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In short, the current exteroceptive sensory system of the CyberHand mimics specific features of the biological sensory system that from neurophysiological and behavioral studies seem to be crucial for human grasp-and-lift.
For a number of human grasps, the corresponding fingertip trajectories are modeled in time and space by fuzzy clustering and Takagi Sugeno (TS) modeling.
In this paper, we address the problem of recognition of human grasps for five-fingered robotic hands and industrial robots in the context of programming-by-demonstration.
The preferences consist of each sublayer reflecting the primitive preference similar to the conditional behaviors of humans for given objectives and their arrangements are adjusted by the heuristics of human grasping.
Eternal life is beyond human grasp.
In this paper, a system for transferring human grasping skills to a robot is presented.
In human grasping, choices are made on the use of hand-parts even before a grasp is realized.
Underactuated mechanisms allow the grasping of an object in a way that is closer to human grasping than can be achieved by independent actuation (Montambault and Gosselin 2001 ).
In the closing sections of her chapter on the nature of body (§162 4), she makes clear that since full knowledge of contingent truths is too complex for humans to grasp through rational intuition (IP §9), we need to turn to some other way of learning them.
While God's relationship to time is difficult or impossible for humans to grasp, the implications for the present discussion are significant.
Physiological aspects might be overlooked when applying pure robotic measures to analyze human grasps.
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