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\chapter{Introduction}
Controlling and learning to control movements of a many degree of freedom system such as the human body is a non-trivial task. How does the central nervous system (CNS) choose from the infinitely many possibilities of how to achieve a certain movement? This problem is famously known as Bernstein's problem \cite{Bernstein1967}. Understanding how natural agents such as humans and animals control their movements is one of the fundamental questions in embodied artificial intelligence \cite{Pfeifer1999,Pfeifer2006}
Complex movements of humans (and other animals such as cats \cite{Torres-Oviedo2006}) are thought to develop based on a simple, rudimentary set of building blocks -- commonly called motor primitives or muscle synergies -- during ontogenetic development \cite{Flash2005, Hart2010}. These primitives are defined by the pattern of simultaneous activation of different muscles and are then combined in order to achieve a certain movement or pose.
Contrary to the hitherto belief that these innate simple reflexes get completely replaced by more complex ones with age, a recent publication by Dominici et al. \cite{Dominici2011} shows that certain basic patterns of muscle activation involved in biped walking are instead retained and are being built upon during development in order to achieve a variety of walking movement behaviors. The study measured EMG activity of 24 muscles (the same 12 muscles in each leg) simultaneously in neonates\footnote{Even though neonates of course can't walk by themselves, stepping can be evoked when they're being held upright and by gently pushing the infant along the pathway. However this behavior typically disappears 4 to 6 weeks after birth.} ($\sim{}3$ days old), toddlers (11-14 months old), preschoolers (22-48 months old) and adults (25-40 years old). Additionally foot pressure was recorded as well as the limb kinematics.
This project thesis attempts to investigate the role these locomotor primitives play in the development of human bipedal walking by building a musculoskeletal simulation model in the OpenSim software \cite{Delp2007} and then applying the basic activation patterns at different stages of human development (neonate, toddlers, preschooler and adults) identified by Dominici et al. \cite{Dominici2011} to it in order to achieve a walking behavior. Thereby we hope to understand the basis of the development of biped walking in order to possibly be applied to humanoid robots, especially anthropomimetic robots \cite{Wittmeier2013} which more closely mimic the internal structure of the human body with respect to muscles, tendons, bones and joints.
The basic process of developing the necessary components and finally reproducing the walking behavior will consist of the following distinct steps:
\begin{description}
\item[Single joint model] Implement a simple musculoskeletal model with one joint to get familiar with OpenSim. Actuate it using a reflex controller.
\item[Full two-legged model] Implement the full musculoskeletal model with two legs, fixed in space without ground forces. Actuate it using a simple reflex controller and pseudo-random data resembling the activation patterns from the study.
\item[Extract data and investigate walking] Extend the model to include the ground-contact forces accordingly. Extract the real activation pattern data from \cite{Dominici2011} and apply it to the model. Examine the walking behavior of the musculoskeletal model.
\end{description}
The remainder of this report is organized as follows: In chapter \ref{ch:methods}, the simulation software environment, the musculoskeletal model and the developed simulation controller are described. Furthermore the data preparation is explained. In chapter \ref{ch:results} the data produced and the simulation behaviors are presented. In chapter \ref{ch:discussion} the obtained results are discussed and the usability of the OpenSim environment for these kinds of experiments is evaluated. Finally in chapter \ref{ch:conclusion} some conclusions are drawn.
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