A simplified MMC model for the control of an arm with redundant degrees of freedom

Steinkühler, Ulrich; Beyn, Wolf–Jürgen; Cruse, Holk

doi:10.1007/bf02279932

Cited by 2 publications

(1 citation statement)

References 3 publications

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“…For instance, the model presented in a series of papers [49,50,51] implements feedback dynamics based on the mean value of multiple computations (MMC, fifth row in Tab. 2.1).…”

Section: Recover Invertibility By Augmenting the Inverse Problemmentioning

confidence: 99%

Reservoir Computing with Output Feedback

Reinhart¹

2012

Künstl Intell

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-Reservoir Computing with Output Feedback René Felix ReinhartA dynamical system approach to forward and inverse modeling is proposed. Forward and inverse models are trained in associative recurrent neural networks that are based on non-linear random projections. Feedback of estimated outputs into such reservoir networks is a key ingredient in the context of bidirectional association but entails the problem of error amplification. Robust training of reservoir networks with output feedback is achieved by a novel one-shot learning and regularization method for input-driven recurrent neural networks. It is shown that output feedback enables the implementation of ambiguous inverse models by means of multi-stable dynamics. The proposed methodology is applied to movement generation of robotic manipulators in a feedforward-feedback control framework.

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“…For instance, the model presented in a series of papers [49,50,51] implements feedback dynamics based on the mean value of multiple computations (MMC, fifth row in Tab. 2.1).…”

Section: Recover Invertibility By Augmenting the Inverse Problemmentioning

confidence: 99%

Reservoir Computing with Output Feedback

Reinhart¹

2012

Künstl Intell

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A holistic model for an internal representation to control the movement of a manipulator with redundant degrees of freedom

Steinkühler

Cruse

1998

Biological Cybernetics

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The paper proposes a model for the control of a multisegmented manipulator with redundant degrees of freedom. On the basis of an earlier model, the socalled MMC net, a simpli®ed version is proposed here which has several advantages. First, it can easily be scaled up for the 3D case. Second, for the linear version a complete convergence proof is possible. Third, an easy way of implementing a damping parameter is shown. Fourth, the properties of the earlier model are unchanged, namely versatile control of the redundant system, immediate change from direct kinematics to inverse kinematics or any mixed control task, as well as robustness in the case of singularities.

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A simplified MMC model for the control of an arm with redundant degrees of freedom

Cited by 2 publications

References 3 publications

Reservoir Computing with Output Feedback

Reservoir Computing with Output Feedback

A holistic model for an internal representation to control the movement of a manipulator with redundant degrees of freedom

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