The human arm as a redundant manipulator: The control of path and joint angles

Cruse, Holk; Brüwer, M.

doi:10.1007/bf00318723

Cited by 190 publications

(48 citation statements)

References 9 publications

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“…The aim of the current investigation was to look for measurable values corresponding to the hypothetical cost functions which were postulated earlier for the control of the redundant arm (Cruse 1986;Cruse and Briiwer 1987). The first question investigated was whether the choice of the arm position depends solely on the values of the joint angles or also on the length of the limbs.…”

Section: Discussionmentioning

confidence: 99%

“…As described in two earlier papers (Cruse 1986, Cruse andBriiwer 1987), the movement of the arm is restricted to the horizontal plane and the three joints at shoulder, elbow and wrist are free to move. To measure the values of the joint angles the arm of the subject was laid on an artificial arm having three joints which was free to glide over a horizontal plane.…”

Section: Methodsmentioning

confidence: 99%

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On the cost functions for the control of the human arm movement

et al. 1990

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Abstract. The aim of our investigation is to understand the mechanisms which control the movement of the human arm. The arm is here considered as a redundant system: the shoulder, elbow and wrist joints, which provide three degrees of freedom, combine to move the hand in a horizontal plane, i.e. a two dimensional space. Thus the system has one extra degree of freedom. Earlier investigations of the static situation led to the hypothesis that independent cost functions were attached to each of the three joints and that the configuration chosen for a given target position is that which provides the minimum total cost (Cruse 1986). The aim of the current investigation was to look for measurable values corresponding to the hypothetical cost functions. Experiments using pointers of different lengths attached to the hand showed that the strategy in choosing the joint angles are independent of the limb length. The muscle force necessary to reach a given angle is increased by a spring mounted across a joint. In this situation the angles of the loaded joint are changed for a given target point to give way to the force effect. This leads to the conclusion that the hypothetical cost functions are not independent of the physiological costs necessary to hold the joint at a given angle. The cost functions seem to depend on joint angle and on the force which is necessary to hold the joint in a given position. Cost functions are measured by psychophysical methods. The results show U-shaped curves which can be approximated by parabolas. The position of minimum cost (maximum comfort) for one joint showed no or weak dependency on the angles of the other joints. For each subject these "psychophysical" cost functions are compared with the hypothetical cost functions. The comparison showed reasonable agreement. This supports the assumption that the psychophysically measured "comfort functions" provide a measure for the hypothetical cost functions postulated to explain the targeting movements. Targeting experiments using a four joint arm which has two extra degrees of freedom showed a much larger scatter compared to the three joint arm. Nevertheless, the results still conform to the hypothesis that also in this case the minimum cost principle is applied to solve the redundancy problem. As the cost function for the whole arm shows a large minimum valley, quite a large range of arm positions is possible of about equal total costs. The scatter does not result from pure randomness but seems to be mainly produced by the fact that the angles at the end of the movement depend on the value of the joint angles at the beginning of the movement.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

On the cost functions for the control of the human arm movement

et al. 1990

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“…However, it predicts a bimodal velocity profile which is at odds with the experimental data (Atkeson and Hollerbach 1985). Later it was suggested that the hand trajectory is the result of a compromise between planning a straight line in the task space and planning a straight line in the joint space (Cruse and Brüwer 1987;Okadome and Honda 1999;Hersch and Billard 2007). Such hybrid computations offer numerous advantages for controlling 3-dimensional reaching movements, such as avoiding singularities and avoiding hitting the joint limits (Hersch and Billard 2007).…”

Section: Computational Approachmentioning

confidence: 99%

Movement curvature planning through force field internal models

Petreska

Billard

2009

Biol Cybern

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Human motion studies have focused primarily on modeling straight point-to-point reaching movements. However, many goal-directed reaching movements, such as movements directed towards oneself, are not straight but rather follow highly curved trajectories. These movements are particularly interesting to study since they are essential in our everyday life, appear early in development and are routinely used to assess movement deficits following brain lesions. We argue that curved and straight-line reaching movements are generated by a unique neural controller and that the observed curvature of the movement is the result of an active control strategy that follows the geometry of one's body, for instance to avoid trajectories that would hit the body or yield postures close to the joint limits. We present a mathematical model that accounts for such an active control strategy and show that the model reproduces with high accuracy the kinematic features of human data during unconstrained reaching movements directed toward the head. The model consists of a nonlinear dynamical system with a single stable attractor at the target. Embodiment-related task constraints are expressed as a force field that acts on the dynamical system. Finally, we discuss the biological plausibility and neural correlates of the model's parameters and suggest that embodiment should be considered as a main cause for movement trajectory curvature.

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“…Various authors proposed more objective measures including specific limitations of motions (Van Thiel, et al 1999, Kawato 1996, Kawato and Wolpert 1998, Uno, et al 1989, Bruwer 1987 andCruse 1990) on which impairment is often largely based (e.g., AMA Guides to the Evaluation of Permanent Impairment [AMA 1997]). The reader is also referred to the recent comparison of commercially available measuring systems (Richards 1998).…”

Section: Introductionmentioning

confidence: 99%

Towards Understanding the Workspace of the Upper Extremities

Abdel‐Malek¹,

Yang²,

Brand³

et al. 2001

SAE Technical Paper Series

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Significant attention in recent years has been given towards obtaining a better understanding of human joint ranges, measurement, and functionality, especially in conjunction with commands issued by the central nervous system. Studies of those commands often include computer algorithms to describe path trajectories. These are typically in "open-form" with specific descriptions of motions, but not "closed form" mathematical solutions of the full range of possibilities. This paper proposes a rigorous "closed form" kinematic formulation to model human limbs, understand their workspace, and delineate barriers therein where a path becomes difficult or impossible owing to physical constraints. The novel ability to visualize barriers in the workspace emphasizes the power of these closed form equations. Moreover, this formulation takes into account joint limits in terms of ranges of motion. Examples include the workspaces of a typical forearm, a typical finger, and is used to illustrate the visualization of the progress in the functionality of a wrist undergoing rehabilitation.

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The human arm as a redundant manipulator: The control of path and joint angles

Cited by 190 publications

References 9 publications

On the cost functions for the control of the human arm movement

On the cost functions for the control of the human arm movement

Movement curvature planning through force field internal models

Towards Understanding the Workspace of the Upper Extremities

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