PUBLICATIONS

[1]
A. Tekden, A. Erdem, E. Erdem, T. Asfour, and E. Ugur. Object and relation centric representations for push effect prediction. Transactions on Robotics, 2021. under review. [ bib ]
[2]
M.Y. Seker, A. Alperoglu, Y. Nagai, M. Asada, E. Oztop, and E. Ugur. Imitation and mirror systems through deep modality blending networks. Neural Networks, 2021. submitted. [ bib ]
[3]
Alejandro Suárez-Hernández, Javier Segovia-Aguas, Carme Torras, and Guillem Alenyà. Online action recognition. In 35th AAAI Conference, page to appear, 2021. [ bib ]
[4]
Erenus Yildiz, Erwan Renaudo, Jakob Hollenstein, Justus Piater, and Florentin Wörgötter. An Extended Visual Intelligence Scheme for Disassembly in Automated Recycling Routines. CCIS. Springer, 2021. Submitted. [ bib ]
[5]
M.T. Akbulut, U. Bozdogan, A. Tekden, and E. Ugur. Reward conditioned neural movement primitives for population based variational policy optimization. In International Conference on Robotics and Automation (ICRA), 2021. [ bib ]
[6]
Cornelius Klas, Felix Hundhausen, Jianfeng Gao, Christian R. G. Dreher, Stefan Reither, You Zhou, and Tamim Asfour. The kit gripper: A multi-functional gripper for disassembly tasks. In International Conference on Robotics and Automation (ICRA), 2021. [ bib ]
[7]
David Peer, Sebastian Stabinger, and Antonio Rodríguez-Sánchez. Auto-tuning of Deep Neural Networks by Conflicting Layer Removal. submitted to Neural Networks, 2021. [ bib | http ]
[8]
David Peer, Sebastian Stabinger, and Antonio Rodríguez-Sánchez. conflicting_bundle.py - A python module to identify problematic layers in deep neural networks. Software Impacts, 7, 2 2021. [ bib | doi | http ]
[9]
David Peer, Sebastian Stabinger, and Antonio Rodríguez-Sánchez. Conflicting Bundles: Adapting Architectures Towards the Improved Training of Deep Neural Networks . In IEEE/CVF Winter Conference on Applications of Computer Vision, pages 256--256, 1 2021. [ bib | pdf ]
[10]
Jakob Hollenstein, Auddy Sayantan, Matteo Saveriano, Erwan Renaudo, and Justus Piater. How do Offline Measures for Exploration in Reinforcement Learning behave? In Knowledge Based Reinforcement Learning Workshop at IJCAI-PRICAI 2020, Yokohama, Japan , 1 2021. [ bib | pdf ]
[11]
David Peer, Sebastian Stabinger, and Antonio Rodríguez-Sánchez. Limitation of capsule networks. Pattern Recognition Letters, 144:68--74, 4 2021. [ bib | doi | http ]
[12]
Alejandro Suárez-Hernández, Javier Segovia-Aguas, Carme Torras, and Guillem Alenyà. Strips action discovery. In Generalization in Planning Workshop at AAAI 2020, 2020. [ bib ]
[13]
Javier Segovia-Aguas, Sergio Jiménez, and Anders Jonsson. Generalized planning with positive and negative examples. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 34, pages 9949--9956, 2020. [ bib ]
[14]
A. Suárez-Hernández, T. Gaugry, J. Segovia-Aguas, A. Bernardin, C. Torras, M. Marchal, and G. Alenyà. Leveraging multiple environments for learning and decision making: a dismantling use case. In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 6902--6908, 2020. [ bib | doi ]
[15]
Romain Lagneau, Alexandre Krupa, and Maud Marchal. Active deformation through visual servoing of soft objects. In IEEE International Conference on Robotics and Automation. IEEE, 2020. [ bib | doi ]
[16]
Jakob J. Hollenstein, Erwan Renaudo, and Justus Piater. Improving exploration of deep reinforcement learning using planning for policy search. In Submitted to International Conference on Development and Learning and Epigenetic Robotics, 2020. under review. [ bib ]
[17]
Timo Lueddecke and Florentin Woergoetter. Fine-grained action plausibility rating. Robotics and Autonomous Systems, 129, 7 2020. [ bib ]
[18]
Erenus Yildiz and Florentin Woergoetter. Dcnn-based screw classification in automated disassembly processes. In International Conference on Robotics, Computer Vision and Intelligent Systems, 2020. [ bib ]
[19]
Erenus Yildiz, Tobias Brinker, Erwan Renaudo, Jakob J. Hollenstein, Simon Haller-Seeber, Justus Piater, and Florentin Woergoetter. A visual intelligence scheme for hard drive disassembly in automated recycling routines. In International Conference on Robotics, Computer Vision and Intelligent Systems, pages 17--27. INSTICC, SciTePress, 2020. [ bib | doi ]
[20]
Erenus Yildiz and Woergoetter Florentin. Dcnn-based wire detection in automated disassembly processes. In Submitted to International Conference on Pattern Recognition, 2020. Under review. [ bib ]
[21]
A. E. Tekden, A. Erdem, E. Erdem, M. Imre, M.Y. Seker, and E. Ugur. Belief regulated dual propagation nets for learning action effects on articulated multi-part objects. In International Conference on Robotics and Automation (ICRA), 2020. [ bib ]
[22]
M.T. Akbulut, E. Oztop, Y. Seker, H. Xue, A. Tekden, and E. Ugur. Acnmp: Flexible skill formation through learning from demonstration and reinforcement learning via representation sharing. In Conference on Robot Learning (CoRL), 2020. [ bib ]
[23]
A. Ahmetoglu, Y. Seker, E. Oztop, M. Asada, and Emre Ugur. Locally weighted cnmps for generating flexible action sequences. In Winter Workshop on Mechanism of Brain and Mind, Hokkaido, Japan, 2020. Poster presentation. [ bib ]
[24]
M. Yunus Seker, Erhan Oztop, Mete Tuluhan Akbulut, Yukie Nagai, Minoru Asada, and Emre Ugur. Towards a mirror neuron system via dual channel conditional neural movement primitives. In ICRA Brain-PIL Workshop, New advances in brain-inspired perception, interaction and learning, ICRA, 2020. Poster presentation. [ bib ]
[25]
Utku Bozdogan and Emre Ugur. Learning from multiple demonstrations with different modes of operations. International Journal of Intelligent Systems and Applications in Engineering, 8(1):37--44, 2020. [ bib ]
[26]
Pilar de la Cruz, Justus Piater, and Matteo Saveriano. Reconfigurable Behavior Trees: Towards an Executive Framework Meeting High-Level Decision Making and Control Layer Features. In IEEE International Conference on Systems, Man, and Cybernetics, 10 2020. To appear. [ bib | http ]
[27]
Matteo Saveriano. An Energy-based Approach to Ensure the Stability of Learned Dynamical Systems. In IEEE International Conference on Robotics and Automation, Piscataway, NJ, 06 2020. IEEE. [ bib | doi | http ]
[28]
Jakob Hollenstein, Erwan Renaudo, Saveriano Matteo, and Justus Piater. How does explicit exploration influence Deep Reinforcement Learning? In Joint Austrian Computer Vision and Robotics Workshop, pages 29--30. Verlag der TU Graz, 8 2020. [ bib | doi | pdf ]
[29]
E. Ugur and H. Girgin. Compliant parametric dynamic movement primitives. Robotica, 2019. [ bib ]
[30]
M. Imre, E. Oztop, Y. Nagai, and E. Ugur. Affordance-based altruistic robotic architecture for human-robot collaboration. Adaptive Behavior, 27(4):223--241, 2019. [ bib | doi ]
[31]
M.Y. Seker, A.E. Tekden, and E. Ugur. Deep effect trajectory prediction in robot manipulation. Robotics and Autonomous Systems, 119:173--184, 2019. [ bib ]
[32]
Mert Imre and M.Yunus Seker ve Emre Ugur. Object manipulation learning via conditional neural movement primitives. In Turkiye Robotbilim Konferansi (Turkish Robotics Conference), 2019. poster publication, best poster award. [ bib ]
[33]
Philipp Zech, Erwan Renaudo, Simon Haller, Xiang Zhang, and Justus Piater. Action representations in robotics: A taxonomy and systematic Classification. International Journal of Robotics Research, 2019. [ bib | doi ]
[34]
You Zhou, Jianfeng Gao, and Tamim Asfour. Learning via-point movement primitives with inter- and extrapolation capabilities. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2019. [ bib ]
[35]
Alejandro Suárez-Hernández, Guillem Alenyà, and Carme Torras. Practical Resolution Methods for MDPs in Robotics Exemplified with Disassembly Planning. IEEE Robotics and Automation Letters, 4(3):2282--2288, 2019. presented at ICRA 2019. [ bib | doi | http ]
[36]
Antonio Andriella, Alejandro Suárez-Hernández, Javier Segovia-Aguas, Carme Torras, and Guillem Alenyà. Natural teaching of robot-assisted rearranging exercises for cognitive training. In 11th International Conference on Social Robotics, page to appear. Springer, 2019. [ bib ]
[37]
Alejandro Suárez-Hernández, Antonio Andriella, Aleksandar Taranović, Javier Segovia-Aguas, Carme Torras, and Guillem Alenyà. Automatic Learning of Cognitive Exercises for Socially Assistive Robotics. In IEEE ICRA, page submitted, 2019. [ bib ]
[38]
Antonin Bernardin, Christian Duriez, and Maud Marchal. An interactive physically-based model for active suction phenomenon simulation. In Proc. of International Conference on Intelligent Robots and Systems (IROS). IEEE/RJS, IEEE, 2019. [ bib | doi ]
[39]
Romain Lagneau, Alexandre Krupa, and Maud Marchal. Active deformation through visual servoing of soft objects. In Technical Report: paper submitted to ICRA 2020, 2019. [ bib ]
[40]
Felix Hundhausen, Cornelius Klas, and Tamim Asfour. Kit multifunctional robotics gripper (v2). Technical report, Karlsruhe Institute of Technology, 2019. [ bib ]
[41]
Erwan Renaudo, Philipp Zech, and Justus Piater. Ades -- autonomous learning of effects and effects models. Technical report, University of Innsbruck, 2019. [ bib ]
[42]
Woergoetter F. Yildiz E. Pose estimation of 2d recognized parts using pointcloud and mesh processing. Technical report, Georg-August University of Goettingen, 2019. [ bib ]
[43]
Erenus Yildiz and Florentin Wörgötter. Dcnn-based screw detection for automated disassembly processes. In 2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), pages 187--192. IEEE, 2019. [ bib ]
[44]
Woergoetter F. Yildiz E. Visual detection of gaps in disassembly routines using stereo-vision. Technical report, Georg-August University of Goettingen, 2019. [ bib ]
[45]
Fabio Ferreira, Lin Shao, Tamim Asfour, and Jeannette Bohg. Learning visual dynamics models of rigid objects using relational inductive biases. In NeurIPS 2019 Graph Representation Learning Workshop, pages 0--0, 2019. [ bib | http ]
[46]
Jakob Hollenstein and Justus Piater. Evaluating Planning for Policy Search. In 1st Workshop on Workshop on Closing the Reality Gap in Sim2real Transfer for Robotic Manipulation, 6 2019. [ bib | pdf ]
[47]
H. Girgin and E. Ugur. Associative skill memory models. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 6043--6048, Madrid, Spain, 2018. [ bib ]
[48]
Júlia Borràs, Raphael Heudorfer, Samuel Rader, Peter Kaiser, and Tamim Asfour. The kit swiss knife gripper for disassembly tasks: A multi-functional gripper for bimanual manipulation with a single arm. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 4590--4597, 2018. [ bib ]
[49]
Júlia Borràs, Raphael Heudorfer, Samuel Rader, Peter Kaiser, and Tamim Asfour. The KIT Swiss Knife Gripper for Disassembly Tasks: A Multi-Functional Gripper for Bimanual Manipulation with a Single Arm. IEEE Robotics and Automation Letters (RA-L), 2018. Submitted. [ bib ]
[50]
Hakan Girgin and Emre Ugur. Parametrik dinamik motor primitifleri. In Turkiye Robotbilim Konferansi (Turkish Robotics Conference), 2018. [ bib ]
[51]
M. Yunus Seker, Erhan Cagirici, and Emre Ugur. Sekil baglami kullanarak eylem-etki tahmini. In Turkiye Robotbilim Konferansi (Turkish Robotics Conference), 2018. [ bib ]
[52]
Ahmet E. Tekden and Emre Ugur. Kaldirma aksiyonuyla olusan yorungenin uzun kisa donem hafiza modeliyle tahmini. In Turkiye Robotbilim Konferansi (Turkish Robotics Conference), 2018. [ bib ]
[53]
Tadahiro Taniguchi, Emre Ugur, Matej Hoffmann, Lorenzo Jamone, Takayuki Nagai, Benjamin Rosman, Toshihiko Matsuka, Naoto Iwahashi, Erhan Oztop, Justus Piater, and Florentin Wörgötter. Symbol Emergence in Cognitive Developmental Systems: a Survey. IEEE Transactions on Cognitive and Developmental Systems, 2018. doi: 10.1109/TCDS.2018.2867772. [ bib | http ]
[54]
Alejandro Suarez-Hernandez, Guillem Alenya, and Carme Torras. Interleaving Hierarchical Task Planning and Motion Constraint Testing for Dual-Arm Manipulation. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 4061--4066. IEEE, 10 2018. [ bib | doi | http ]
[55]
R. Kartmann, F. Paus, M. Grotz, and T. Asfour. Extraction of physically plausible support relations to predict and validate manipulation action effects. IEEE Robotics and Automation Letters (RA-L), 3(4):3991--3998, 2018. [ bib ]
[56]
Hakan Girgin and Emre Ugur. Towards generalizable associative skill memories. In ICRA Workshop on Learning and control for autonomous manipulation systems: the role of dimensionality reduction, 2017. [ bib ]
[57]
Simon Hangl, Sebastian Stabinger, and Justus Piater. Autonomous Skill-centric Testing using Deep Learning. In IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 95--102, Piscataway, NJ, 8 2017. IEEE. [ bib | doi | pdf ]
[58]
Philipp Zech, Simon Haller, Safoura Rezapour Lakani, Barry Ridge, Emre Ugur, and Justus Piater. Computational models of affordance in robotics: a taxonomy and systematic classification. Adaptive Behavior, 25(5):235--271, 9 2017. [ bib | doi | pdf ]
[59]
M.Y. Seker, M. Imre, J. Piater, and E. Ugur. Conditional neural movement primitives. In Robotics: Science and Systems (RSS), Freiburg, Germany. [ bib ]
[60]
Agniva Sengupta, Romain Lagneau, Alexandre Krupa, Eric Marchand, and Maud Marchal. Simultaneous tracking and elasticity parameter estimation of deformable objects. In IEEE International Conference on Robotics and Automation. IEEE. [ bib | doi ]
[61]
Romain Lagneau, Alexandre Krupa, and Maud Marchal. Automatic shape control of deformable wires based on model-free visual servoing. IEEE Robotics and Automation Letters, 5:5252--5259. [ bib | doi ]