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The past decade has seen great progress in the development of adaptive, low-complexity, underactuated robot hands. An advantage of these hands is that they use under-constrained mechanisms and compliance, which facilitate grasping even under significant object pose uncertainties. However, for many minimal contact grasps such as precision fingertip grasps, these hands tend to move the object after a grasp is secured, to an equilibrium configuration determined by the elasticity of the mechanism and the contact forces exerted through the robot fingertips. In this paper, we present a methodology based on constrained optimization methods for deriving stable, minimal effort grasps for underactuated robot hands and compensating for post-contact, in-hand parasitic object motions. To do so, we compute the imposed object motions for different object shapes and sizes and we synthesize appropriate robot arm trajectories that eliminate them. The approach allows for the computation of these grasps and motions even for hands with complex, flexure-based, compliant members. The effectiveness of the proposed methods is validated using a redundant robot arm (Barrett WAM) and a two fingered, compliant, underactuated robot hand (Yale Open Hand model T42), for a series of simulated and experimental paradigms.
Liarokapis et al. (Mon,) studied this question.
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