2 Does Torque Minimization Yield a Stable Human Grasp?

Baud-Bovy, Gabriel; Prattichizzo, Domenico; Brogi, Nadia

doi:10.1007/11429555_2

Cited by 14 publications

(5 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…More generally, the core idea of optimal control is that behavior reflects the optimum of some cost function (Todorov and Jordan, 2002; Todorov, 2004). In the context of grasping, this general framework has been used to explain both how a set of contact positions (Friedman and Flash, 2007; Lukos et al, 2007, 2008; Ciocarlie et al, 2009; Fu et al, 2010, 2011; Craje et al, 2011; Gilster et al, 2012) and contact forces (Hershkovitz et al, 1997; Chalfoun et al, 2004; Pataky et al, 2004; Baud-Bovy et al, 2005; Niu et al, 2009; Terekhov et al, 2010) are selected. However, a problem with this framework is that it does not explain how the optimal solution might be actually computed in a biologically plausible manner.…”

Section: Force Synergiesmentioning

confidence: 99%

Neural bases of hand synergies

Santello¹,

Baud-Bovy²,

Jörntell³

2013

Front. Comput. Neurosci.

Self Cite

218

190

View full text Add to dashboard Cite

The human hand has so many degrees of freedom that it may seem impossible to control. A potential solution to this problem is “synergy control” which combines dimensionality reduction with great flexibility. With applicability to a wide range of tasks, this has become a very popular concept. In this review, we describe the evolution of the modern concept using studies of kinematic and force synergies in human hand control, neurophysiology of cortical and spinal neurons, and electromyographic (EMG) activity of hand muscles. We go beyond the often purely descriptive usage of synergy by reviewing the organization of the underlying neuronal circuitry in order to propose mechanistic explanations for various observed synergy phenomena. Finally, we propose a theoretical framework to reconcile important and still debated concepts such as the definitions of “fixed” vs. “flexible” synergies and mechanisms underlying the combination of synergies for hand control.

show abstract

Section: Force Synergiesmentioning

confidence: 99%

Neural bases of hand synergies

Santello¹,

Baud-Bovy²,

Jörntell³

2013

Front. Comput. Neurosci.

Self Cite

218

190

View full text Add to dashboard Cite

show abstract

“…Since the pioneering study of Nubar and Contini (1961) the main idea behind the employed cost functions was that a certain measure of muscular effort is minimized, e.g. the sum of squared muscle moments of force (Nubar, Contini 1961), the weighted norm of the joint torque vector (Baud-Bovy et al 2005); the sum of the cubed muscle stresses (Crowninshield 1978; Stokes, Gardner-Morse 2001), ‘global muscular effort’, i.e. the sum of squared values of the muscle forces normalized with respect to their maximal magnitudes (Chalfoun et.…”

Section: Introductionmentioning

confidence: 99%

Effects of grasping force magnitude on the coordination of digit forces in multi-finger prehension

2009

View full text Add to dashboard Cite

The study addresses three main questions: (1) Does the magnitude of the grasping force affect the prehension synergies, i.e. conjoint changes of finger forces and moments? (2) Do individual finger forces scale with the total grasping forces ('scale-invariance hypothesis')? (3) How specification of the grasping force magnitude affects the inverse optimization of digit forces. Subjects (n=7) grasped with minimal force an instrumented handle and maintained it at rest in the air. Then, the subjects doubled the initial grasping force. The forces and moments exerted by individual digits were recorded with 6-component sensors. External torques that the subjects should resist (9 in total) varied among the trials from zero to 0.46 Nm both in clockwise and counterclockwise directions. After the force doubling, the moments of the normal forces (M n ) increased in the pronation effort tasks (PR-tasks) and decreased in the supination effort tasks (SU-tasks). The changes in the moments of the tangential forces (M t ) were opposite to the M n changes; the moments increased in the SU-tasks and decreased in the PR-tasks. The opposite effects of force doubling on the M t s in the SU-tasks and PR-tasks were a consequence of the unidirectional changes of the thumb tangential forces: in all the tasks the contribution of the thumb tangential force to the total tangential force increased after the grasping force doubling (and the total contribution of the four fingers decreased). The decrease of the virtual finger (VF) tangential force was mainly due to the decrease of the index finger force (VF is an imagined finger that exerts the same force and moment as all the fingers together). In the non-zero torque tasks the individual finger forces did not scale proportionally with the grasping force, the sharing percentage of the individual finger forces in the VF normal force changed with the grasping force increase. The root mean square (RMS) differences between the actual finger sharing percentages in the VF force and the sharing percentages predicted from optimization procedures in which different cost functions were used were in all cases smaller after the doubling than before the doubling. Hence the answers to the three questions formulated above are: (1) the alteration of the grasping force magnitude induces complex coordinated changes of all digit forces and moments; (2) the scale invariance hypothesis is confirmed only for the zero-torque tasks and rejected for the nonzero tasks, and (3) the specification of the grasping force magnitude at the level of twice the initial grasping force -which essentially restricts the control task to the object tilt prevention-improves the accuracy of the employed optimization procedures.

show abstract

“…Future work can use this framework to study this question, as well as to investigate whether people grasp objects in an optimal manner, for example, extending schemes such as that in Baud-Bovy et al [36] to include a more accurate model of constraints on muscle forces. Another way this work can be extended is to synthesize optimal grasps when the task requirement is given and the optimal contact points on an object are computed by anatomically-based quality measures.…”

Section: Discussionmentioning

confidence: 99%

On the Importance of Asymmetries in Grasp Quality Metrics for Tendon Driven Hands

Pollard

2006

2006 IEEE/RSJ International Conference on Intelligent Robots and Systems

View full text Add to dashboard Cite

Abstract-Grasp quality measures are important for understanding how to plan for and maintain appropriate and secure grasps for pick and place operations and tool use. Most grasp quality measures assume certain symmetries about the mechanism or the task. For example, contact points may be considered to be independent and identical, or an ellipsoidal measure such as the force manipulability ellipsoid may be used. However, many tasks have strong asymmetries, where wrenches in certain directions dominate. Tendon driven hand designs may also have strong asymmetries, leading to differing abilities to apply contact forces in different directions. This paper begins to explore empirically the validity of some of the symmetry assumptions employed by common grasp quality metrics. We examine the human hand and the Shadow Robot Hand, and find that force abilities vary with finger choice and with location of the contact on the finger for both hands. However, while the human hand shows dramatic changes for different poses due to its asymmetric design, the Shadow hand, with a symmetric design shows much smaller changes and resembles the assumption of identical and independent contact points reasonably well. Thus, we suggest that the underlying design of the hand is a very important factor to consider for grasp quality metrics and for grasp planning and control. The specific grasp quality metric we study in this paper also brings together a variety of previous research. We outline a linear programming approach for computing a grasp quality metric that includes tendon force constraints and contact constraints and can handle any task described as a polytope in wrench space.

show abstract

2 Does Torque Minimization Yield a Stable Human Grasp?

Cited by 14 publications

References 37 publications

Neural bases of hand synergies

Neural bases of hand synergies

Effects of grasping force magnitude on the coordination of digit forces in multi-finger prehension

On the Importance of Asymmetries in Grasp Quality Metrics for Tendon Driven Hands

Contact Info

Product

Resources

About