Robot. Auton. Syst. (RAS) 40(2–3), 121–130 (2002)
Klein, G., Murray, D.: Parallel tracking and mapping for small AR workspaces. In: Proceedings of IEEE/ACM International Symposium on Mixed and Augmented Reality (ISMAR) (2007)
Lovegrove, S., Davison, A.J., Ibanez-Guzman, J.: Accurate visual odometry from a rear parking camera. In: Proceedings of the Intelligent Vehicles Symposium (IV) (2011)
Marshall, J., Barfoot, T.D., Larsson, J.: Autonomous underground tramming for center-articulated vehicles. J. Field Robot. (JFR) 25, 400–421 (2008)
Matsumoto, Y., Inaba, M., Inoue, H.: Visual navigation using view-sequenced route representation. In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 83–88 (1996)
McManus, C., Furgale, P., Stenning, B., Barfoot, T.D.: Lighting-invariant visual teach and repeat using appearance-based Lidar. J. Field Robot. (JFR) 30(2), 254–287 (2013)
Ostafew, C., Schoellig, A., Barfoot, T.: Iterative learning control to improve mobile robot path tracking in challenging outdoor environments. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 176–181 (2013)
Peretroukhin, V., Kelly, J., Barfoot, T.: Optimizing camera perspective for stereo visual odometry. In: Proceedings of the Conference on Computer and Robot Vision (CRV), pp. 1–7 (2014)
Quigley, M., Conley, K., Gerkey, B.P., Faust, J., Foote, T., Leibs, J., Wheeler, R., Ng, A.Y.: ROS: an open-source robot operating system. In: Proceedings of the ICRA Workshop Open Source Software (2009)
Remazeilles, A., Chaumette, F., Gros, P.: 3D navigation based on a visual memory. In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 2719–2725 (2006)
Royer, E., Lhuillier, M., Dhome, M., Lavest, J.M.: Monocular vision for mobile robot localization and autonomous navigation. Int. J. Comput. Vision (IJCV) 74(3), 237–260 (2007)
Simhon, S., Dudek, G.: A global topological map formed by local metric maps. In: Proceedings of the IEEE/RSJ Intrnational Conference on Intelligent Robots and Systems (IROS), pp. 1708–1714 (1998)
Zhang, A.M., Kleeman, L.: Robust appearance based visual route following for navigation in large-scale outdoor environments. Int. J. Robot. Research (IJRR) 28(3), 331–356 (2009)
Zhang, J., Singh, S., Kantor, G.: Robust monocular visual odometry for a ground vehicle in undulating Terrain. In: Proceedings of the Field and Service Robotics (FSR), pp. 311–326 (2012)
Zhao, L., Huang, S., Yan, L., Jianguo, J., Hu, G., Dissanayake, G.: Large-scale monocular SLAM by local bundle adjustment and map joining. In: Proceedings of the IEEE International Conference on Control, Automation Robotics and Vision (ICARCV), pp. 431–436 (2010)
Acknowledgments
The authors would like to thank Matthew Giamou and Valentin Peretroukhin of the Space and Terrestrial Autonomous Robotic Systems (STARS) lab for their assistance with field testing, the Autonomous Space Robotics Lab (ASRL) for their guidance in interacting with the VT&R code base, Leica Geosystems for providing the MultiStation, and Clearpath Robotics for providing the Husky rover. This work was supported by the Natural Sciences and Engineering Research Council (NSERC) through the NSERC Canadian Field Robotics Network (NCFRN).
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Clement, L., Kelly, J., Barfoot, T.D. (2016). Monocular Visual Teach and Repeat Aided by Local Ground Planarity. In: Wettergreen, D., Barfoot, T. (eds) Field and Service Robotics. Springer Tracts in Advanced Robotics, vol 113. Springer, Cham. https://doi.org/10.1007/978-3-319-27702-8_36
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DOI: https://doi.org/10.1007/978-3-319-27702-8_36
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