Natural landmark extraction for mobile robot navigation based on an adaptive curvature estimation

Authors:
P. Núñez;R. Vázquez-Martín;J. C. del Toro;A. Bandera;F. Sandoval
Affiliations:
Grupo de Ingeniería de Sistemas Integrados, Dpto. Tecnología Electrónica, E.T.S.I. Telecomunicación, Universidad de Málaga, Campus de Teatinos s/n 29071-Málaga, Spain;Grupo de Ingeniería de Sistemas Integrados, Dpto. Tecnología Electrónica, E.T.S.I. Telecomunicación, Universidad de Málaga, Campus de Teatinos s/n 29071-Málaga, Spain;Grupo de Ingeniería de Sistemas Integrados, Dpto. Tecnología Electrónica, E.T.S.I. Telecomunicación, Universidad de Málaga, Campus de Teatinos s/n 29071-Málaga, Spain;Grupo de Ingeniería de Sistemas Integrados, Dpto. Tecnología Electrónica, E.T.S.I. Telecomunicación, Universidad de Málaga, Campus de Teatinos s/n 29071-Málaga, Spain;Grupo de Ingeniería de Sistemas Integrados, Dpto. Tecnología Electrónica, E.T.S.I. Telecomunicación, Universidad de Málaga, Campus de Teatinos s/n 29071-Málaga, Spain
Venue:
Robotics and Autonomous Systems
Year:
2008

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Abstract

This paper proposes a geometrical feature detection system which is to be used with conventional 2D laser range finders. It consists of three main modules: data acquisition and pre-processing, segmentation and landmark extraction and characterisation. The novelty of this system is a new approach for laser data segmentation based on an adaptive curvature estimation. Contrary to other works, this approach divides the laser scan into line and curve segments. Then, these items are used to directly extract several types of landmarks associated with real and virtual features of the environment (corners, center of tree-like objects, line segments and edges). For each landmark, characterisation provides not only the parameter vector, but also complete statistical information, suitable to be used in a localization and mapping algorithm. Experimental results show that the proposed approach is efficient to detect landmarks for structured and semi-structured environments.