Publications

Many of these publications are copyrighted by their respective publishers. Downloadable versions are not necessarily identical to the published versions. They are made available here for personal use only.

  1. M. Hjelm, R. Detry, C. H. Ek and D. Kragic, Representations for Cross-task, Cross-object Grasp Transfer. In IEEE International Conference on Robotics and Automation, 2014.
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  2. M. Kopicki, R. Detry, F. Schmidt, C. Borst, R. Stolkin and J. L. Wyatt, Learning dextrous grasps that generalise to novel objects by combining hand and contact models. In IEEE International Conference on Robotics and Automation, 2014.
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  3. R. Detry, C. H. Ek, M. Madry and D. Kragic, Learning a Dictionary of Prototypical Grasp-predicting Parts from Grasping Experience. In IEEE International Conference on Robotics and Automation, 2013.
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  4. R. Detry, M. Hjelm, C. H. Ek and D. Kragic, Generalizing Task Parameters Through Modularization. In Autonomous Learning Workshop (Workshop at ICRA 2013), 2013.
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  5. R. Detry and J. Piater, Unsupervised Learning Of Predictive Parts For Cross-object Grasp Transfer. In IEEE/RSJ International Conference on Intelligent Robots and Systems, 2013.
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  6. M. Hjelm, C. H. Ek, R. Detry, H. Kjellström and D. Kragic, Sparse Summarization of Robotic Grasp Data. In IEEE International Conference on Robotics and Automation, 2013.
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  7. A. Rietzler, R. Detry and J. Piater, Inertially-safe Grasping of Novel Objects. In Cognitive Robotics Systems: Replicating Human Actions and Activities (Workshop at IROS 2013), 2013.
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  8. Y. Bekiroglu, R. Detry and D. Kragic, Grasp Stability from Vision and Touch. In Advances in Tactile Sensing and Touch-based Human Robot Interaction (Workshop at IROS 2012), 2012.
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  9. R. Detry, C. H. Ek, M. Madry, J. Piater and D. Kragic, Generalizing Grasps Across Partly Similar Objects. In IEEE International Conference on Robotics and Automation, 2012.
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  10. R. Detry, C. H. Ek, M. Madry and D. Kragic, Compressing Grasping Experience into a Dictionary of Prototypical Grasp-predicting Parts. In International Workshop on Human-Friendly Robotics, 2012.
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  11. M. Madry, C. H. Ek, R. Detry, K. Hang and D. Kragic, Improving Generalization for 3D Object Categorization with Global Structure Histograms. In IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012. (Best cognitive paper award).
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  12. Y. Bekiroglu, R. Detry and D. Kragic, Joint Observation of Object Pose and Tactile Imprints for Online Grasp Stability Assessment. In Manipulation Under Uncertainty (Workshop at IEEE ICRA 2011), 2011.
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  13. Y. Bekiroglu, R. Detry and D. Kragic, Learning Tactile Characterizations Of Object- And Pose-specific Grasps. In IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011.
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  14. L. Bodenhagen, R. Detry, J. Piater and N. Krüger, What a successful grasp tells about the success chances of grasps in its vicinity. In ICDL-EpiRob, 2011.
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  15. R. Detry, D. Kraft, O. Kroemer, L. Bodenhagen, J. Peters, N. Krüger and J. Piater, Learning Grasp Affordance Densities. In Paladyn. Journal of Behavioral Robotics, 2 (1): 1–17, 2011.
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  16. R. Detry and J. Piater, Grasp Generalization Via Predictive Parts. In Austrian Robotics Workshop, 2011.
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  17. J. Piater, S. Jodogne, R. Detry, D. Kraft, N. Krüger, O. Kroemer and J. Peters, Learning Visual Representations for Perception-Action Systems. In International Journal of Robotics Research, 30 (3): 294–307, 2011.
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  18. R. Detry, E. Başeski, M. Popović, Y. Touati, N. Krüger, O. Kroemer, J. Peters and J. Piater, Learning Continuous Grasp Affordances by Sensorimotor Exploration. In From Motor Learning to Interaction Learning in Robots, pages 451–465, Springer-Verlag, 2010.
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  19. R. Detry, D. Kraft, A. G. Buch, N. Krüger and J. Piater, Refining Grasp Affordance Models by Experience. In IEEE International Conference on Robotics and Automation, pages 2287–2293, 2010.
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  20. R. Detry and J. Piater, Continuous Surface-point Distributions for 3D Object Pose Estimation and Recognition. In Asian Conference on Computer Vision, pages 572–585, 2010.
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  21. R. Detry, Learning of Multi-Dimensional, Multi-Modal Features for Robotic Grasping. Ph.D. Thesis, University of Liège, 2010.
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  22. A. Erkan, O. Kroemer, R. Detry, Y. Altun, J. Piater and J. Peters, Learning Probabilistic Discriminative Models of Grasp Affordances under Limited Supervision. In IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 1586–1591, 2010.
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  23. D. Kraft, R. Detry, N. Pugeault, E. Başeski, F. Guerin, J. Piater and N. Krüger, Development of Object and Grasping Knowledge by Robot Exploration. In IEEE Transactions on Autonomous Mental Development, 2 (4): 368–383, 2010.
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  24. O. Kroemer, R. Detry, J. Piater and J. Peters, Adapting Preshaped Grasping Movements using Vision Descriptors. In From Animals to Animats 11 – International Conference on the Simulation of Adaptive Behavior, pages 156–166, 2010.
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  25. O. Kroemer, R. Detry, J. Piater and J. Peters, Grasping with Vision Descriptors and Motor Primitives. In International Conference on Informatics in Control, Automation and Robotics, 2010.
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  26. O. Kroemer, R. Detry, J. Piater and J. Peters, Combining Active Learning and Reactive Control for Robot Grasping. In Robotics and Autonomous Systems, 58 (9): 1105–1116, 2010.
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  27. R. Detry, N. Pugeault and J. Piater, A Probabilistic Framework for 3D Visual Object Representation. In IEEE Trans. Pattern Anal. Mach. Intell., 31 (10): 1790–1803, 2009.
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  28. R. Detry, E. Başeski, N. Krüger, M. Popović, Y. Touati and J. Piater, Autonomous Learning of Object-specific Grasp Affordance Densities. In Approaches to Sensorimotor Learning on Humanoid Robots (Workshop at the IEEE International Conference on Robotics and Automation), 2009.
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  29. R. Detry, E. Başeski, N. Krüger, M. Popović, Y. Touati, O. Kroemer, J. Peters and J. Piater, Learning Object-specific Grasp Affordance Densities. In IEEE International Conference on Development and Learning, pages 1–7, 2009.
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  30. D. Kraft, R. Detry, N. Pugeault, E. Başeski, J. Piater and N. Krüger, Learning Objects and Grasp Affordances through Autonomous Exploration. In International Conference on Computer Vision Systems, pages 235–244, 2009.
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  31. O. Kroemer, R. Detry, J. Piater and J. Peters, Active Learning using Mean Shift Optimization for Robot Grasping. In IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 2610–2615, 2009.
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  32. J. Piater, S. Jodogne, R. Detry, D. Kraft, N. Krüger, O. Kroemer and J. Peters, Learning Visual Representations for Interactive Systems. In International Symposium on Robotics Research, 2009.
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  33. R. Detry, N. Pugeault and J. H. Piater, Probabilistic Pose Recovery Using Learned Hierarchical Object Models. In International Cognitive Vision Workshop (Workshop at the 6th International Conference on Vision Systems), pages 107–120, Springer-Verlag, Berlin, Heidelberg, 2008.
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  34. D. Kraft, E. Başeski, M. Popović, A. M. Batog, A. Kjær-Nielsen, N. Krüger, R. Petrick, C. Geib, N. Pugeault, M. Steedman, T. Asfour, R. Dillmann, S. Kalkan, F. Wörgötter, B. Hommel, R. Detry and J. Piater, Exploration and Planning in a Three-Level Cognitive Architecture. In International Conference on Cognitive Systems (Workshop at the IEEE International Conference on Robotics and Automation), 2008. (Extended Abstract).
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  35. J. Piater, F. Scalzo and R. Detry, Vision as Inference in a Hierarchical Markov Network. In International Conference on Cognitive and Neural Systems, 2008. (Extended Abstract).
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  36. J. Piater and R. Detry, 3D Probabilistic Representations for Vision and Action. In Robotics Challenges for Machine Learning II (Workshop at the IEEE/RSJ International Conference on Intelligent Robots and Systems), 2008. (Extended Abstract).
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  37. R. Detry and J. H. Piater, Hierarchical Integration of Local 3D Features for Probabilistic Pose Recovery. In Robot Manipulation: Sensing and Adapting to the Real World (Workshop at Robotics, Science and Systems), 2007.
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