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A Stochastic Map Building Method for Mobile Robot using 2-D Laser Range Finder

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Abstract

This paper presents a stochastic map building method for mobile robot using a 2-D laser range finder. Unlike other methods that are based on a set of geometric primitives, the presented method builds a map with a set of obstacle regions. In building a map of the environment, the presented algorithm represents the obstacles with a number of stochastic obstacle regions, each of which is characterized by its own stochastic parameters such as mean and covariance. Whereas the geometric primitives based map sometimes does not fit well to sensor data, the presented method reliably represents various types of obstacles including those of irregular walls and sets of tiny objects. Their shapes and features are easily extracted from the stochastic parameters of their obstacle regions, and are used to develop reliable navigation and obstacle avoidance algorithms. The algorithm updates the world map in real time by detecting the changes of each obstacle region. Consequently, it is adequate for modeling the quasi-static environment, which includes occasional changes in positions of the obstacles rather than constant dynamic moves of the obstacles. The presented map building method has successfully been implemented and tested on the ARES-II mobile robot system equipped with a LADAR 2D-laser range finder.

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References

  • Borenstein, J. and Koren, Y. 1991(a). The vector field histogram fast obstacle avoidance for mobile robot. IEEE Transaction on Robotics and Automation, 7(3):278-288.

    Google Scholar 

  • Boreinstein, J. and Koren, Y. 1991(b). Histogrammic in motion mapping for mobile robot obstacle avoidance. IEEE Transaction on Robotics and Automation, 7(4):535-549.

    Google Scholar 

  • Crowley, J.L. 1989. World modelling and position estimation for a mobile robot using ultra sonic ranging. In Proceedings of the IEEE International Conference on Robotics and Automation, pp. 674-680.

  • Cho, D.W. 1990. Certainty grid representation for robot navigation by a bayesian method. Robotics, 8:159-165.

    Google Scholar 

  • Cho, D.W. and Lim, J.H. 1995. A new certainty grid based mapping and navigation system for an autonomous mobile robot. International Journal of Advanced Manufacturing Technology, 139-148.

  • Elfes, A. 1986. Sonar based real mapping and navigation system. In Proceedings of the IEEE International Conference on Robotics and Automation, pp. 1151-1156.

  • Elfes, A. 1991. Occupancy grids: A stochastic spatial representation for active robot perception. Autonomous Mobile Robot, IEEE Computer Society Press, pp. 60-70.

  • Gonzalez, J., Stentz, A., and Ollero, A. 1995. A mobile robot iconic position estimator using a radial laser scanner. Journal of Intelligent Robotics Systems, 13:161-179.

    Google Scholar 

  • Gonzalez, R.C. and Woods, R.E. 1992. Digital image processing, Addison-Wesley Publishing.

  • Kwon, Y.D. and Lee, J.S. 1995. An obstacle avoidance algorithm for mobile robot: The improved weighted safety vector field method. In Proceedings of the IEEE 10th International Symposium on Intelligent Control, pp. 441-446.

  • Kwon, Y.D. and Lee, J.S. 1996. A local path generation method using obstacle vectors and via points. In Proceeding of WAC 96, pp. 415-420.

  • Leonard, J.J., Durrant-Whyte, H.F., and Cox, J.I. 1992. Dynamic map building for an autonomous mobile robot. The International Journal of Robotics Research, 11(4):286-298.

    Google Scholar 

  • “LADAR 2D Controller Software Programmers Manual,” IBEO Lasertechnik, 1992.

  • Taylor, R.M. and Probert, P.J. 1996. Range finding and feature extraction by segmentation of images for mobile robot navigation. In Proceedings of the IEEE International Conference on Robotics and Automation, pp. 95-100.

  • Vandorpe, J., Van Brussel, H., and Xu, H. 1996. Exact dynamic map building for a mobile robot using geometrical primitives produced by a 2D range finder. In Proceedings of the IEEE International Conference on Robotics and Automation, pp. 901-908.

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Kwon, Y.D., Lee, J.S. A Stochastic Map Building Method for Mobile Robot using 2-D Laser Range Finder. Autonomous Robots 7, 187–200 (1999). https://doi.org/10.1023/A:1008966218715

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  • DOI: https://doi.org/10.1023/A:1008966218715

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