ROBUSTNESS OF GUIDED SELF-ORGANIZATION AGAINST SENSORIMOTOR DISRUPTIONS

Georg Martius ()
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Georg Martius: Max Planck Institute for Mathematics in the Sciences, Inselstr. 22, 04103 Leipzig, Germany

Advances in Complex Systems (ACS), 2013, vol. 16, issue 02n03, 1-21

Abstract: Self-organizing processes are crucial for the development of living beings. Practical applications in robots may benefit from the self-organization of behavior, e.g., to increase fault tolerance and enhance flexibility, provided that external goals can also be achieved. We present results on the guidance of self-organizing control by visual target stimuli and show a remarkable robustness to sensorimotor disruptions. In a proof of concept study an autonomous wheeled robot is learning an object finding and ball-pushing task from scratch within a few minutes in continuous domains. The robustness is demonstrated by the rapid recovery of the performance after severe changes of the sensor configuration.

Keywords: Autonomous robots; learning; guided self-organization; robustness; dynamical systems; self-modeling (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1142/S021952591350001X

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