In this paper we report our experiments with the e-puck robots for developing a communication system using evolutionary robotics. In order to do the latter we follow the evolutionary approach by using Neural Networks and Genetic Algorithms. The robots develop a communication scheme for solving tasks like: locating food areas, avoiding obstacles, approaching light sources and locating sound-sources (other robots emitting sounds). Evorobot* and Webots simulators are used as tools for computing the evolutionary process and optimization of the weights of neural controllers. As a consequence, two different kinds of neural controllers emerge. On one hand, one controller is used for robot movement; on the other hand the second controller process sound signals. © 2011 Springer-Verlag.
CITATION STYLE
Montes-Gonzalez, F., & Aldana-Franco, F. (2011). The evolution of signal communication for the e-puck robot. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7094 LNAI, pp. 466–477). https://doi.org/10.1007/978-3-642-25324-9_40
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