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Motion Optimization for Musculoskeletal Dynamics A Flatness-Based Polynomial Approach

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Document pages: 8 pages

Abstract: A new approach for trajectory optimization of musculoskeletal dynamic modelsis introduced. The model combines rigid body and muscle dynamics described witha Hill-type model driven by neural control inputs. The objective is to findinput and state trajectories which are optimal with respect to a minimum-effortobjective and meet constraints associated with musculoskeletal models. Themeasure of effort is given by the integral of pairwise average forces of theagonist-antagonist muscles. The concepts of flat parameterization of nonlinearsystems and sum-of-squares optimization are combined to yield a method thateliminates the numerous set of dynamic constraints present in collocationmethods. With terminal equilibrium, optimization reduces to a feasible linearprogram, and a recursive feasibility proof is given for more general polynomialoptimization cases. The methods of the paper can be used as a basis for fastand efficient solvers for hierarchical and receding-horizon control schemes.Two simulation examples are included to illustrate the proposed methods

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