PUB - Publikationen an der Universität Bielefeld

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• [14]
  

  2012 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2306886

  Schöpfer, M., et al., 2012. Identifying Relevant Tactile Features for Object Identification. In E. Prassler, et al., eds. Towards Service Robots for Everyday Environments. Recent Advances In Designing Service Robots For Complex Tasks In Everyday Environments. Springer Tracts in Advanced Robotics. no.76 Berlin: Springer, pp. 417-430.

  PUB | DOI | WoS
   
• [13]
  

  2011 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2141974

  Steffen, J.F., et al., 2011. Integrating Feature Maps and Competitive Layer Architectures For Motion Segmentation. Neurocomputing, 74(9), p 1372-1381.

  PUB | DOI | WoS
   
• [12]
  

  2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2282158

  Barchunova, A., et al., 2010. Identification of High-level Object Manipulation Operations from Multimodal Input. Presented at the IASTED International Conferences on Automation, Control, and Information Technology

  PUB | PDF
   
• [11]
  

  2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1894923

  Schöpfer, M., et al., 2010. Open Source Real-Time Control Software for the Kuka Light Weight Robot. In Institute of Electrical and Electronics Engineers, ed. Proc. of World Congress on Intelligent Control and Automation. Jinan, China: IEEE, pp. 444-449.

  PUB | DOI
   
• [10]
  

  2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1996857

  Schöpfer, M., et al., 2010. Using a Piezo-Resistive Tactile Sensor for Detection of Incipient Slippage. In International Symposium on Robotics. pp. 1-7.

  PUB | PDF | Download (ext.)
   
• [9]
  

  2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2033993

  Steffen, J.F., et al., 2010. Neural competition for motion segmentation. In 18th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN). Bruges (Belgium): d-side, pp. 59-64.

  PUB | PDF
   
• [8]
  

  2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2488317

  Pardowitz, M., 2009. Elements of robot learning: from the skill to the task level. In Workshop: Bridging the gap between high-level discrete representations and low-level continuous behaviours.

  PUB
   
• [7]
  

  2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1894911

  Schöpfer, M., Pardowitz, M., & Ritter, H., 2009. Using Entropy for Dimension Reduction of Tactile Data. In 14th International Conference on Advanced Robotics. Munich, Germany: IEEE, pp. 1-6.

  PUB
   
• [6]
  

  2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1996902

  Steffen, J.F., Pardowitz, M., & Ritter, H., 2009. Using Structured UKR Manifolds for Motion Classification and Segmentation. In Intelligent Robots and Systems (IROS). pp. 4785-4790.

  PUB | PDF | DOI
   
• [5]
  

  2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1894932

  Schöpfer, M., et al., 2009. Handling of Deformable Material Using Tactile Sensors in a Bi-manual Scenario. In Workshop on Tactile Sensing in Humanoids @ HUMANOIDS. Paris.

  PUB
   
• [4]
  

  2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1996826

  Pardowitz, M., Steffen, J.F., & Ritter, H., 2009. Self-emerging Action Gestalts for Task Segmentation. In 32nd German Conference on Artificial Intelligence (KI-2009). Berlin, Heidelberg: Springer, pp. 589-596.

  PUB | DOI
   
• [3]
  

  2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1894915

  Schöpfer, M., Pardowitz, M., & Ritter, H., 2009. Evaluation of Tactile Features for Object Categorization. In Workshop on Tactile Sensing in Humanoids @ HUMANOIDS. Paris.

  PUB
   
• [2]
  

  2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1996898

  Steffen, J.F., Pardowitz, M., & Ritter, H., 2009. A Manifold Representation as Common Basis for Action Production and Recognition. In 32nd German Conference on Artificial Intelligence (KI-2009). Berlin, Heidelberg: Springer, pp. 607-614.

  PUB | DOI
   
• [1]
  

  2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1996821

  Pardowitz, M., et al., 2008. Gestalt-Based Action Segmentation for Robot Task Learning. In IEEE-RAS 7th International Conference on Humanoid Robots (HUMANOIDS). pp. 347-352.

  PUB | PDF | DOI