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

2009

Article

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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 timescales 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 timescales. 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.

@article{hesse:sensorbased09,
  title = {A Sensor-Based Learning Algorithm for the Self-Organization of Robot Behavior},
  author = {Hesse, Frank and Martius, Georg and Der, Ralf and Herrmann, J. Michael},
  journal = {Algorithms},
  volume = {2},
  number = {1},
  pages = {398-409},
  year = {2009},
  doi = {},
  url = {http://www.mdpi.com/1999-4893/2/1/398}
}