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Direction Augmented Probabilistic Scan Matching for Reliable Localization

신뢰성 높은 위치 인식을 위하여 방향을 고려한 확률적 스캔 매칭 기법

  • 최민용 (포항공과대학교 기계공학과) ;
  • 최진우 (포항공과대학교 기계공학과) ;
  • 정완균 (포항공과대학교 기계공학과)
  • Received : 2011.09.16
  • Accepted : 2011.10.24
  • Published : 2011.12.01

Abstract

The scan matching is widely used in localization and mapping of mobile robots. This paper presents a probabilistic scan matching method. To improve the performance of the scan matching, a direction of data point is incorporated into the scan matching. The direction of data point is calculated using the line fitted by the neighborhood data. Owing to the incorporation, the performance of the matching was improved. The number of iterations in the scan matching decreased, and the tolerance against a high rotation between scans increased. Based on real data of a laser range finder, experiments verified the performance of the proposed direction augmented probabilistic scan matching algorithm.

Keywords

References

  1. P. Besl and N. McKay, "A method for registration of 3-D shapes," IEEE Trans. Pattern Anal. Mach. Intell., vol. 14, no. 2, pp. 239-256, Feb. 1992. https://doi.org/10.1109/34.121791
  2. F. Lu and E. Milios, "Robot pose estimation in unknown environments by matching 2D range scans," Intelligent and Robotic Systems, vol. 18, no. 3, pp. 249-275, Mar. 1997. https://doi.org/10.1023/A:1007957421070
  3. J. Minguez, L. Montesano, and F. Lamiraux, "Metric-based iterative closest point scan matching for sensor displacement estimation," IEEE Trans. Robot., vol. 22, no. 5, pp. 1047-1054, Oct. 2006. https://doi.org/10.1109/TRO.2006.878961
  4. L. Armesto, J. Minguez, and L. Montesano, "A generalization of the metric-based iterative closest point technique for 3D Scan matching," Proc. of IEEE Intl. Conf. Robot. Autom., Anchorage, USA, pp. 1367-1372, May 2010.
  5. L. Montesano, J. Minguez, and L. Montano, "Probabilistic scan matching for motion estimation in unstructured environments," Proc. of IEEE/RSJ Intl. Conf. Intell. Robot. Syst., Edmonton, Canada, pp. 1445-1450, Aug. 2005.
  6. A. Burguera, Y. González, and G. Oliver, "Probabilistic sonar scan matching for robust localization," Proc. of IEEE Intl. Conf. Robot. Autom., Roma, Italy, pp. 3154-3160, Apr. 2007.
  7. D. A. Forsyth and J. Ponce, Computer Vision A Modern Approach, Prentice Hall, New Jersey, 2003.
  8. Y. Bar-Shalom and T. Fortmann, Tracking and Data Association, Academic Press, Inc., Orlando, 1988.
  9. From Wikipedia, the free encyclopedia, Chi-square distribution, http://en.wikipedia.org/wiki/Chi-square_distribution