Motion Optimization for Musculoskeletal Dynamics: A Flatness-Based Polynomial Approach

A new approach for trajectory optimization of musculoskeletal dynamic models is introduced. The model combines rigid-body and muscle dynamics described with a Hill-type driven by neural control inputs. objective to find input state trajectories that are optimal respect minimum-effort meet constraints associated models. measure effort given the integral pairwise average forces agonist-antagonist muscles. concepts flat parameterization nonlinear systems sum-of-squares combined yield method eliminates numerous set present in collocation methods. With terminal equilibrium, reduces feasible linear program, recursive feasibility proof more general polynomial cases. methods article can be used as basis fast, efficient solvers hierarchical, receding-horizon schemes. Two simulation examples included illustrate proposed