Behavioral control through evolutionary neurocontrollers for autonomous mobile robot navigation

Fernandez-Leon, Jose A, Acosta, Gerardo G and Mayosk, Miguel A (2009) Behavioral control through evolutionary neurocontrollers for autonomous mobile robot navigation. Robotics and Autonomous Systems, 57 (4). pp. 411-419. ISSN 09218890

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This paper deals with the study of scaling up behaviors in evolutive robotics (ER). Complex behaviors were obtained from simple ones. Each behavior is supported by an artificial neural network (ANN)-based controller or neurocontroller. Hence, a method for the generation of a hierarchy of neurocontrollers, resorting to the paradigm of Layered Evolution (LE), is developed and verified experimentally through computer simulations and tests in a Khepera® micro-robot. Several behavioral modules are initially evolved using specialized neurocontrollers based on different ANN paradigms. The results show that simple behaviors coordination through LE is a feasible strategy that gives rise to emergent complex behaviors. These complex behaviors can then solve real-world problems efficiently. From a pure evolutionary perspective, however, the methodology presented is too much dependent on user’s prior knowledge about the problem to solve and also that evolution take place in a rigid, prescribed framework. Mobile robot’s navigation in an unknown environment is used as a test bed for the proposed scaling strategies.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Informatics
Depositing User: Jose A. FernandezLeon
Date Deposited: 20 Feb 2012 16:56
Last Modified: 14 Jun 2012 12:34
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