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Human Motion Planning Based on Recursive Dynamics and Optimal Control Techniques

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Abstract

This paper presents an efficient optimal control and recursive dynamics-based computer animation system for simulating and controlling themotion of articulated figures. A quasi-Newton nonlinear programmingtechnique (super-linear convergence) is implemented to solve minimumtorque-based human motion-planning problems. The explicit analyticalgradients needed in the dynamics are derived using a matrix exponentialformulation and Lie algebra. Cubic spline functions are used to make thesearch space for an optimal solution finite. Based on our formulations,our method is well conditioned and robust, in addition to beingcomputationally efficient. To better illustrate the efficiency of ourmethod, we present results of natural looking and physically correcthuman motions for a variety of human motion tasks involving open andclosed loop kinematic chains.

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Authors and Affiliations

  1. Department of Computer and Information Science, School of Engineering and Applied Sciences, University of Pennsylvania, 200 South 33rd St., Philadelphia, PA, 19104, U.S.A

    Janzen Lo, Gang Huang & Dimitris Metaxas

Authors
  1. Janzen Lo
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  2. Gang Huang
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  3. Dimitris Metaxas
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Lo, J., Huang, G. & Metaxas, D. Human Motion Planning Based on Recursive Dynamics and Optimal Control Techniques. Multibody System Dynamics 8, 433–458 (2002). https://doi.org/10.1023/A:1021111421247

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