Journal:

  • Simultaneous Tactile Exploration and Grasp Refinement for Unknown Objects, C. de Farias, N. Marturi, R. Stolkin, Y. Bekiroglu, IEEE Robotics and Automation Letters, 2021.

  • Visual and Tactile 3D Point Cloud Data from Real Robots for Shape Modeling and Completion, Y. Bekiroglu*, M. Bjorkman*, G. Z. Gandler*, J. Exner, C. H. Ek, D. Kragic, Data in Brief, 2020.

  • Object shape estimation and modeling, based on sparse Gaussian process implicit surfaces, combining visual data and tactile exploration, G. Z. Gandler, C. H. Ek, M. Bjorkman, R. Stolkin, Y. Bekiroglu, Robotics and Autonomous Systems, 2020.

  • Benchmarking Protocol for Grasp Planning Algorithms, Y. Bekiroglu*, N. Marturi*, M. A. Roa*, K. J. M. Adjigble, T. Pardi, C. Grimm, R. Balasubramanian, K. Hang, R. Stolkin, IEEE Robotics and Automation Letters, vol. 5, no. 2, pp. 315-322, April 2020.

  • Dynamic grasp and trajectory planning for moving objects, N. Marturi, M. Kopicki, A. Rastegarpanah, R. Stolkin, A. Leonardis, Y. Bekiroglu, Autonomous Robots, 43(5), 1241-1256, 2019.

  • A Database for Reproducible Manipulation Research: CapriDB - Capture, Print, Innovate, Y. Bekiroglu*, F. T. Pokorny*, K. Pauwels, J. Butepage, C. Scherer, D. Kragic, Data in Brief, 2017

  • Hierarchical Fingertip Space: A Unified Framework for Grasp Planning and In-Hand Grasp Adaptation, K. Hang, M. Li, J. A. Stork, Y. Bekiroglu, F. T. Pokorny, A. Billard, D. Kragic, IEEE Transactions on Robotics 2016.

  • Assessing grasp stability based on learning and haptic data, Y. Bekiroglu, J. Laaksonen, J.A. Jorgensen, V. Kyrki and D. Kragic, IEEE Transactions on Robotics, 27(3):616-629, 2011.

Conference:

  • Simultaneous Tactile Exploration and Grasp Refinement for Unknown Objects, C. de Farias, N. Marturi, R. Stolkin, Y. Bekiroglu, IEEE International Conference on Robotics and Automation, 2021, Xi'an, China.

  • Evaluating the Quality of Non-Prehensile Balancing Grasps, R. Krug, Y. Bekiroglu, D. Kragic, M. A. Roa, IEEE International Conference on Robotics and Automation, 2018, Brisbane.

  • Teaching Assembly by Demonstration using Advanced Human Robot Interaction and a Knowledge Integration Framework, M. Haage, G. Piperagkas, C. Papadopoulos, I. Mariolis, J. Malec, Y. Bekiroglu, Hedelind M., D. Tzovaras, International Conference on Flexible Automation and Intelligent Manufacturing (FAIM), 2017

  • Grasp Quality Evaluation Done Right: How Assumed Contact Force Bounds Affect Wrench-Based Quality Metrics, R. Krug, Y. Bekiroglu, M. A. Roa, IEEE International Conference on Robotics and Automation, 2017, Singapore.

  • Towards Robotic Manipulation for Nuclear Decommissioning: A Pilot Study on Tele-operation and Autonomy, N. Marturi, A. Rastegarpanah, C. Takahashi, J. Kuo, R. Stolkin, Y. Bekiroglu, IEEE International Conference on Robotics and Automation for Humanitarian Applications (RAHA), 2016, Kerala, India, Best Paper Award.

  • Active Exploration Using Gaussian Random Fields and Gaussian Process Implicit Surfaces, S. Caccamo, Y. Bekiroglu, C. H. Ek, D. Kragic, IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016, Daejeon, Korea.

  • Analytic Grasp Success Prediction with Tactile Feedback, R. Krug, A. J. Lilienthal, D. Kragic, Y. Bekiroglu, IEEE International Conference on Robotics and Automation 2016, Stockholm, Sweden.

  • Probabilistic Consolidation of Grasp Experience, Y. Bekiroglu, A. Damianou, R. Detry, J. A. Stork, D. Kragic, C. H. Ek, IEEE International Conference on Robotics and Automation 2016, Stockholm, Sweden.

  • Learning Predictive State Representation for In-Hand Manipulation, J. A. Stork, C. H. Ek, Y. Bekiroglu and D. Kragic, IEEE International Conference on Robotics and Automation 2015, Seattle, Washington, USA.

  • Learning to Disambiguate Object Hypotheses through Self-Exploration, M. Bjorkman and Y. Bekiroglu, IEEE-RAS International Conference on Humanoid Robots 2014, Madrid, Spain.

  • Learning of Grasp Adaptation through Experience and Tactile Sensing, M. Li, Y. Bekiroglu, D. Kragic and A. Billard, IEEE/RSJ International Conference on Intelligent Robots and Systems 2014, Chicago, USA.

  • What's in the Container? Classifying Object Contents from Vision and Touch, P. Guler, Y. Bekiroglu, X. Gratal, K. Pauwels and D. Kragic, IEEE/RSJ International Conference on Intelligent Robots and Systems 2014, Chicago, USA.

  • Grasp Moduli Spaces and Spherical Harmonics, F. T. Pokorny, Y. Bekiroglu and D. Kragic, IEEE International Conference on Robotics and Automation 2014, Hong Kong, China.

  • Predicting Slippage and Learning Manipulation Affordances through Gaussian Process Regression, F. Vina, Y. Bekiroglu, C. Smith, Y. Karayiannidis and D. Kragic, IEEE-RAS International Conference on Humanoid Robots 2013, Atlanta, USA.

  • Enhancing Visual Perception of Shape through Tactile Glances, M. Bjorkman, Y. Bekiroglu, V. Hogman and D. Kragic, IEEE/RSJ International Conference on Intelligent Robots and Systems 2013, Tokyo, Japan, IROS CoTeSys Cognitive Robotics Best Paper Award Finalist.

  • A Probabilistic Framework for Task-Oriented Grasp Stability Assessment, Y. Bekiroglu, D. Song, L. Wang and D. Kragic, IEEE International Conference on Robotics and Automation 2013, Karlsruhe, Germany, Best Manipulation Paper Award.

  • Learning Tactile Characterizations Of Object- And Pose-specific Grasps, Y. Bekiroglu, R. Detry and D. Kragic, IEEE/RSJ International Conference on Intelligent Robots and Systems 2011, San Francisco, USA.

  • Integrating Grasp Planning with Online Stability Assessment using Tactile Sensing, Y. Bekiroglu, K. Huebner and D. Kragic, IEEE International Conference on Robotics and Automation 2011, Shanghai, China.

  • Learning grasp stability with tactile data and HMMs, Y. Bekiroglu, V. Kyrki and D. Kragic, IEEE International Symposium on Robot and Human Interactive Communication 2010, Viareggio, Italy.

Workshop:

  • Shape Modeling based on Sparse Gaussian Process Implicit Surfaces, G. Z. Gandler, C. H. Ek, M Bjorkman, Y Bekiroglu, NeurIPS 2018, WIML workshop, Montreal, Canada.

  • CapriDB - Capture, Print, Innovate: A Low-Cost Pipeline and Database for Reproducible Manipulation Research, F. T. Pokorny, Y. Bekiroglu, K. Pauwels, J. Butepage, C. Scherer, D. Kragic, IEEE ICRA 2016 Workshop: Grasping and Manipulation Datasets, Stockholm, Sweden.

  • Grasp Moduli Spaces, Gaussian Processes and Multimodal Sensor Data, F. T. Pokorny, Y. Bekiroglu, M. Bjorkman, J. Exner and D. Kragic, RSS 2014 Workshop: Information-based Grasp and Manipulation Planning, Berkeley, USA.

  • Hierarchical Fingertip Space for Synthesizing Adaptable Fingertip Grasps, K. Hang, M. Li, J. A. Stork, Y. Bekiroglu, A. Billard and D. Kragic, ICRA 2014 Workshop: Autonomous Grasping and Manipulation: An Open Challenge, Hong Kong, China.

  • Grasp Stability from Vision and Touch, Y. Bekiroglu, R. Detry and D. Kragic, IEEE IROS 2012 Workshop: Advances in Tactile Sensing and Touch-based Human Robot Interaction, Vilamoura, Portugal.

  • Learning Task- and Touch-based Grasping, Y. Bekiroglu, D. Song, L. Wang and D. Kragic, IEEE IROS 2012 Workshop: Beyond Robot Grasping - Modern Approaches for Learning Dynamic Manipulation, Vilamoura, Portugal.

  • Joint Observation of Object Pose and Tactile Imprints for Online Grasp Stability Assessment, Y. Bekiroglu, R. Detry and D. Kragic, IEEE ICRA 2011 workshop: Manipulation Under Uncertainty, Shanghai, China.

  • Learning grasp stability based on haptic data, Y. Bekiroglu, J. Laaksonen, J. A. Jorgensen, V. Kyrki and D. Kragic, RSS 2010 workshop: Representations for object grasping and manipulation in single and dual arm tasks, Zaragoza, Spain.

Other:

  • Learning a generative model for robot control using visual feedback, N Gothoskar, M Lázaro-Gredilla, A Agarwal, Y Bekiroglu, D George, ArXiv preprint arXiv:2003.04474, 2020

  • Smart Assembly Robot with Advanced Functionalities (SARAFun), Y. Bekiroglu, R. Haschke, Y. Karayiannidis, I Mariolis, J McIntyre, J Malec, Impact, 2017

  • Towards advanced robotic manipulation for nuclear decommissioning, N. Marturi, A. Rastegarpanah, V. Rajasekaran, V. Ortenzi, Y. Bekiroglu, J. Kuo, R. Stolkin, Robots Operating in Hazardous Environments, InTechOpen, 2017

  • CapriDB-Capture, Print, Innovate: A Low-Cost Pipeline and Database for Reproducible Manipulation Research, F. T. Pokorny, Y. Bekiroglu, K. Pauwels, J. Butepage, C. Scherer, D. Kragic, ArXiv preprint arXiv:1610.05175, 2016

  • Active Exploration Using Gaussian Random Fields and Gaussian Process Implicit Surfaces, S. Caccamo, Y. Bekiroglu, C. Ek, D. Kragic, ArXiv preprint arXiv:1802.04642, 2016

  • Multisensory exploration - ROBOHOW.COG:D4.3, C. Smith, Y. Karayiannidis, Y., Bekiroglu, K. Pauwels, D. Kragic, 2015.

  • Tracking and State Estimation of Manipulated Objects - ROBOHOW.COG:D4.2, C. Smith, Y. Karayiannidis, Y. Bekiroglu, D. Kragic, 2013.

  • Learning to Assess Grasp Stability from Vision, Touch and Proprioception, Y. Bekiroglu, PhD Thesis, 2012.

  • Qualitative models of object behaviour, and grasping of novel objects - CogX:D2.5, R. Detry, M. Zillich, A. Richtsfeld, J. Prankl, M. Roa, S., Zurek, Y. Bekiroglu, T. Morwald, M. Vincze, D. Kragic, J. Wyatt, G.-J. Kruijff, 2012.

  • Manipulation of previously unseen objects - CogX:D2.4, M. Zillich, S. Zurek, M. Kopicki, R. Stolkin, Y. Bekiroglu, R. Detry, 2011.

  • Representation of Gaps in Object Knowledge - CogX:D2.3, M. Zillich, J. Prankl, M. Vincze, Y. Bekiroglu, D. Kragic, S., Zurek, R. Stolkin, 2010.

  • Representations of 3D shape for manipulation - CogX:D2.1, M. Zillich, M. Vincze, T. Mörwald, A. Richtsfeld, K. Zhou, Y. Bekiroglu, M. Kopicki, 2009.