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

机译:生物动力模型,用于控制视觉引导的抓握运动

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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.
机译:在准确性,速度,鲁棒性和灵活性方面,人的抓取力仍比其机器人同行高。因此,在尝试开发机械手眼系统时,建议自己检查神经科学的结果。在本文中,我们描述了一种视觉引导的可抓握运动模型,该模型统一了“先走后走”和视觉伺服这两种机器人策略,从而弥补了每种策略单独使用时所表现出的问题。该模型是通过分析和扩展用于控制人类伸手抓紧运动的当前模型而开发的。

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