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A Biologically Inspired Autonomous Robot Control Based on Behavioural Coordination in Evolutionary Robotics

A Biologically Inspired Autonomous Robot Control Based on Behavioural Coordination in Evolutionary Robotics

José A. Fernández-León, Gerardo G. Acosta, Miguel A. Mayosky, Oscar C. Ibáñez
Copyright: © 2009 |Pages: 23
ISBN13: 9781599049960|ISBN10: 1599049961|EISBN13: 9781599049977
DOI: 10.4018/978-1-59904-996-0.ch007
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MLA

Fernández-León, José A., et al. "A Biologically Inspired Autonomous Robot Control Based on Behavioural Coordination in Evolutionary Robotics." Advancing Artificial Intelligence through Biological Process Applications, edited by Ana B. Porto Pazos, et al., IGI Global, 2009, pp. 107-129. https://doi.org/10.4018/978-1-59904-996-0.ch007

APA

Fernández-León, J. A., Acosta, G. G., Mayosky, M. A., & Ibáñez, O. C. (2009). A Biologically Inspired Autonomous Robot Control Based on Behavioural Coordination in Evolutionary Robotics. In A. Porto Pazos, A. Pazos Sierra, & W. Buño Buceta (Eds.), Advancing Artificial Intelligence through Biological Process Applications (pp. 107-129). IGI Global. https://doi.org/10.4018/978-1-59904-996-0.ch007

Chicago

Fernández-León, José A., et al. "A Biologically Inspired Autonomous Robot Control Based on Behavioural Coordination in Evolutionary Robotics." In Advancing Artificial Intelligence through Biological Process Applications, edited by Ana B. Porto Pazos, Alejandro Pazos Sierra, and Washington Buño Buceta, 107-129. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-59904-996-0.ch007

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Abstract

This work is intended to give an overview of technologies, developed from an artificial intelligence standpoint, devised to face the different planning and control problems involved in trajectory generation for mobile robots. The purpose of this analysis is to give a current context to present the Evolutionary Robotics approach to the problem, which is now being considered as a feasible methodology to develop mobile robots for solving real life problems. This chapter also show the authors’ experiences on related case studies, which are briefly described (a fuzzy logic based path planner for a terrestrial mobile robot, and a knowledge-based system for desired trajectory generation in the Geosub underwater autonomous vehicle). The development of different behaviours within a path generator, built with Evolutionary Robotics concepts, is tested in a Khepera© robot and analyzed in detail. Finally, behaviour coordination based on the artificial immune system metaphor is evaluated for the same application.

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