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

Frank Hesse, Georg Martius, Ralf Der, J. Michael Herrmann

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

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.
Original languageEnglish
Pages (from-to)398-409
Number of pages12
JournalAlgorithms
Volume2
Issue number1
DOIs
Publication statusPublished - 2009

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