Simulation data of optimal control problems - Comparison of free-floating base and full-body dynamics for Trampoline Miller acrobatic

Published: 27 April 2022| Version 2 | DOI: 10.17632/rz8t786st8.2
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Description

These folders contain the results of optimal control problems that predicts the motion of a trampoline Miller. It investigates the effect of equations of motion and optimal control problems formulations (explicit and implicit) to solve trampoline Miller optimal control problems with direct multiple shooting using Bioptim software. The performance of each OCP formulation and equation of motion is assessed through computational time, dynamic consistency, and cost function values. Simulation data refers to the 100 simulations per optimal control problem (OCP) investigated with a different initial guess: Explicit formulation of the OCP with full-body dynamics, Explicit formulation of the OCP with free-floating base dynamics, Implicit formulation of the OCP with full-body dynamics, Implicit formulation of the OCP with free-floating base dynamics, Implicit formulation of the OCP with full-body dynamics and generalized accelerations as states and jerks as controls, and Implicit formulation of the OCP with free-floating base dynamics and generalized accelerations as states and jerks as controls "Effect of mesh points" refers to the 30 simulations per OCP investigated with a different initial guess while increasing the density of mesh points from 150 to 840. The implicit formulations were only considered: Implicit formulation of the OCP with full-body dynamics, Implicit formulation of the OCP with free-floating base dynamics, Implicit formulation of the OCP with full-body dynamics and generalized accelerations as states and jerks as controls, and Implicit formulation of the OCP with free-floating base dynamics and generalized accelerations as states and jerks as controls. Zip folders contain the raw data from each simulation in two formats, namely .pkl (python) and .bo (bioptim) and DataFrame Pickle files contain a pandas Dataframe which summarizes all the parameters and results of each simulation. The code to process the data is available on the following repository: https://github.com/Ipuch/OnDynamicsForSommersaults/

Files

Steps to reproduce

Code to reproduce the data is available in the script of the following repository: https://github.com/Ipuch/OnDynamicsForSommersaults

Institutions

Universite de Montreal

Categories

Computational Biomechanics, Optimal Control Theory, Biomechanics of Motion

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