<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>292</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>6</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2020-02-12</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Co-Development of an Infant Prototype in Hardware and  Simulation based on CT Imaging Data</title>
    <abstract language="eng">The development of biomimetic robots has gained research interest in  the last years as it may both help under-standing processes of motion execution in biological systems as well as developping a novel generation of intelligent and energy efficient robots. However, exact  model generation that builds up on observations and robot design is very time intensive. In this  paper we present a novel pipeline for  co-development of biomimetic hardware and simulation models based on biological Computer Tomography (CT) data. For this purpose we exploit State of the Art rapid prototyping technologies such as 3D Printing and the  Neurorobotics Platform for musculoskeletal simulations in virtual environments. The co-development  integrates both advantages of virtual and physical experimental models and is expected to increase development speed of controllers that can be tested on the  simulated  counterpart before application to a printed robot model. We demonstrate the  pipeline by  generating a one year old infant model as a musculoskeletal simulation model  and a print-in-place 3D printed skeleton as a single movable part. Even though we hereonly introduce the initial body generation and only a first testsetup for a modular sensory  and control framework, we can clearly spot advantages in terms of rapid model generation and highly biological related models. Engineering costs are reducedand models can be provided to a wide research community for controller testing in an early development phase.</abstract>
    <parentTitle language="eng">IEEE International Conference on Cyborg and Bionic Systems (CBS), 2019, Munich</parentTitle>
    <identifier type="url">http://mediatum.ub.tum.de/doc/1520042/985669104579.pdf</identifier>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Sebastian Dendorfer</author>
    <author>Benedikt Feldotto</author>
    <author>Blasius Walch</author>
    <author>Patrick Koch</author>
    <author>Alois Knoll</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Biomechanische Analyse</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Robotik</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Computertomographie</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>3D-Druck</value>
    </subject>
    <collection role="institutes" number="FAKMB">Fakultät Maschinenbau</collection>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="persons" number="dendorferlbm">Dendorfer, Sebastian (Prof. Dr.), Zeitschriftenbeiträge - Labor Biomechanik</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="institutes" number="">Labor Biomechanik (LBM)</collection>
  </doc>
</export-example>
