Definition and force distribution of power grasps

Zhang, Y.; Gruver, W.A.

doi:10.1109/robot.1995.525469

Cited by 38 publications

(14 citation statements)

References 12 publications

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“…An approach for IF analysis, which allows subspace dimension calculation of controllable and uncontrollable parts of CFs and MFs was developed by Zhang and Gruver [15]. They classified grasps into three categories: power grasps, constrained motion grasps and free motion grasps [16].…”

Section: Introductionmentioning

confidence: 99%

“…As will be shown later, the virtual linkage model further incorporates virtual forces, i.e. physically implausible forces, while methods not generating such virtual forces have been presented by Zhang et al [15], [16] and by Yoshikawa and Nagai [12]. However, the approach of Zhang et al allows no direct calculation of CFs and MFs but rather the computation of controllable and uncontrollable parts.…”

Section: Introductionmentioning

confidence: 99%

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A new interaction force decomposition maximizing compensating forces under physical work constraints

Schmidts

Schneider²,

Kühne

et al. 2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A new interaction force decomposition maximizing compensating forces under physical work constraints

Schmidts

Schneider²,

Kühne

et al. 2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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“…Robotic grasping can be broadly categorized into two types: precision grasps, in which the fingertips are used to contact the object, and power grasps, where the palm and proximal finger links are used to envelop the object (Zhang and Gruver, 1995). While precision grasps allow for greater object manipulation, power grasps are superior in terms of restraining the object.…”

Section: Introductionmentioning

confidence: 99%

Spatial grasp synthesis for complex objects using model‐based simulation

Liu

Starr

Wood

et al. 2005

Industrial Robot: An International Journal

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Purpose -Selection of an effective grasp of a complex object using a multifingered gripper is a challenging problem because of the many possible grasp positions that are typically available. Design/methodology/approach -Given the geometrical description of the particular object feature to be grasped, all feasible grasps are performed in offline simulation using a geometrically accurate model of the desired gripper. The six-dimensional convex hull for each grasp is computed and archived. This convex hull indicates the span of forces and torques that the grasp can resist. When a grasp is needed the force/torque due to the total object weight is estimated and the best grasp is selected. The selected grasp has minimum peak contact force consistent with equilibrium. Findings -Experimental trials with several complex object show the method is capable of producing grasps which can support the object and resist external force/torque. Research limitations/implications -An accurate geometrical description of the feature to be grasped must be known in advance. This would typically be a cylindrical or prismatic portion of the object. Practical implications -There are many environments in which a dexterous multifingered gripper must be used due to the variety of objects which must be grasped. The results indicate that effective grasps can be selected for complex objects from a database of simulated grasps. Originality/value -The primary contribution of this paper is the use of a database of simulated grasps on simple graspable features to synthesize grasps on complex objects.

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“…The existence of uncontrollable grasp force is the main issue of the grasp force analyses in power grasps [3]- [5], [8], [9]. Bicchi first discussed this issue and decomposed the grasp force into controllable and uncontrollable ones [3]- [5].…”

Section: Introductionmentioning

confidence: 99%

“…Equations (3)-(8) can be written in matrix-vector form as (9) where is the composite contact force vector and is the shown at the bottom of the page.…”

Section: Introductionmentioning

confidence: 99%

Rigid body analysis of the indeterminate grasp force in power grasps

Omata

Nagata²

2000

IEEE Trans. Robot. Automat.

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This paper analyzes the indeterminate grasp force in power grasps with a rigid body model. A power grasp overconstrains an object with multiple contact points using the surfaces of finger links and palm. It is known that the overconstrained grasp results in the static indeterminacy of the grasp force. This paper shows that it also results in an infeasible combination of the sliding directions at the contact points. A static friction force acts only in the opposite direction of the trend of sliding. This characteristic of friction restricts the grasp force in power grasps although it is indeterminate. First, we show an example to illustrate the restriction on the grasp force. Then, we formulate it formally. This analysis leads to a special case where the grasp force is unique.

show abstract

Definition and force distribution of power grasps

Cited by 38 publications

References 12 publications

A new interaction force decomposition maximizing compensating forces under physical work constraints

A new interaction force decomposition maximizing compensating forces under physical work constraints

Spatial grasp synthesis for complex objects using model‐based simulation

Rigid body analysis of the indeterminate grasp force in power grasps

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