Abstract
This paper presents a method of autonomous topological modeling and localization in a home environment using only low-cost sonar sensors. The topological model is extracted from a grid map using cell decomposition and normalized graph cut. The autonomous topological modeling involves the incremental extraction of a subregion without predefining the number of subregions. A method of topological localization based on this topological model is proposed wherein a current local grid map is compared with the original grid map. The localization is accomplished by obtaining a node probability from a relative motion model and rotational invariant grid-map matching. The proposed method extracts a well-structured topological model of the environment, and the localization provides reliable node probability even when presented with sparse and uncertain sonar data. Experimental results demonstrate the performance of the proposed topological modeling and localization in a real home environment.
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References
Beeson, P., Jong, N. K., & Kuipers, B. (2005). Towards autonomous topological place detection using the extended Voronoi graph. In Proc. of IEEE international conference on robotics and automation (pp. 4373–4379).
Brunskill, E., Kollar, T., & Roy, N. (2007). Topological mapping using spectral clustering and classification. In Proc. of IEEE/RSJ international conference on intelligent robots and systems (pp. 3491–3496).
Buschka, P., & Saffiotti, A. (2002). A virtual sensor for room detection. In Proc. of IEEE/RSJ international conference on intelligent robots and systems (pp. 637–642).
Choi, J., Ahn, S., & Chung, W. K. (2005). Robust sonar feature detection for the SLAM of mobile robot. In Proc. of IEEE/RSJ international conference on intelligent robots and systems (pp. 3415–3420).
Choi, J., Choi, M., Lee, K., & Chung, W. K. (2009a). Topological modeling and classification in home environment using sonar gridmap. In Proc. of IEEE international conference on robotics and automation (pp. 3892–3898).
Choi, J., Choi, M., & Chung, W. K. (2009b). Incremental topological modeling using sonar gridmap in home environment. In Proc. of IEEE/RSJ international conference on intelligent robots and systems (pp. 3582–3587).
Choset, H., & Nagatani, K. (2001). Topological simultaneous localization and mapping (SLAM): Toward exact localization without explicit localization. IEEE Transactions on Robotics and Automation, 17(2), 125–137.
Doh, N. L., Lee, K., Chung, W. K., & Cho, H. (2009). Simultaneous localisation and mapping algorithm for topological maps with dynamics. IET Control Theory and Applications, 3(9), 1249–1260.
Elfes, A. (1989). Using occupancy grids for mobile robot perception and navigation. IEEE Computer, 22(6), 46–57.
Gonzalez, R. C., & Woods, R. E. (2002). Digital image processing (2nd ed.). New Jersey: Prentice Hall.
Gutmann, J.-S., & Konolige, K. (1999). Incremental mapping of large cyclic environments. In Proc. of IEEE international symposium on computational intelligence in robotics and automation (pp. 318–325).
Katevas, N. I., Tzafestas, S. G., & Pnevmatikatos, C. G. (1998). The approximate cell decomposition with local node refinement global path planning method: Path nodes refinement and curve parametric interpolation. Journal of Intelligent and Robotic Systems, 22(3–4), 289–314.
Kleeman, L., & Kuc, R. (2008). Sonar sensing. In B. Siciliano & O. Khatib (Eds.), Handbook on robotics. Berlin: Springer.
Lee, K., Cho, N., Chung, W. K., & Doh, N. L. (2006). Topological navigation of mobile robot in corridor environment using sonar sensor. In Proc. of IEEE/RSJ international conference on intelligent robots and systems (pp. 2760–2765).
Lee, K., & Chung, W. K. (2009). Effective maximum likelihood grid map with conflict evaluation filter using sonar sensors. IEEE Transactions on Robotics, 25(4), 887–901.
Leonard, J. J., & Durrant-Whyte, H. F. (1991). Simultaneous map building and localization for an autonomous mobile robot. In Proc. of IEEE/RSJ international conference on intelligent robots and systems (pp. 1442–1447).
Lin, Y., Chen, C., & Wei, C. (2006). New method for subpixel image matching with rotation invariance by combining the parametric template method and the ring projection transform process. Optical Engineering, 45(6), 067 202(1-9).
Mozos, O. M., & Burgard, W. (2006). Supervised learning of topological maps using semantic information extracted from range data. In Proc. of IEEE/RSJ international conference on intelligent robots and systems (pp. 2772–2777).
Remolina, E., & Kuipers, B. (2004). Towards a general theory of topological maps. Artificial Intelligence, 152, 47–104.
Shi, J., & Malik, J. (2000). Normalized cuts and image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(8), 888–905.
Tapus, A., & Siegwart, R. (2006). A cognitive modeling of space using fingerprints of places for mobile robot navigation. In Proc. of IEEE international conference on robotics and automation (pp. 1188–1193).
Tardós, J. D., Neira, J., Newman, P. M., & Leonard, J. J. (2002). Robust mapping and localization in indoor environments using sonar data. International Journal of Robotic Research, 21(4), 311–330.
Thrun, S. (1998). Learning metric-topological maps for indoor mobile robot navigation. Artificial Intelligence, 99(1), 21–77.
Thrun, S., Fox, D., Burgard, W., & Dellaert, F. (2001). Robust Monte Carlo localization for mobile robots. Artificial Intelligence, 128(1–2), 99–141.
Thrun, S. (2002). Robotic mapping: A survey. In G. Lakemeyer, & B. Nebel (Eds.), Exploring artificial intelligence in the new millennium. San Mateo: Morgan Kaufmann.
Yap, T. N., & Shelton, C. R. (2009). SLAM in large indoor environments with low-cost, noisy, and sparse sonars. In Proc. of IEEE international conference on robotics and automation (pp. 1395–1401).
Yun, Y., Park, B., & Chung, W. K. (2008). Odometry calibration using home positioning function for mobile robot. In Proc. of IEEE international conference on robotics and automation (pp. 2116–2121).
Zivkovic, Z., Bakker, B., & Krose, B. (2006). Hierarchical map building and planning based on graph partitioning. In Proc. of IEEE international conference on robotics and automation (pp. 803–809).
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Choi, J., Choi, M., Nam, S.Y. et al. Autonomous topological modeling of a home environment and topological localization using a sonar grid map. Auton Robot 30, 351–368 (2011). https://doi.org/10.1007/s10514-011-9223-6
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DOI: https://doi.org/10.1007/s10514-011-9223-6