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2003
Springer

Evolving the Neural Controller for a Robotic Arm Able to Grasp Objects on the Basis of Tactile Sensors

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Evolving the Neural Controller for a Robotic Arm Able to Grasp Objects on the Basis of Tactile Sensors
We describe the results of a set of evolutionary experiments in which a simulated robotic arm provided with a two-fingered hand has to reach and grasp objects with different shapes and orientations on the basis of simple tactile information. Obtained results are rather encouraging and demonstrate that the problem of grasping objects with characteristics that vary within a certain range can be solved by producing rather simple forms of behaviour. These forms of behaviour exploit emergent characteristics of the interaction between the body of the robot, its control system and the environment. In particular we show that evolved individuals do not try to keep the environment stable but on the contrary push and pull the objects thus producing a dynamic in the environment and exploit the interaction between the body of the robot and the dynamic environment to master different environmental conditions with similar control strategies.
Raffaele Bianco, Stefano Nolfi
Added 06 Jul 2010
Updated 06 Jul 2010
Type Conference
Year 2003
Where AIIA
Authors Raffaele Bianco, Stefano Nolfi
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