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Navigating mobile robots with a modular neural architecture

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Abstract

Neural architectures have been proposed to navigate mobile robots within several environment definitions. In this paper a new neural modular constructive approach to navigate mobile robots in unknown environments is presented. The problem, in its basic form, consists of defining and executing a trajectory to a pre-defined goal while avoiding all obstacles, in an unknown environment. Some crucial issues arise when trying to solve this problem, such as an overflow of sensorial information and conflicting objectives. Most neural network (NN) approaches to this problem focus on a monolithic system, i.e., a system with only one neural network that receives and analyses all available information, resulting in conflicting training patterns, long training times and poor generalisation. The work presented in this article circumvents these problems by the use of a constructive modular NN. Navigation capabilities were proven with the NOMAD 200 mobile robot.

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Notes

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Acknowledgements

This work was partially supported by the Portuguese Ministério da Ciência e Tecnologia and the European Union through the R&D Unit 326/94 (CISUC).

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  1. Centro de Informática e Sistemas, Universidade de Coimbra, 3030 Coimbra, Portugal

    Catarina Silva & Bernardete Ribeiro

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  1. Catarina Silva
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  2. Bernardete Ribeiro
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Correspondence to Catarina Silva.

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Silva, C., Ribeiro, B. Navigating mobile robots with a modular neural architecture. Neural Comput & Applic 12, 200–211 (2003). https://doi.org/10.1007/s00521-003-0383-y

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  • DOI: https://doi.org/10.1007/s00521-003-0383-y

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