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A Road Following Approach Using Artificial Neural Networks Combinations

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Abstract

Navigation is a broad topic that has been receiving considerable attention from the mobile robotic community over the years. In order to execute autonomous driving in outdoor urban environments it is necessary to identify parts of the terrain that can be traversed and parts that should be avoided. This paper describes an analyses of terrain identification based on different visual information using a MLP artificial neural network and combining responses of many classifiers. Experimental tests using a vehicle and a video camera have been conducted in real scenarios to evaluate the proposed approach.

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Authors and Affiliations

  1. Institute of Mathematics and Computer Science, University of Sao Paulo, Sao Carlos, SP, Brazil

    Patrick Yuri Shinzato & Denis Fernando Wolf

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  1. Patrick Yuri Shinzato
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  2. Denis Fernando Wolf
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Correspondence to Patrick Yuri Shinzato.

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Shinzato, P.Y., Wolf, D.F. A Road Following Approach Using Artificial Neural Networks Combinations. J Intell Robot Syst 62, 527–546 (2011). https://doi.org/10.1007/s10846-010-9463-2

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  • DOI: https://doi.org/10.1007/s10846-010-9463-2

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