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   <dc:title>Optimal control prediction of dynamically consistent walking motions</dc:title>
   <dc:creator>Pallarès López, Roger</dc:creator>
   <dc:subject>Àrees temàtiques de la UPC::Enginyeria mecànica</dc:subject>
   <dc:subject>Predictive control</dc:subject>
   <dc:subject>Human locomotion</dc:subject>
   <dc:subject>Control predictiu</dc:subject>
   <dc:subject>Locomoció humana</dc:subject>
   <dcterms:abstract>The main objective of this bachelor thesis in Industrial Technology Engineering is to predict dynamically&#xd;
consistent walking motions from kinematic and dynamic measurements obtained at the&#xd;
UPC Biomechanics Laboratory. A healthy gait cycle is captured and foot-ground contact forces are&#xd;
measured. Then, in order to acquire the new motions, optimal control techniques are applied.&#xd;
The human body is modeled with a multibody system formed by rigid bodies. Concretely, a twodimensional&#xd;
simpli ed skeletal model focused on the lower extremity is used in this work. It is&#xd;
formed by a total of 12 rigid bodies (trunk, pelvis and leg segments) and it has 10 degrees of freedom.&#xd;
The inverse dynamic analysis is performed using OpenSim, a free software tool developed by&#xd;
Stanford University that is widely used by the scienti c community.&#xd;
The optimal control algorithm to obtain dynamically consistent walking motions from experimental&#xd;
data is implemented in MATLAB. Moreover, the software used to solve the optimal control problem&#xd;
is GPOPS-II, a general-purpose MATLAB-based software for solving multiple-phase optimal&#xd;
control problems, developed by the University of Florida. Parameters of GPOPS-II are changed to&#xd;
study the in&#xd;
uence on the solution. Then, di erent formulations are analyzed to assess convergence&#xd;
and similarity between the new motion and the captured one.&#xd;
During this report, all the processes involved in the analysis and the related theory are detailed,&#xd;
as well as the methodology used. Theoretical background is presented and complemented with&#xd;
examples of other works. The skeletal model used is described in detail. The process to export&#xd;
and obtain the experimental kinematics and dynamics using OpenSim is explained step by step.&#xd;
Optimal control theory and GPOPS-II working environment, which are employed as the tool to&#xd;
predict new motions, are also explained. And  nally, results are presented and discussed.&#xd;
This project is considered an initial study of optimal control techniques to predict human motion.&#xd;
Thereby, it allows to understand these techniques and gain knowledge about how they can be used&#xd;
in order to be applied, in the future, in more complex models.</dcterms:abstract>
   <dcterms:issued>2017-06-15</dcterms:issued>
   <dc:type>Bachelor thesis</dc:type>
   <dc:rights>http://creativecommons.org/licenses/by-nc-nd/3.0/es/</dc:rights>
   <dc:rights>Open Access</dc:rights>
   <dc:publisher>Universitat Politècnica de Catalunya</dc:publisher>
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