Abstract
In this paper, we show how a simulated anthropomorphic robotic arm controlled by an artificial neural network can develop effective reaching and grasping behaviour through a trial and error process in which the free parameters encode the control rules which regulate the fine-grained interaction between the robot and the environment and variations of the free parameters are retained or discarded on the basis of their effects at the level of the global behaviour exhibited by the robot situated in the environment. The obtained results demonstrate how the proposed methodology allows the robot to produce effective behaviours thanks to its ability to exploit the morphological properties of the robot's body (i.e. its anthropomorphic shape, the elastic properties of its muscle-like actuators and the compliance of its actuated joints) and the properties which arise from the physical interaction between the robot and the environment mediated by appropriate control rules.
DOI
10.3389/neuro.12.004.2007
Publication Date
2007-01-01
Publication Title
Frontiers in Neurorobotics
Volume
1
Publisher
Frontiers Media SA
ISSN
1662-5218
Embargo Period
2024-11-22
Recommended Citation
Massera, G. (2007) 'Evolution of prehension ability in an anthropomorphic neurorobotic arm', Frontiers in Neurorobotics, 1. Frontiers Media SA: Available at: https://doi.org/10.3389/neuro.12.004.2007
