Abstract
Autonomous exploration is an important tasks in many robotic fields such as disaster response scenarios. In time critical situations, the use of multiple robots can reduce the time to create a complete map of the environment. However among the most popular map formats in use today, none are ideal for the multi-robot autonomous indoor localization. In terms of memory usage, visualization, and usability in navigation and exploration tasks, all formats have some strengths and weaknesses.
In this paper we introduce PolyMap, a map format that is based on simple polygons. Since the polygons are based on line segments, this is a special case of vector-based map formats. This format provides advantages in terms of memory footprint over occupancy grids, while not falling behind in visualization. Its sparse nature is also an advantage for navigation tasks, in particular when the map needs to be shared over a wireless network connection. Additionally the explicit modeling of frontiers helps with autonomous exploration.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
References
Baizid, K., Lozenguez, G., Fabresse, L., Bouraqadi, N.: Vector maps: a lightweight and accurate map format for multi-robot systems. In: Kubota, N., Kiguchi, K., Liu, H., Obo, T. (eds.) ICIRA 2016. LNCS (LNAI), vol. 9834, pp. 418–429. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-43506-0_37
Castellanos, J.A., Montiel, J., Neira, J., Tardós, J.D.: The SPmap: a probabilistic framework for simultaneous localization and map building. IEEE Trans. Robot. Autom. 15(5), 948–952 (1999)
Chatila, R., Laumond, J.P.: Position referencing and consistent world modeling for mobile robots. In: Proceedings of the 1985 IEEE International Conference on Robotics and Automation, vol. 2, pp. 138–145. IEEE (1985)
Chen, Y., Qu, C., Wang, Q., Jin, Z., Shen, M., Shen, J.: TVSLAM: an efficient topological-vector based SLAM algorithm for home cleaning robots. In: Huang, Y.A., Wu, H., Liu, H., Yin, Z. (eds.) ICIRA 2017. LNCS (LNAI), vol. 10464, pp. 166–178. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-65298-6_16
The Robot Map Data Representation (MDR) Working Group: IEEE standard for robot map data representation for navigation, sponsor: IEEE robotics and automation society, June 2016. http://standards.ieee.org/findstds/standard/1873-2015.html
Jelinek, A.: Vector maps in mobile robotics. Acta Polytech. CTU Proc. 2(2), 22–28 (2015)
LaValle, S.M.: Planning Algorithms. Cambridge University Press, New York (2006)
Lv, J., Kobayashi, Y., Ravankar, A.A., Emaru, T.: Straight line segments extraction and EKF-SLAM in indoor environment. J. Autom. Control Eng. 2(3), 270–276 (2014)
Pfister, S.T., Roumeliotis, S.I., Burdick, J.W.: Weighted line fitting algorithms for mobile robot map building and efficient data representation. In: Proceedings of the IEEE International Conference on Robotics and Automation, 2003, ICRA 2003, vol. 1, pp. 1304–1311. IEEE (2003)
Ravankar, A., Ravankar, A.A., Hoshino, Y., Emaru, T., Kobayashi, Y.: On a hopping-points SVD and hough transform-based line detection algorithm for robot localization and mapping. Int. J. Adv. Robot. Syst. 13(3), 98 (2016)
Sohn, H.J., Kim, B.K.: VecSLAM: an efficient vector-based SLAM algorithm for indoor environments. J. Intell. Rob. Syst. 56(3), 301–318 (2009). https://doi.org/10.1007/s10846-009-9313-2
Stachniss, C., Grisetti, G., Hähnel, D., Burgard, W.: Improved rao-blackwellized mapping by adaptive sampling and active loop-closure. In: Proceedings of the Workshop on Self-Organization of AdaptiVE behavior (SOAVE) (2004)
Toussaint, G.: Efficient triangulation of simple polygons. Visual Comput. 7(5–6), 280–295 (1991)
Yamauchi, B.: A frontier-based approach for autonomous exploration. In: Proceedings of CIRA 1997 (1997)
Acknowledgment
This work is part of the CPER DATA project that is supported by Région Hauts de France, and the French state.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Dichtl, J., Fabresse, L., Lozenguez, G., Bouraqadi, N. (2018). PolyMap: A 2D Polygon-Based Map Format for Multi-robot Autonomous Indoor Localization and Mapping. In: Chen, Z., Mendes, A., Yan, Y., Chen, S. (eds) Intelligent Robotics and Applications. ICIRA 2018. Lecture Notes in Computer Science(), vol 10984. Springer, Cham. https://doi.org/10.1007/978-3-319-97586-3_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-97586-3_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-97585-6
Online ISBN: 978-3-319-97586-3
eBook Packages: Computer ScienceComputer Science (R0)