Browse > Article
http://dx.doi.org/10.5302/J.ICROS.2006.12.7.693

Thinning-Based Topological Map Building for Local and Global Environments  

Kwon Tae-Bum (고려대학교 기계공학과)
Song Jae-Bok (고려대학교 기계공학과)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.12, no.7, 2006 , pp. 693-699 More about this Journal
Abstract
An accurate and compact map is essential to an autonomous mobile robot system. For navigation, it is efficient to use an occupancy grid map because the environment is represented by probability distribution. But it is difficult to apply it to the large environment since it needs a large amount of memory proportional to the environment size. As an alternative, a topological map can be used to represent it in terms of the discrete nodes with edges connecting them. It is usually constructed by the Voronoi-like graphs, but in this paper the topological map is incrementally built based on the local grid map using the thinning algorithm. This algorithm can extract only meaningful topological information by using the C-obstacle concept in real-time and is robust to the environment change, because its underlying local grid map is constructed based on the Bayesian update formula. In this paper, the position probability is defined to evaluate the quantitative reliability of the end nodes of this thinning-based topological map (TTM). The global TTM can be constructed by merging each local TTM by matching the reliable end nodes determined by the position probability. It is shown that the proposed TTM can represent the environment accurately in real-time and it is readily extended to the global TTM.
Keywords
TTM (Thinning-based Topological Map); grid map; position probability;
Citations & Related Records
연도 인용수 순위
  • Reference
1 A. Elfes, 'Using occupancy grids for mobile robot perception and navigation,' IEEE Journal of Computer, vol. 22, no. 6, pp. 46-57, 1989   DOI   ScienceOn
2 E. Remolina and B. Kuipers, 'Towards a general theory of topological maps,' Artificicl Intelligence, vol. 152, pp. 47-104, 2004   DOI   ScienceOn
3 J. C. Latombe, 'Robot motion planning,' Kluwer Academic Publishers, 1991
4 T. B. Kwon, J. B. Song, and S. Y Lee, 'Improved exploration algorithm using reliabilityndex of thinning based topological nodes,' Proc. of 2005 Int. Conf. on Control. Automation and Systems, pp.250-255, 2005
5 G. A. Baxes, 'Digital image processing,' John Wiley & Sons, 1994
6 H. Choset and K. Nagatani, 'Topological simultaneous localization and mapping (SLAM): Toward exact localization without explicit localization,' IEEE Trans. on Robotics and Automation, vol. 17, no. 2, pp, 125-137, April, 2001   DOI   ScienceOn
7 P. Beeson and B. Kuipers, 'Towards autonomous topological place detection using the extended voronoi graph,' Proc. of IEEE Int. Con. on Robotics and Automation, pp. 4384-4390, 2005
8 J. Modayil, P. Beeson, and B. Kuipers, 'Using the topological skeleton for scalable global metrical map-building,' Proc. of IEEE/RSJ Int. Con. on Intelligent Robots and Systems, vol. 2, pp. 1530-1536, 2004   DOI
9 S. Thrun, 'Learning maps for indoor mobile robot navigation,' ArtijicialIntelligence, vol. 1, pp. 21-71, 1999
10 H. Choset and J. Burdick, 'Sensor-based exploration: the hierarchical generalized voronoi graph,' Int. Journal of Robotics Research, vo1. 19, no. 2, pp. 96-125, 2000   DOI   ScienceOn
11 E. Remolina and B. Kuipers, 'Towards a formalization of the spatial semantic hierarchy,' Proc. of 4th Symosium on Logical Fonnalizations of Commonsense Reasoning, 1998
12 D. V. Zwynsvoorde, T. Simeon, and R. Alami, 'Incremental topological modeling using local voronoi-like graphs,' Proc. of IEEE/RSJ Int. Con. on Intelligent Robots and Systems, vol. 2, pp. 897-902,2001   DOI