Toeard a formulation of the human grasping quality sense

Hershkovitz, Moshe; Tasch, U.; Teboulle, Marc

doi:10.1002/rob.4620120404

Cited by 18 publications

(22 citation statements)

References 16 publications

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“…Five cost functions f(F) were selected on the basis of intuition or their previous use in the prehension literature (e.g., Hershkovitz et al 1995Hershkovitz et al , 1997. All were convex except one (Sect.…”

Section: Methodsmentioning

confidence: 99%

“…We are unaware of any earlier study that incorporates F t into the objective function. Although f 1 explicitly addresses only external contact forces, this function has been proposed to be related to minimization of muscular effort (Hershkovitz et al 1995(Hershkovitz et al , 1997.…”

Section: Methodsmentioning

confidence: 99%

“…was introduced by Hershkovitz et al (1995Hershkovitz et al ( ,1997. The equation does not represent entropy as a physical variable but was rather derived from information theory to reflect the uniformity of the contact forces.…”

Section: Entropylike Function-mentioning

confidence: 99%

“…with respect to the robotics literature, which customarily formulates grasping optimization in terms of only F n and assumes that the F t are passive consequences of the mechanical properties of the effectors (e.g., Hershkovitz et al 1995). Additionally, the neural sensitivity of finger pad afferents to small strains has been well documented (e.g., Bremner et al 1991;McNulty et al 1999).…”

Section: Tissue Deformation Function-tissue Displacement Minimizationmentioning

confidence: 99%

“…The finding that tissue displacement minimization did not produce good agreement with experimental data is significant because the grasp-planning algorithms proposed in the robotics literature are concerned primarily with normal forces; tangential forces are passive consequences of the structural properties of the effectors (e.g., Hershkovitz et al 1995). Although tissue displacement minimization cannot explain the observed finger forces, perhaps more sophisticated models of the passive properties of the fingers could.…”

mentioning

confidence: 97%

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Prehension synergies during nonvertical grasping, II: Modeling and optimization

2004

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This study examines various optimization criteria as potential sources of constraints that eliminate (or at least reduce the degree of) mechanical redundancy in prehension. A model of nonvertical grasping mimicking the experimental conditions of Pataky et al. (current issue) was developed and numerically optimized. Several cost functions compared well with experimental data including energylike functions, entropylike functions, and a "motor command" function. A tissue deformation function failed to predict finger forces. In the prehension literature, the "safety margin" (SM) measure has been used to describe grasp quality. We demonstrate here that the SM is an inappropriate measure for nonvertical grasps. We introduce a new measure, the "generalized safety margin" (GSM), which reduces to the SM for vertical and two-digit grasps. It was found that a close-to-constant GSM accounts for many of the finger force patterns that are observed when grasping an object oriented arbitrarily with respect to the gravity field. It was hypothesized that, when determining finger forces, the CNS assumes that a grasped object is more slippery than it actually is. An "operative friction coefficient" of approximately 30% of the actual coefficient accounted for the offset between experimental and optimized data. The data suggest that the CNS utilizes an optimization strategy when coordinating finger forces during grasping.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Entropylike Function-mentioning

confidence: 99%

Section: Tissue Deformation Function-tissue Displacement Minimizationmentioning

confidence: 99%

mentioning

confidence: 97%

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Prehension synergies during nonvertical grasping, II: Modeling and optimization

2004

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Optimal grasping formulations that result in high quality and robust configurations

1998

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This study develops a mathematical formulation that addresses robust and high quality grasps. Grasping quality is obtained by minimizing the entropy of the finger normal forces, and robustness is attained by minimizing the effects perturbations in the finger contact locations have on grasping quality variations. Robustness and quality are two distinct yet interrelated mechanisms that affect the selection of finger contact locations when forming a grasping configuration. The mathematical formulation has two weighing factors that convey the relative importance of the robustness and the quality mechanisms. Computer simulations of two and three finger grasps demonstrate that the new formulation can select contact locations that result in optimal grasping configurations. The optimal conditions vary through the model weighing factors. Optimal grasps of four different objects are obtained when the user Ž . Ž . Ž . seeks i robust configurations, ii high quality grasps, and iii grasps for which robustness and quality are equal in importance. ᮊ

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Multi-Finger Prehension: Control of a Redundant Mechanical System

Latash

Zatsiorsky²

2009

Advances in Experimental Medicine and Biology

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The human hand has been a fascinating object of study for researchers in both biomechanics and motor control. Studies of human prehension have contributed significantly to the progress in addressing the famous problem of motor redundancy. After a brief review of the hand mechanics, we present results of recent studies that support a general view that the apparently redundant design of the hand is not a source of computational problems but a rich apparatus that allows performing a variety of tasks in a reliable and flexible way (the principle of abundance). Multi-digit synergies have been analyzed at two levels of a hypothetical hierarchy involved in the control of prehensile actions. At the upper level, forces and moments produced by the thumb and virtual finger (an imagined finger with a mechanical action equal to the combined mechanical action of all four fingers of the hand) co-vary to stabilize the gripping action and the orientation of the hand-held object. These results support the principle of superposition suggested earlier in robotics with respect to the control of artificial grippers. At the lower level of the hierarchy, forces and moments produced by individual fingers co-vary to stabilize the magnitude and direction of the force vector and the moment of force produced by the virtual finger. Adjustments to changes in task constraints (such as, for example, friction under individual digits) may be local and synergic. The latter reflect multi-digit prehension synergies and may be analyzed with the so-called chain effects: Sequences of relatively straightforward cause-effect links directly related to mechanical constraints leading to non-trivial strong co-variation between pairs of elemental variables. Analysis of grip force adjustments during motion of hand-held objects suggests that the central nervous system adjusts to gravitational and inertial loads differently. The human hand is a gold mine for researchers interested in the control of natural human movements.

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Toeard a formulation of the human grasping quality sense

Cited by 18 publications

References 16 publications

Prehension synergies during nonvertical grasping, II: Modeling and optimization

Prehension synergies during nonvertical grasping, II: Modeling and optimization

Optimal grasping formulations that result in high quality and robust configurations

Multi-Finger Prehension: Control of a Redundant Mechanical System

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