Abstract
In this paper, a new algorithm is described for dynamic map building with geometrical primitives for a mobile robot. The dynamic map is built up using a 2D range finder mounted on the mobile robot LiAS1 which is navigating in the environment. The dynamic map is used for both planning and localisation purposes. The map is composed of line segments and circles. For the extraction of line segments, a total least squares algorithm is used. The parameters describing the geometrical primitives are provided with uncertainties which are used in the matching phase and which are necessary if the map is used for localisation. This paper describes in detail how the uncertainty on the robot position and the uncertainty on a single range measurement leads to the uncertainty on the parameters of a geometrical primitive. Promising experimental results obtained by the algorithm in real unstructured environments are presented.
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References
Vandorpe J., Van Brussel H., ‘A Reflexive Navigation Algorithm for an Autonomous Mobile Robot', Proc. Int Conf. on Multisensor Fusion and Integration of Intelligent Systems, 1995, pp. 251–259.
Vandorpe J., Van Brussel H., Xu H., ‘LiAS: A Navigation Architecture for an Intelligent Mobile Robot System', Special Issue of IEEE Multisensor Fusion and Integration for Intelligent Systems in the Transactions on Industrial Electronics, June, 1996, pp. 432–440.
Vandorpe J., Van Brussel H., Xu. H, Aertbelien E., ‘Positioning of the Mobile Robot LiAS using Natural Landmarks and a 2D Range Finder', Proc. Int. Conf Multisensor Fusion and Integration for Intelligent Systems, 1996, pp. 257–264.
Xu H., Van Brussel H., De Schutter J., Vandorpe J. ‘Sensor Fusion and Positioning of the Mobile Robot LiAS', Proc. Int. Conf. Intelligent Autonomous Systems 4, 1995, pp. 246–253.
Elfes A., ‘Using Occupancy Grids for Mobile Robot Perception and Navigation', IEEE, Computer, June 1989, pp. 46–57.
Moravec H.P., ‘Sensor Fusion in Certainty Grids for Mobile Robots', AI Magazine 9 (2) 1988, 61–74.
Gonzales J., Ollerd A., Reina A., ‘Map Building for a Mobile Robot with a 2D Laser Rangefinder', Int. Conf. Rob. & Autom., 1994, 1904–1909.
Fortarezza G., Oriolo G., Ulivi G., Vendittelli M., ‘A Mobile Robot Localisation Method for Incremented Map Building and Navigation', Proc. of the 3rd Int. Symp. in Intell. Robotic Systems, 1995, 57–65.
Vandorpe J., Van Brussel H., Xu H., ‘Exact Dynamic Map Building for a Mobile Robot using Geometrical Primitives Produced by a 2D Range Finder', Proc. Int. Conf. on Robotics and Automation, Minneapolis, April 1996, pp. 901–909.
Vandorpe J., ‘Navigation Techniques for the Mobile Robot LiAS', PhD. dissertation 97D3, Katholieke Universiteit Leuven, Dept. Werktuigkunde, PMA, Jan. 1997, ISBN/1996/7515/46.
Hald A., ‘Statistical Theory with Engineering Applications', John Wiley & Sons Inc., New York, 1952.
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© 1998 Springer-Verlag London Limited
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Vandorpe, J., Van Brussel, H., De Schutter, J., Xu, H., Moreas, R. (1998). Positioning of the mobile robot LiAS with line segments extracted from 2D range finder data using total least squares. In: Casals, A., de Almeida, A.T. (eds) Experimental Robotics V. Lecture Notes in Control and Information Sciences, vol 232. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0112977
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DOI: https://doi.org/10.1007/BFb0112977
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