Dealing with constraints: a biomechanical approach

Russell, Donald; Hogan, Neville

doi:10.1109/iembs.1989.96034

Cited by 18 publications

(19 citation statements)

References 2 publications

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“…12 and 16b), although the simulated hand forces using (39) are higher than those using (37). This is in agreement with the findings of Russell and Hogan (1989).…”

Section: Combined Criterion With Muscle Modelsupporting

confidence: 95%

“…Figure 3f shows the hand force profile in the task space. These graphs show that the subjects use significant radial forces, in agreement with the findings of Russell and Hogan (1989).…”

Section: Crank-rotation Experimentssupporting

confidence: 90%

“…The experiments of Russell and Hogan (1989), in which human subjects turned a frictionally loaded crank, show that significant radial forces (compressing or extending the crank) are exerted despite the fact that these forces are not necessary to perform the task. The presence of these ineffective forces does not violate the smoothness of velocity profiles.…”

Section: Introductionmentioning

confidence: 98%

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Optimal trajectory formation of constrained human arm reaching movements

Ohta

Svinin²,

Zhang³

et al. 2004

Biol. Cybern.

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Opening a door, turning a steering wheel, and rotating a coffee mill are typical examples of human movements that are constrained by the physical environment. The constraints decrease the mobility of the human arm and lead to redundancy in the distribution of actuator forces (either joint torques or muscle forces). Due to this actuator redundancy, there is an infinite number of ways to form a specific arm trajectory. However, humans form trajectories in a unique way. How do humans resolve the redundancy of the constrained motions and specify the hand trajectory? To investigate this problem, we examine human arm movements in a crank-rotation task. To explain the trajectory formation in constrained point-to-point motions, we propose a combined criterion minimizing the hand contact force change and the actuating force change over the course of movement. Our experiments show a close matching between predicted and experimental data.

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“…12 and 16b), although the simulated hand forces using (39) are higher than those using (37). This is in agreement with the findings of Russell and Hogan (1989).…”

Section: Combined Criterion With Muscle Modelsupporting

confidence: 95%

“…Figure 3f shows the hand force profile in the task space. These graphs show that the subjects use significant radial forces, in agreement with the findings of Russell and Hogan (1989).…”

Section: Crank-rotation Experimentssupporting

confidence: 90%

Section: Introductionmentioning

confidence: 98%

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Optimal trajectory formation of constrained human arm reaching movements

Ohta

Svinin²,

Zhang³

et al. 2004

Biol. Cybern.

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“…Franklin and Milner (2003) used a manipulandum to generate arbitrary constraints while the manipulandum was moved by a human subject. Other studies used a physical crank and performed force measurements in the handle while the human subject turned the crank (Ohta et al 2004;Russel and Hogan 1989). As the human arm has redundant degrees of freedom (Bernstein 1967), the experiments were designed such that the movement complexity was reduced to that of a planar manipulator where shoulder and elbow joint were regarded as the first and second hinge joint.…”

Section: Discussionmentioning

confidence: 99%

Winching up heavy loads with a compliant arm: a new local joint controller

2008

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A closed kinematic chain, like an arm that operates a crank, has a constrained movement space. A meaningful movement of the chain's endpoint is only possible along the free movement directions which are given implicitly by the contour of the object that confines the movement of the chain. Many technical solutions for such a movement task, in particular those used in robotics, use central controllers and force-torque sensors in the arm's wrist or a leg's ankle to construct a coordinate system (task frame formalism) at the local point of contact the axes of which coincide with the free and constrained movement directions. Motivated by examples from biology, we introduce a new control system that solves a constrained movement task. The control system is inspired by the control architecture that is found in stick insects like Carausius morosus. It consists of decentral joint controllers that work on elastic joints (compliant manipulator). The decentral controllers are based on local positive velocity feedback (LPVF). It has been shown earlier that LPVF enables contour following of a limb in a compliant motion task without a central controller. In this paper we extend LPVF in such a way that it is even able to follow a contour if a considerable counter force drags the limb away along the contour in a direction opposite to the desired. The controller extension is based on the measurement of the local mechanical power generated in the elastic joint and is called power-controlled relaxation LPVF. The new control approach has the following advantages. First, it still uses local joint controllers without knowledge of the kinematics. Second, it does not need a force or torque measurement at the end of the limb. In this paper we test power-controlled relaxation LPVF on a crank turning task in which a weight has to be winched up by a two-joint compliant manipulator.

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“…Other previous work on partially constrained arm motion includes work examining how subjects turn a crank (Russell and Hogan [7]; Svinin et al [8]). Russell and Hogan showed that people apply significant radial forces (compressing or extending the crank) even though they are workless.…”

Section: B Related Workmentioning

confidence: 99%

Static single-arm force generation with kinematic constraints

Pan

Lynch

Peshkin

et al. 2004

IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004

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Abstract-This study investigates natural single-arm interaction with kinematic constraints. Smooth, frictionless, kinematic constraints reduce the degrees-of-freedom of motion at the hand, but add force freedoms. These force freedoms allow the hand to push and pull against the constraints with no effect on the task. Understanding how subjects take advantage of kinematic constraints will be useful in designing constraint surfaces for assisted manipulation.This paper reports the results of an experiment studying how subjects make use of the presence of a kinematic constraint in a static planar single-arm task. Subjects are asked to hold a handle that is free to slide on a linear rail, and to apply a force tangent to the rail to resist a pulling force. Thus the goal of the task is to hold the handle stationary. Subjects are also free to apply any force normal to the rail, as these forces have no effect on the task. This freedom does not exist without a kinematic constraint.We find that subjects make use of the force freedom by applying significant forces against the constraint in a consistent and constraint-configuration-dependent fashion. We show that the constraint forces can be predicted by a convex, scale-invariant objective function on the hand force space. The level curves of this objective function can be found directly from the experimental data without any biomechanical modeling.

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Dealing with constraints: a biomechanical approach

Cited by 18 publications

References 2 publications

Optimal trajectory formation of constrained human arm reaching movements

Optimal trajectory formation of constrained human arm reaching movements

Winching up heavy loads with a compliant arm: a new local joint controller

Static single-arm force generation with kinematic constraints

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