Abstract
In the field of visually guided grasping, humans still outshine their robotic counterparts with respect to accuracy, speed, robustness, and flexibility. We therefore examined current neuroscientific models for the control of human reach-to-grasp movements and, based on one of them, developed a novel visual motion control strategy. This control strategy was integrated into a complete hand-eye system, including modules for the determination of suitable 3D grasping positions on unknown objects from the images of a stereo camera system. The modules were implemented and tested on the experimental hand-eye system MINERVA.
The work presented in this paper was supported by the Deutsche Forschungsgemeinschaft as part of the Special Research Program “Sensorimotor — Analysis of Biological Systems, Modeling, and Medical-Technical Application” (SFB 462).
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Hauck, A., Passig, G., Rüttinger, J., Sorg, M., Färber, G. (2000). Biologically Motivated Hand-Eye Coordination for the Autonomous Grasping of Unknown Objects. In: Schmidt, G., Hanebeck, U., Freyberger, F. (eds) Autonome Mobile Systeme 1999. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59708-4_14
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DOI: https://doi.org/10.1007/978-3-642-59708-4_14
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