Amarsi Benchmark Framework

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<opendatametainfo>

  <title>Amarsi Benchmark Framework</title>

  <organisation>

        <name>CITEC -- Center of Excellence Cognitive Interaction Technology, Bielefeld University</name>

        <url>http://cit-ec.de</url>

  </organisation>

  <description>

    This benchmark framework evaluates the performance of reaching motion generation approaches.The performance of these approaches is evaluated on a wide range of performance measures and typical tasks in robotics. The evaluation in this open source MATLAB software framework is done in the context of a default training data-set of human motions, which specifies the ground truth in the comparisons. The systematic comparisons allow to identify strengths and weaknesses of competing approaches and statistical evaluation of generalization and robustness. Robustness is tested by a chosen set of perturbation scenarios, which will interfere with the motion generation. 

  </description>

  <projects>

        <project>

          <name>AMARSi</name>

          <url>http://www.amarsi-project.eu/</url>

          <description>

             Motor skills of humans and animals are still utterly astonishing when compared to robots. AMARSi aims at a qualitative jump in robotic motor skills towards biological richness. AMARSi' objective: the experimentation and demonstration of rich motor skills on the iCub humanoid robot and on the quadruped Oncilla. Rich motor skills in robots will have a tremendous impact on our society. Dexterous and skillful motion in robots will make them more suitable for a large number of tasks. The compliant and natural movements will make them blend into everyday routines, safe and psychologically acceptable.

          </description>

        </project>

  </projects>

  <version>v1.0.0</version>

  <date>2014-07-09</date>

  <creators>

        <creator>

          <name>Andre Lemme</name>

          <url>http://www.cit-ec.de/users/alemme</url>

        </creator>

        <creator>

          <name>Mohammad Khansari-Zadeh</name>

        </creator>

  </creators>

  <contributors>

    <contributor>

      <name>Yaron Meirovitch</name>

    </contributor>

    <contributor>

      <name>Sebastien Gay</name>

    </contributor>

  </contributors>

  <downloadurls>

        <downloadurl>http://openresearch.cit-ec.de/attachments/download/268/AMRASiReachingBenchmark_v1.0.0.zip</downloadurl>

  </downloadurls>

  <license>

        Amarsi Benchmark Framework: Copyright(c) 2014 Andre Lemme, Mohammad Khansari-Zadeh, Yaron Meirovitch, Sebastien Gay http://opensource.cit-ec.de/amarsi . This software may be licensed under the terms of the GNU Lesser General Public License Version 3 (the ``LGPL''), or (at your option) any later version. Software distributed under the License is distributed on an ``AS IS'' basis, WITHOUT WARRANTY OF ANY KIND, either express or implied. See the LGPL for the specific language governing rights and limitations. You should have received a copy of the LGPL along with this program. If not, go to http://www.gnu.org/licenses/lgpl.html or write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. 

  </license>

  <keywords>

    <keyword>movement primitive</keyword>

    <keyword>benchmark</keyword>

    <keyword>comparisons</keyword>

    <keyword>dynamical systems learning</keyword>

    <keyword>movement generation</keyword>

  </keywords>

  <!--

  <structure>

        Time series of joint angles and hand positions. Note that the Cyberglove captures at approximately 90hz and the Vicon system at exactly 200hz. 

  </structure>

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  <formats>

          <format>MATLAB</format>

  </formats>

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  <relation>http://pub.uni-bielefeld.de/pub?func=drec&#38;id=2034003"</relation>

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  <acknowledgements>

    The development of this software was funded by FP7 under GA. No. 248311-AMARSi.

    <!--The development of this database was supported by the Excellence Cluster EXC 277 Cognitive Interaction Technology. The Excellence Cluster EXC 277 is a grant of the Deutsche                 Forschungsgemeinschaft (DFG) in the context of the German Excellence Initiative.--> 

  </acknowledgements>

</opendatametainfo>

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