Johannes Andreas Stork

…

Contact

Dr. Johannes Andreas Stork

AASS Research Centre
School of Science and Technology
Örebro University
70182 Örebro, Sweden
Room T1215
Phone +46 (0)19 30 39 40
johannesandreas.stork@oru.se

Publications

Journal Articles

[1]	D. C. Dominguez, M. Iannotta, J. A. Stork, E. Schaffernicht and T. Stoyanov. A Stack-of-Tasks Approach Combined With Behavior Trees : A New Framework for Robot Control. IEEE Robotics and Automation Letters, 7(4):12110-12117, 2022 [ BibTeX \| DiVA ]
[2]	Y. Yang, J. A. Stork and T. Stoyanov. Learning differentiable dynamics models for shape control of deformable linear objects. Robotics and Autonomous Systems, 158, 2022 [ BibTeX \| DiVA ]
[3]	J. A. Stork. Preparing to adapt is key for Olympic curling robots. Science robotics, 5(46), 2020 [ BibTeX \| DiVA ]
[4]	W. Yuan, K. Hang, D. Kragic, M. Y. Wang and J. A. Stork. End-to-end nonprehensile rearrangement with deep reinforcement learning and simulation-to-reality transfer. Robotics and Autonomous Systems, 119:119-134, 2019 [ BibTeX \| DiVA ]
[5]	K. Hang, X. Lyu, H. Song, J. A. Stork, A. Dollar, D. Kragic and F. Zhang. Perching and resting : A paradigm for UAV maneuvering with modularized landing gears. Science Robotics, 4(28), 2019 [ BibTeX \| DiVA ]
[6]	K. Hang, J. A. Stork, N. S. Pollard and D. Kragic. A Framework For Optimal Grasp Contact Planning. IEEE Robotics and Automation Letters, 2(2):704-711, 2017 [ BibTeX \| DiVA ]
[7]	K. Hang, M. Li, J. A. Stork, Y. Bekiroglu, F. T. Pokorny, A. Billard and D. Kragic. Hierarchical fingertip space : A unified framework for grasp planning and in-hand grasp adaptation. IEEE Transactions on robotics, 32(4):960-972, 2016 [ BibTeX \| DiVA ]

Refereed Conference and Workshop Articles

[1]	Y. Shih-Min, M. Magnusson, J. A. Stork and T. Stoyanov. Learning Extrinsic Dexterity with Parameterized Manipulation Primitives. In 2024 IEEE International Conference on Robotics and Automation (ICRA), pages 5404-5410, 2024 [ BibTeX \| DiVA \| PDF ]
[2]	F. Rietz and J. A. Stork. Diversity for Contingency : Learning Diverse Behaviors for Efficient Adaptation and Transfer. 2023 [ BibTeX \| DiVA ]
[3]	D. C. Hoang, J. A. Stork and T. Stoyanov. Context-Aware Grasp Generation in Cluttered Scenes. In 2022 International Conference on Robotics and Automation (ICRA), pages 1492-1498, 2022 [ BibTeX \| DiVA \| PDF ]
[4]	M. Iannotta, D. C. Dominguez, J. A. Stork, E. Schaffernicht and T. Stoyanov. Heterogeneous Full-body Control of a Mobile Manipulator with Behavior Trees. In IROS 2022 Workshop on Mobile Manipulation and Embodied Intelligence (MOMA): Challenges and Opportunities 2022 [ BibTeX \| DiVA \| PDF ]
[5]	Y. Yang, J. A. Stork and T. Stoyanov. Learn to Predict Posterior Probability in Particle Filtering for Tracking Deformable Linear Objects. In 3rd Workshop on Robotic Manipulation of Deformable Objects: Challenges in Perception, Planning and Control for Soft Interaction (ROMADO-SI), IROS 2022, Kyoto, Japan 2022 [ BibTeX \| DiVA \| PDF ]
[6]	Y. Yang, J. A. Stork and T. Stoyanov. Online Model Learning for Shape Control of Deformable Linear Objects. In 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 4056-4062, 2022 [ BibTeX \| DiVA \| PDF ]
[7]	F. Rietz, E. Schaffernicht, T. Stoyanov and J. A. Stork. Towards Task-Prioritized Policy Composition. 2022 [ BibTeX \| DiVA ]
[8]	Q. Yang, J. A. Stork and T. Stoyanov. Transferring Knowledge for Reinforcement Learning in Contact-Rich Manipulation. 2022 [ BibTeX \| DiVA ]
[9]	Q. Yang, A. Dürr, E. A. Topp, J. A. Stork and T. Stoyanov. Learning Impedance Actions for Safe Reinforcement Learning in Contact-Rich Tasks. In NeurIPS 2021 Workshop on Deployable Decision Making in Embodied Systems (DDM) 2021 [ BibTeX \| DiVA \| PDF ]
[10]	Y. Yang, J. A. Stork and T. Stoyanov. Learning to Propagate Interaction Effects for Modeling Deformable Linear Objects Dynamics. In 2021 IEEE International Conference on Robotics and Automation (ICRA) : IEEE International Conference on Robotics and Automation (ICRA 2021), Xi'an, China, May 30 - June 5, 2021, pages 1950-1957, 2021 [ BibTeX \| DiVA \| PDF ]
[11]	Q. Yang, J. A. Stork and T. Stoyanov. Null space based efficient reinforcement learning with hierarchical safety constraints. In 2021 European Conference on Mobile Robots (ECMR) 2021 [ BibTeX \| DiVA \| PDF ]
[12]	J. A. Stork and T. Stoyanov. Ensemble of Sparse Gaussian Process Experts for Implicit Surface Mapping with Streaming Data. In IEEE International Conference on Robotics and Automation, pages 10758-10764, 2020 [ BibTeX \| DiVA ]
[13]	H. Song, J. A. Haustein, W. Yuan, K. Hang, M. Y. Wang, D. Kragic and J. A. Stork. Multi-Object Rearrangement with Monte Carlo Tree Search : A Case Study on Planar Nonprehensile Sorting. , pages 9433-9440, 2020 [ BibTeX \| DiVA ]
[14]	A. Isac, C. J. Frederico, D. Kragic and J. A. Stork. The effect of Target Normalization and Momentum on Dying ReLU. In The 32nd annual workshop of the Swedish Artificial Intelligence Society (SAIS) 2020 [ BibTeX \| DiVA ]
[15]	I. Mitsioni, Y. Karayiannidis, J. A. Stork and D. Kragic. Data-Driven Model Predictive Control for the Contact-Rich Task of Food Cutting. In IEEE-RAS International Conference on Humanoid Robots, pages 244-250, 2019 [ BibTeX \| DiVA ]
[16]	J. A. Haustein, K. Hang, J. A. Stork and D. Kragic. Object Placement Planning and optimization for Robot Manipulators. In IEEE International Conference on Intelligent Robots and Systems, pages 7417-7424, 2019 [ BibTeX \| DiVA ]
[17]	W. Yuan, K. Hang, H. Song, D. Kragic, M. Y. Wang and J. A. Stork. Reinforcement Learning in Topology-based Representation for Human Body Movement with Whole Arm Manipulation. In 2019 International Conference on Robotics and Automation (ICRA), pages 2153-2160, 2019 [ BibTeX \| DiVA ]
[18]	I. Arnekvist, D. Kragic and J. A. Stork. VPE : Variational Policy Embedding for Transfer Reinforcement Learning. In 2019 International Conference on Robotics and Automation (ICRA), pages 36-42, 2019 [ BibTeX \| DiVA ]
[19]	R. Antonova, M. Kokic, J. A. Stork and D. Kragic. Global Search with Bernoulli Alternation Kernel for Task-oriented Grasping Informed by Simulation. In Proceedings of Machine Learning Research : Conference on Robot Learning 2018, 87:641-650, 2018 [ BibTeX \| DiVA ]
[20]	J. A. Haustein, I. Arnekvist, J. A. Stork, K. Hang and D. Kragic. Non-prehensile Rearrangement Planning with Learned Manipulation States and Actions. 2018 [ BibTeX \| DiVA ]
[21]	W. Yuan, J. A. Stork, D. Kragic, M. Y. Wang and K. Hang. Rearrangement with Nonprehensile Manipulation Using Deep Reinforcement Learning. In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages 270-277, 2018 [ BibTeX \| DiVA ]
[22]	M. Kokic, J. A. Stork, J. A. Haustein and D. Kragic. Affordance detection for task-specific grasping using deep learning. In 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids), pages 91-98, 2017 [ BibTeX \| DiVA ]
[23]	A. Thippur, J. A. Stork and P. Jensfelt. Non-Parametric Spatial Context Structure Learning for Autonomous Understanding of Human Environments. In 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pages 1317-1324, 2017 [ BibTeX \| DiVA ]
[24]	Y. Bekiroglu, A. Damianou, R. Detry, J. A. Stork, D. Kragic and C. H. Ek. Probabilistic consolidation of grasp experience. In 2016 IEEE International Conference on Robotics and Automation (ICRA), pages 193-200, 2016 [ BibTeX \| DiVA ]
[25]	J. A. Stork, C. H. Ek, Y. Bekiroglu and D. Kragic. Learning Predictive State Representation for In-Hand Manipulation. In 2015 IEEE International Conference on Robotics and Automation (ICRA), pages 3207-3214, 2015 [ BibTeX \| DiVA ]
[26]	J. A. Stork, C. H. Ek and D. Kragic. Learning Predictive State Representations for planning. In 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 3427-3434, 2015 [ BibTeX \| DiVA ]
[27]	J. A. Stork, C. H. Ek and D. Kragic. Learning Predictive State Representations for planning. 2015 [ BibTeX \| DiVA ]
[28]	K. Hang, J. A. Stork, F. T. Pokorny and D. Kragic. Combinatorial optimization for hierarchical contact-level grasping. In 2014 IEEE International Conference on Robotics and Automation (ICRA), pages 381-388, 2014 [ BibTeX \| DiVA ]
[29]	A. Marzinotto, J. A. Stork, D. V. Dimarogonas and D. Kragic. Cooperative grasping through topological object representation. In 2014 IEEE-RAS International Conference on Humanoid Robots, pages 685-692, 2014 [ BibTeX \| DiVA ]
[30]	K. Hang, J. A. Stork and D. Kragic. Hierarchical fingertip space for multi-fingered precision grasping. In 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 1641-1648, 2014 [ BibTeX \| DiVA ]
[31]	K. Hang, M. Li, J. A. Stork, Y. Bekiroglu, A. Billard and D. Kragic. Hierarchical Fingertip Space for Synthesizing Adaptable Fingertip Grasps. 2014 [ BibTeX \| DiVA ]
[32]	J. A. Stork, F. T. Pokorny and D. Kragic. A topology-based object representation for clasping, latching and hooking. In 2013 13TH IEEE-RAS INTERNATIONAL CONFERENCE ON HUMANOID ROBOTS (HUMANOIDS), pages 138-145, 2013 [ BibTeX \| DiVA ]
[33]	F. T. Pokorny, J. A. Stork and D. Kragic. Grasping Objects with Holes : A Topological Approach. In 2013 IEEE International Conference on Robotics and Automation, pages 1100-1107, 2013 [ BibTeX \| DiVA ]
[34]	J. A. Stork, F. T. Pokorny and D. Kragic. Integrated motion and clasp planning with virtual linking. In 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 3007-3014, 2013 [ BibTeX \| DiVA ]
[35]	J. A. Stork, F. T. Pokorny and D. Kragic. Towards Postural Synergies for Caging Grasps. 2013 [ BibTeX \| DiVA ]
[36]	J. A. Stork, L. Spinello, J. Silva and K. O. Arras. Audio-Based Human Activity Recognition Using Non-Markovian Ensemble Voting. In 2012 IEEE RO-MAN : The 21st IEEE International Symposium on Robot and Human Interactive Communication, pages 509-514, 2012 [ BibTeX \| DiVA ]
[37]	J. A. Stork, J. Silva, L. Spinello and K. O. Arras. Audio-Based Human Activity Recognition with Robots. 2011 [ BibTeX \| DiVA ]
[38]	M. Luber, J. A. Stork, G. D. Tipaldi and K. O. Arras. People tracking with human motion predictions from social forces. In 2010 IEEE International Conference on Robotics and Automation, Proceedings, pages 464-469, 2010 [ BibTeX \| DiVA ]

Find the complete BibTeX record here.