Self-Supervised Mapping for Road Shape Estimation Using Laser Remission in Urban Environments
Teppei Saitoh and Yoji Kuroda
Department of Mechanical Engineering, Meiji University, 1-1-1 Higashimita, Tama-ku, Kawasaki, Kanagawa 214-8571, Japan
This paper describes the novel road surface analysis estimating road shape using laser scanner reflectivity in structured outdoor environments. The proposed approach can estimate road shape where a robot can drive safely in complex scenes including structures, curbs or low vegetation and so on. Road shapes are estimated robustly by using information of remission value as reflectivity of a laser, which much less depends on brightness of color or ambient lighting than passive camera. Our proposal is applicable to structured outdoor environments using road surface remission value distributions with self-supervised learning. This article shows that the method is successfully verified with road shape estimation at both the testing course of the 2009 Real World Robot Challenge, which is known as “Tsukuba Challenge” including low vegetation and our university campus.
-  S. Thrun, M. Montemerlo, H. Dahlkamp, D. Stavens, A. Aron, J. Diebel, P. Fong, J. Gale, M. Halpenny, G. Hoffmann, K. Lau, C. Oakley, M. Palatucci, V. Pratt, P. Stang, S. Strohband, C. Dupont, L.-E. Jendrossek, C. Koelen, C. Markey, C. Rummel, J. Niekerk, E. Jensen, P. Alessandrini, G. Bradski, B. Davies, S. Ettinger, A. Kaehler, A. Nefian, and P. Mahoney, “Stanley: The robot that won the DARPA Grand Challenge,” J. of Field Robotics, Vol.23, No.9, pp. 661-692, 2006.
-  C. Urmson, J. Anhalt, D. Bartz, M. Clark, T. Galatali, A. Gutierrez, S. Harbaugh, J. Johnston, H. Kato, P. Koon, W. Messner, N. Miller, A. Mosher, K. Peterson, C. Ragusa, D. Ray, B. Smith, J. Snider, S. Spiker, J. Struble, J. Ziglar, and W. Whittaker, “A robust approach to high-speed navigation for unrehearsed desert terrain,” J. of Field Robotics, Vol.23, pp. 467-508, 2006.
-  M. Montemerlo et al., “Junior: The Stanford entry in the Urban Challenge,” J. of Field Robotics, Vol.25, No.9, Aug 2008.
-  W. S. Wijesoma, K. R. S. Kodagoda, and A. P. Balasuriya, “Road-Boundary Detection and Tracking Using laser Sensing,” IEEE Trans. on robotics and automation, Vol.20, No.3, 2004.
-  B. Southall and C. J. Taylor, “Stochastic road shape estimation,” in Int. Conf. on Computer Vision, pp. 205-212, 2001.
-  S. Nedevschi, R. Schmidt, T. Graf, R. Danescu, D. Frentiu, T. Marita, F. Oniga, and C. Pocol, “3D lane detection system based on stereo-vision,” in Proc. of the IEEE Intelligent Transportation Systems Conference, pp. 161-166, 2004.
-  J. McCall and M. M. Trivedi, “Video based lane estimation and tracking for driver assistance: survey, system, and evaluation,” IEEE Trans. Intell. Transp. Syst., Vol.7, No.1, pp. 20-37, Mar. 2006.
-  M. Beauvais and S. Lakshmanan, “CLARK: a heterogeneous sensor fusion method for finding lanes and obstacles,” Image and Vision Computing, Vol.18, No.5, pp. 397-413, 2000.
-  B. Ma, S. Lakshmanan, and A. O. Hero, “Simultaneous detection of lane and pavement boundaries using model-based multisensor fusion”, IEEE Trans. on Intelligent Transportation Systems, Vol.1, No.5, pp. 135-147, September 2000.
-  P. Pfaff, R. Triebel, C. Stachniss, P. Lamon, W. Burgard, and R. Siegwart, “Towards Mapping of Cities,” In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA ’07), Rome, Italy, April 2007.
-  T. Weiss, B. Schiele, and K. Dietmayer, “Robust Driving Path Detection in Urban and Highway Scenarios using a Laser Scanner and Online Occupancy Grids,” Proc. 2006 IEEE Intelligent Vehicles Symposium (IV2006), pp. 184-189, June 2006.
-  S. Rusinkiewicz and M. Levoy, “Efficient variants of the ICP algorithm,” In Proc. Third Int. Conf. on 3D Digital Imaging and Modeling (3DIM), Quebec City, Canada, 2001.
-  S. Thrun, M. Montemerlo, and A. Aron, “Probabilistic terrain analysis for high-speed desert driving,” In Proc. of the Robotics Science and Systems Conference, 2006.
-  J. Macedo, R. Manduchi, and L. Matthies, “Laser-based discrimination of grass from obstacles for autonomous navigation,” In ISER 2000: Experimental Robotics VII, London, UK, 2001.
-  J.-F. Lalonde, N. Vandapel, D. Huber, and M. Hebert, “Natural terrain classification using three-dimensional ladar data for ground robot mobility,” J. of Field Robotics, Vol.23, No.10, pp. 839-861, 2006.
-  D. F. Wolf, G. Sukhatme, D. Fox, and W. Burgard, “Autonomous terrain mapping and classification using hidden Markov models,” In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), 2005.
-  R. Hadsell, P. Sermanet, J. Ben, A. Erkan, M. Scoffier, K. Kavukvuoglu, U. Muller, and Y. LeCun, “Learning Long-Range Vision for Autonomous Off-Road Driving,” J. of Field Robotics, 2009.
-  M. Bajracharya, A. Howard, L. H. Matthies, B. Tang, and M. Turmon “Autonomous Off-Road Navigation with End-to-End Learning for the LAGR Progrm,” J. of Field Robotics, 2009.
-  P. Sermanet, R. Hadsell, M. Scoffier, M Grimes, J. Ben, A. Erken, C. Crudele, U. Muller, and Y. LeCun “A Multi-Range Architecture for Collision-Free Off-Road Robot Navigation,” J. of Field Robotics, 2009.
-  D. Bradley, R. Unnikrishnan, and J. Bagnell, “Vegetation detection for driving in complex environments,” In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), 2007.
-  R. Manduchi, A. Castano, A. Talukder, and L. Matthies, “Obstacle detection and terrain classification for autonomous off-road navigation,” Autonomous Robots, Vol.18, pp. 81-102, 2003.
-  C. Wellington, A. Courville, and A. Stentz, “A generative model of terrain for autonomous navigation in vegetation,” Int. J. of Robotics Research, Vol.25, No.12, pp. 1287-1304, 2006.
-  H. Dahlkamp, A. Kaehler, D. Stavens, S. Thrun, and G. Bradski, “Self-supervised monocular road detection in desert terrain,” In Proc. of Robotics: Science and Systems (RSS), Philadelphia, USA, 2006.
-  J. Levinson, M. Montemerlo, and S. Thrun, “Map-Based Precision Vehicle Localization in Urban Environments,” Proc. of the Robotics: Science and Systems Conference (RSS), Atlanta, USA. June, 2007.
-  P. Newman et. al, “Navigating, Recognizing and Describing Urban Spaces With Vision and Lasers,” The Int. J. of Robotics Research, Online First, July 21, 2009.
-  K. M. Wurm, R. Kümmerle, C. Stachniss, and W. Burgard, “Improving Robot Navigation in Structured Outdoor Environments by Identifying Vegetation from Laser Data,” In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), 2009.
-  A. Dempster, A. Laird, and D. Rubin, “Maximum likelihood from incomplete data via the EM algorithm,” J. of the Royal Statistical Society, Series B, Vol.39, 1977.
-  S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, “A tutorial on particle filters for on-line non-linear/non-Gaussian Bayesian tracking,” IEEE Trans. on Signal Processing, 2001.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.
Copyright© 2010 by Fuji Technology Press Ltd. and Japan Society of Mechanical Engineers. All right reserved.