A biologically motivated model for the control of visually guided reach-to-grasp movements

Abstract

Human grasping still outshines its robotical counterparts with respect to accuracy, speed, robustness, and flexibility. When trying to develop a robotical hand-eye system, it therefore suggests itself to examine the results of neuroscience. In this paper, we describe a model for visually guided reach-to-grasp movements that unifies the two robotical strategies look-then-move and visual servoing, thereby compensating the problems that each strategy shows when used alone. This model was developed by analyzing and extending current models for the control of human reach-to-grasp movements.