Summary
Segment-based maps have recently emerged as an effective solution to reduce the dimensions of environment models built by mobile robots. In this paper, we present a novel method for building segment-based maps that contain a small number of line segments. The method works also when data are collected by many robots. Experimental results show that our approach is effective in significantly reducing the size of the resulting maps.
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References
F. Amigoni, S. Gasparini, and M. Gini. Scan matching without odometry information. In Proc. of the Int’l Conf. on Informatics in Control, Automation and Robotics, pages 349–352, 2004.
D. Austin and B. McCarragher. Geometric constraint identification and mapping for mobile robots. ROBOT AUTON SYST, 35:59–76, 2001.
E. Brunskill and N. Roy. SLAM using incremental probabilistic PCA and dimensionality reduction. In Proc. of the IEEE Int’l Conf. on Robotics and Automation, pages 342–347, 2005.
J. Gasós and A. Martín. Mobile robot localization using fuzzy maps. In T. Martin and A. Ralescu, editors, Fuzzy Logic in AI-Proc. of the IJCAI’95 Workshop, volume LNAI 1188, pages 207–224. Springer-Verlag, 1997.
H. H. Gonzáles-Baños and J. C. Latombe. Navigation strategies for exploring indoor environments. INT J ROBOT RES, 21(10–11):829–848, 2002.
Y. L. Ip, A. B. Rad, K. M. Chow, and Y. K. Wong. Segment-based map building using enhanced adaptive fuzzy clustering algorithm for mobile robot applications. J INTELL ROBOT SYST, 35:221–245, 2002.
L. J. Latecki, R. Lakaemper, X. Sun, and D. Wolter. Building polygonal maps from laser range data. In Int’l Cognitive Robotics Workshop, 2004.
M. López-Sánchez, F. Esteva, R. López De Màntanaras, and C. Sierra. Map generation by cooperativa low-cost robots in structured unknown environments. AUTON ROBOT, 5:53–61.
F. Lu and E. Milios. Robot pose estimation in unknown environments by matching 2D range scans. J INTELL ROBOT SYST, 18(3):249–275, 1998.
R. Mázl and L. Přeučil. Building a 2d environment map from laser range-finder data. In Proc. of the IEEE Intelligent Vehicles Symposium, pages 290–295, 2000.
J. W. Burdick S. T. Pfister, S. I. Roumeliotis. Weighted line fitting algorithms for mobile robot map building and efficient data representation. In Proc. of the IEEE Int’l Conf. on Robotics and Automation, pages 1304–1311, 2003.
S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2003.
E. Zalama, G. Candela, J. Gómez, and S. Thrun. Concurrent mapping and localization for mobile robots with segmented local maps. In Proc. of the IEEE/RSJ Int’l Conf. on Intelligent Robots and Systems, pages 546–551, 2002.
L. Zhang and B. Ghosh. Line segment based map building and localization using 2D laser rangefinder. In Proc. of the IEEE Int’l Conf. on Robotics and Automation, pages 2538–2543, 2000.
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© 2006 Springer-Verlag Tokyo
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Amigoni, F., Fontana, G., Garigiola, F. (2006). A Method for Building Small-Size Segment-Based Maps. In: Gini, M., Voyles, R. (eds) Distributed Autonomous Robotic Systems 7. Springer, Tokyo. https://doi.org/10.1007/4-431-35881-1_2
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DOI: https://doi.org/10.1007/4-431-35881-1_2
Publisher Name: Springer, Tokyo
Print ISBN: 978-4-431-35878-7
Online ISBN: 978-4-431-35881-7
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