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Algorithms 2009, 2(1), 398-409; doi:10.3390/a2010398
Article

A Sensor-Based Learning Algorithm for the Self-Organization of Robot Behavior

1, 2, 3,* , 1, 2,.3
, 4
 and 1, 2, 5
Received: 30 November 2008; Accepted: 26 February 2009 / Published: 4 March 2009
(This article belongs to the Special Issue Neural Networks and Sensors)
Download PDF [2618 KB, uploaded 13 March 2009]
Abstract: Ideally, sensory information forms the only source of information to a robot. We consider an algorithm for the self-organization of a controller. At short time scales the controller is merely reactive but the parameter dynamics and the acquisition of knowledge by an internal model lead to seemingly purposeful behavior on longer time scales. As a paradigmatic example, we study the simulation of an underactuated snake-like robot. By interacting with the real physical system formed by the robotic hardware and the environment, the controller achieves a sensitive and body-specific actuation of the robot.
Keywords: Self-Organization; Autonomous Robot Control; Neural Networks; Homeokinesis Self-Organization; Autonomous Robot Control; Neural Networks; Homeokinesis
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Hesse, F.; Martius, G.; Der, R.; Herrmann, J.M. A Sensor-Based Learning Algorithm for the Self-Organization of Robot Behavior. Algorithms 2009, 2, 398-409.

AMA Style

Hesse F, Martius G, Der R, Herrmann JM. A Sensor-Based Learning Algorithm for the Self-Organization of Robot Behavior. Algorithms. 2009; 2(1):398-409.

Chicago/Turabian Style

Hesse, Frank; Martius, Georg; Der, Ralf; Herrmann, J. Michael. 2009. "A Sensor-Based Learning Algorithm for the Self-Organization of Robot Behavior." Algorithms 2, no. 1: 398-409.

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