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]	A. Lahoud, E. Schaffernicht and J. A. Stork. DataSP : A Differential All-to-All Shortest Path Algorithm for Learning Costs and Predicting Paths with Context. In Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, pages 2094-2112, 2024 [ BibTeX \| DiVA \| PDF ]
[2]	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 ]
[3]	A. S. Khan, E. Schaffernicht and J. A. Stork. On the Effects of Irrelevant Variables in Treatment Effect Estimation with Deep Disentanglement. In 27th European Conference on Artificial Intelligence, 19–24 October 2024, Santiago de Compostela, Spain – Including 13th Conference on Prestigious Applications of Intelligent Systems (PAIS 2024), 392(392):2822-2829, 2024 [ BibTeX \| DiVA \| PDF ]
[4]	F. Rietz, E. Schaffernicht, S. Heinrich and J. A. Stork. Prioritized soft q-decomposition for lexicographic reinforcement learning. In 12th International Conference on Learning Representations, ICLR 2024 2024 [ BibTeX \| DiVA ]
[5]	Y. Yang, J. A. Stork and T. Stoyanov. Tracking Branched Deformable Linear Objects Using Particle Filtering on Depth Images. In 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE), pages 912-919, 2024 [ BibTeX \| DiVA \| PDF ]
[6]	F. Rietz and J. A. Stork. Diversity for Contingency : Learning Diverse Behaviors for Efficient Adaptation and Transfer. 2023 [ BibTeX \| DiVA ]
[7]	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 ]
[8]	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 ]
[9]	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 ]
[10]	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 ]
[11]	F. Rietz, E. Schaffernicht, T. Stoyanov and J. A. Stork. Towards Task-Prioritized Policy Composition. 2022 [ BibTeX \| DiVA ]
[12]	Q. Yang, J. A. Stork and T. Stoyanov. Transferring Knowledge for Reinforcement Learning in Contact-Rich Manipulation. 2022 [ BibTeX \| DiVA ]
[13]	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 ]
[14]	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 ]
[15]	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 ]
[16]	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 ]
[17]	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 ]
[18]	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 ]
[19]	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 ]
[20]	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 ]
[21]	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 ]
[22]	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 ]
[23]	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 ]
[24]	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 ]
[25]	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 ]
[26]	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 ]
[27]	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 ]
[28]	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 ]
[29]	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 ]
[30]	J. A. Stork, C. H. Ek and D. Kragic. Learning Predictive State Representations for planning. 2015 [ BibTeX \| DiVA ]
[31]	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 ]
[32]	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 ]
[33]	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 ]
[34]	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 ]
[35]	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 ]
[36]	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 ]
[37]	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 ]
[38]	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 ]
[39]	J. A. Stork, F. T. Pokorny and D. Kragic. Towards Postural Synergies for Caging Grasps. 2013 [ BibTeX \| DiVA ]
[40]	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 ]
[41]	J. A. Stork, J. Silva, L. Spinello and K. O. Arras. Audio-Based Human Activity Recognition with Robots. 2011 [ BibTeX \| DiVA ]
[42]	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.