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Johannes Andreas Stork

Position: Senior Lecturer School/office: School of Science and Technology

Email: johannesandreas.stork@oru.se

Phone: +46 19 303940

Room: T1214

Research subject

Computer Science

Research environments

Centre for Applied Autonomous Sensor Systems (AASS)

About Johannes Andreas Stork

Johannes A. Stork is Associate Senior Lecturer and WASP Professor of machine learning at Örebro University and works at the Center for Applied Autonomous Sensor Systems (AASS). He joined the Autonomous Mobile Manipulation Lab (AMM) as a founding member. His main research interests are in machine learning and autonomous intelligent systems.

Starting spring of 2020 he is WASP Professor as part of the Wallenberg AI, Autonomous Systems and Software Program (WASP), Sweden’s largest ever individual research program and major national initiative for strategic basic research, education, and faculty recruitment. From 2018 to 2020, he held a position as Associate Senior Lecturer as part of the vice chancellor's strategic initiative for faculty development. Before joining AASS in 2018, he was a post-doctoral researcher and before that PhD. student in Computer Science (Computer Vision and Robotics) at the Computer Vision and Active Perception Lab (CVAP) at the Royal Institute of Technology (KTH) in Stockholm. He did his post-graduate research as a member of Professor Danica Kragic’s research group where his co-supervisors were Dr. Carl Henrik Ek and Dr. Yasemin Bekiroglu. Before that, he spent several years of his undergraduate studies at the University of Freiburg, Germany, as a student research assistant at the Social Robotics Lab of Professor Kai O. Arras. He holds a MSc. and a BSc. degree in Computer Science with concentration in Artificial Intelligence and Robotics from Freiburg University.

Active projects

Completed projects

Research groups

Adaptive and Interpretable Learning Systems

Publications

Articles in journals | Conference papers | Manuscripts | Reports |

Articles in journals

Rietz, F. , Magg, S. , Heintz, F. , Stoyanov, T. , Wermter, S. & Stork, J. A. (2023). Hierarchical goals contextualize local reward decomposition explanations. Neural Computing & Applications, 35 (23), 16693-16704.
Dominguez, D. C. , Iannotta, M. , Stork, J. A. , Schaffernicht, E. & Stoyanov, T. (2022). A Stack-of-Tasks Approach Combined With Behavior Trees: A New Framework for Robot Control. IEEE Robotics and Automation Letters, 7 (4), 12110-12117.
Yang, Y. , Stork, J. A. & Stoyanov, T. (2022). Learning differentiable dynamics models for shape control of deformable linear objects. Robotics and Autonomous Systems, 158.
Yang, Q. , Stork, J. A. & Stoyanov, T. (2022). MPR-RL: Multi-Prior Regularized Reinforcement Learning for Knowledge Transfer. IEEE Robotics and Automation Letters, 7 (3), 7652-7659.
Ivan, J. A. , Stoyanov, T. & Stork, J. A. (2022). Online Distance Field Priors for Gaussian Process Implicit Surfaces. IEEE Robotics and Automation Letters, 7 (4), 8996-9003.
Yang, Y. , Stork, J. A. & Stoyanov, T. (2022). Particle Filters in Latent Space for Robust Deformable Linear Object Tracking. IEEE Robotics and Automation Letters, 7 (4), 12577-12584.
Yang, Q. , Dürr, A. , Topp, E. A. , Stork, J. A. & Stoyanov, T. (2022). Variable Impedance Skill Learning for Contact-Rich Manipulation. IEEE Robotics and Automation Letters, 7 (3), 8391-8398.
Güler, P. , Stork, J. A. & Stoyanov, T. (2022). Visual state estimation in unseen environments through domain adaptation and metric learning. Frontiers in Robotics and AI, 9.
Hoang, D. , Stork, J. A. & Stoyanov, T. (2022). Voting and Attention-Based Pose Relation Learning for Object Pose Estimation From 3D Point Clouds. IEEE Robotics and Automation Letters, 7 (4), 8980-8987.
Stork, J. A. (2020). Preparing to adapt is key for Olympic curling robots. Science robotics, 5 (46).
Yuan, W. , Hang, K. , Kragic, D. , Wang, M. Y. & Stork, J. A. (2019). End-to-end nonprehensile rearrangement with deep reinforcement learning and simulation-to-reality transfer. Robotics and Autonomous Systems, 119, 119-134.
Hang, K. , Lyu, X. , Song, H. , Stork, J. A. , Dollar, A. , Kragic, D. & Zhang, F. (2019). Perching and resting: A paradigm for UAV maneuvering with modularized landing gears. Science Robotics, 4 (28).
Hang, K. , Stork, J. A. , Pollard, N. S. & Kragic, D. (2017). A Framework For Optimal Grasp Contact Planning. IEEE Robotics and Automation Letters, 2 (2), 704-711.
Hang, K. , Li, M. , Stork, J. A. , Bekiroglu, Y. , Pokorny, F. T. , Billard, A. & Kragic, D. (2016). Hierarchical fingertip space: A unified framework for grasp planning and in-hand grasp adaptation. IEEE Transactions on robotics, 32 (4), 960-972.

Conference papers

Rietz, F. & Stork, J. A. (2023). Diversity for Contingency: Learning Diverse Behaviors for Efficient Adaptation and Transfer. Paper presented at 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023), Detroit, MI, USA, October 1-5, 2023.
Yang, Q. , Stork, J. A. & Stoyanov, T. (2023). Learn from Robot: Transferring Skills for Diverse Manipulation via Cycle Generative Networks. In: 2023 IEEE 19th International Conference on Automation Science and Engineering (CASE). Paper presented at 19th International Conference on Automation Science and Engineering (IEEE CASE 2023), Cordis, Auckland, New Zealand, August 26-30, 2023. IEEE conference proceedings.
Hoang, D. , Stork, J. A. & Stoyanov, T. (2022). Context-Aware Grasp Generation in Cluttered Scenes. In: 2022 International Conference on Robotics and Automation (ICRA). Paper presented at IEEE International Conference on Robotics and Automation (ICRA 2022), Philadelphia, USA, May 23-27, 2022. (pp. 1492-1498). IEEE.
Iannotta, M. , Dominguez, D. C. , Stork, J. A. , Schaffernicht, E. & Stoyanov, T. (2022). 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. Paper presented at International Conference on Intelligent Robots and Systems (IROS 2022), Kyoto, Japan, October 23-27, 2022.
Yang, Y. , Stork, J. A. & Stoyanov, T. (2022). 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. Paper presented at 35th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022), Kyoto, Japan, October 24-26, 2022.
Yang, Y. , Stork, J. A. & Stoyanov, T. (2022). Online Model Learning for Shape Control of Deformable Linear Objects. In: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Paper presented at 35th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022), Kyoto, Japan, October 23-27, 2022. (pp. 4056-4062). IEEE.
Rietz, F. , Schaffernicht, E. , Stoyanov, T. & Stork, J. A. (2022). Towards Task-Prioritized Policy Composition. Paper presented at 35th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022), Kyoto, Japan, October 24-26, 2022.
Yang, Q. , Stork, J. A. & Stoyanov, T. (2022). Transferring Knowledge for Reinforcement Learning in Contact-Rich Manipulation. Paper presented at 2nd RL-CONFORM Workshop at IROS 2022, October 23, 2022.
Yang, Q. , Dürr, A. , Topp, E. A. , Stork, J. A. & Stoyanov, T. (2021). Learning Impedance Actions for Safe Reinforcement Learning in Contact-Rich Tasks. In: NeurIPS 2021 Workshop on Deployable Decision Making in Embodied Systems (DDM). Paper presented at NeurIPS 2021 Workshop on Deployable Decision Making in Embodied Systems (DDM), (Online conference), Sydney, Australia, December 6-14, 2021.
Yang, Y. , Stork, J. A. & Stoyanov, T. (2021). 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. Paper presented at IEEE International Conference on Robotics and Automation (ICRA 2021), Xi'an, China, May 30 - June 5, 2021. (pp. 1950-1957). IEEE.
Yang, Q. , Stork, J. A. & Stoyanov, T. (2021). Null space based efficient reinforcement learning with hierarchical safety constraints. In: 2021 European Conference on Mobile Robots (ECMR). Paper presented at European Conference on Mobile Robots (ECMR 2021), Virtual meeting, August 31 - September 3, 2021. IEEE.
Stork, J. A. & Stoyanov, T. (2020). Ensemble of Sparse Gaussian Process Experts for Implicit Surface Mapping with Streaming Data. In: IEEE International Conference on Robotics and Automation. Paper presented at 2020 IEEE International Conference on Robotics and Automation (ICRA), PAris, France, 31 May-31 August, 2020. (pp. 10758-10764). IEEE.
Song, H. , Haustein, J. A. , Yuan, W. , Hang, K. , Wang, M. Y. , Kragic, D. & Stork, J. A. (2020). Multi-Object Rearrangement with Monte Carlo Tree Search: A Case Study on Planar Nonprehensile Sorting. Paper presented at IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, NV, USA (Virtual), October 25-29, 2020. (pp. 9433-9440). IEEE Press.
Isac, A. , J. Frederico, C. , Kragic, D. & Stork, J. A. (2020). The effect of Target Normalization and Momentum on Dying ReLU. In: The 32nd annual workshop of the Swedish Artificial Intelligence Society (SAIS). Paper presented at The 32nd annual workshop of the Swedish Artificial Intelligence Society (SAIS), Gothenburg, Sweden (Virtual), June 16–17, 2020.
Mitsioni, I. , Karayiannidis, Y. , Stork, J. A. & Kragic, D. (2019). Data-Driven Model Predictive Control for the Contact-Rich Task of Food Cutting. In: IEEE-RAS International Conference on Humanoid Robots. Paper presented at IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids), Toronto, Canada, October 15-17, 2019. (pp. 244-250). IEEE Computer Society.
Haustein, J. A. , Hang, K. , Stork, J. A. & Kragic, D. (2019). Object Placement Planning and optimization for Robot Manipulators. In: IEEE International Conference on Intelligent Robots and Systems. Paper presented at 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, China, November 3-8, 2019. (pp. 7417-7424). Institute of Electrical and Electronics Engineers (IEEE).
Yuan, W. , Hang, K. , Song, H. , Kragic, D. , Wang, M. Y. & Stork, J. A. (2019). Reinforcement Learning in Topology-based Representation for Human Body Movement with Whole Arm Manipulation. In: Howard, A; Althoefer, K; Arai, F; Arrichiello, F; Caputo, B; Castellanos, J; Hauser, K; Isler, V; Kim, J; Liu, H; Oh, P; Santos, V; Scaramuzza, D; Ude, A; Voyles, R; Yamane, K; Okamura, A;, 2019 International Conference on Robotics and Automation (ICRA). Paper presented at International Conference on Robotics and Automation (ICRA), Montreal, Canada, May 20-24, 2019. (pp. 2153-2160). IEEE.
Arnekvist, I. , Kragic, D. & Stork, J. A. (2019). VPE: Variational Policy Embedding for Transfer Reinforcement Learning. In: Howard, A; Althoefer, K; Arai, F; Arrichiello, F; Caputo, B; Castellanos, J; Hauser, K; Isler, V Kim, J; Liu, H; Oh, P; Santos, V; Scaramuzza, D; Ude, A; Voyles, R; Yamane, K; Okamura, A, 2019 International Conference on Robotics and Automation (ICRA). Paper presented at International Conference on Robotics and Automation (ICRA), Montreal, Canada, May 20-24, 2019. (pp. 36-42). IEEE.
Antonova, R. , Kokic, M. , Stork, J. A. & Kragic, D. (2018). Global Search with Bernoulli Alternation Kernel for Task-oriented Grasping Informed by Simulation. In: Proceedings of Machine Learning Research Conference on Robot Learning 2018. Paper presented at The 2nd Conference on Robot Learning (CoRL), Zürich, Switzerland, October 29-31, 2018. (pp. 641-650). PMLR.
Haustein, J. A. , Arnekvist, I. , Stork, J. A. , Hang, K. & Kragic, D. (2018). Non-prehensile Rearrangement Planning with Learned Manipulation States and Actions. Paper presented at Workshop "Machine Learning in Robot Motion Planning" at International Conference on Intelligent Robots and Systems (IROS 2018), Madrid, Spain, October 1-5, 2018.
Yuan, W. , Stork, J. A. , Kragic, D. , Wang, M. Y. & Hang, K. (2018). Rearrangement with Nonprehensile Manipulation Using Deep Reinforcement Learning. In: 2018 IEEE International Conference on Robotics and Automation (ICRA). Paper presented at IEEE International Conference on Robotics and Automation, Brisbane, QLD, Australia, May 21-25, 2018. (pp. 270-277). IEEE conference proceedings.
Kokic, M. , Stork, J. A. , Haustein, J. A. & Kragic, D. (2017). Affordance detection for task-specific grasping using deep learning. In: 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids). Paper presented at IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids), Birmingham, UK, November 15-17, 2017. (pp. 91-98). IEEE conference proceedings.
Thippur, A. , Stork, J. A. & Jensfelt, P. (2017). 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). Paper presented at 26th IEEE International Symposium on Robot and Human Interactive Communication, Lisbon, Portugal, August 28 - September 1, 2018. (pp. 1317-1324). IEEE conference proceedings.
Bekiroglu, Y. , Damianou, A. , Detry, R. , Stork, J. A. , Kragic, D. & Ek, C. H. (2016). Probabilistic consolidation of grasp experience. In: 2016 IEEE International Conference on Robotics and Automation (ICRA). Paper presented at IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, May 16-21, 2016. (pp. 193-200). IEEE conference proceedings.
Stork, J. A. , Ek, C. H. , Bekiroglu, Y. & Kragic, D. (2015). Learning Predictive State Representation for In-Hand Manipulation. In: 2015 IEEE International Conference on Robotics and Automation (ICRA). Paper presented at IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, May 26-30, 2015. (pp. 3207-3214). IEEE conference proceedings.
Stork, J. A. , Ek, C. H. & Kragic, D. (2015). Learning Predictive State Representations for planning. In: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Paper presented at IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, September 28 - October 2, 2015. (pp. 3427-3434). IEEE Press.
Stork, J. A. , Ek, C. H. & Kragic, D. (2015). Learning Predictive State Representations for planning. Paper presented at International Conference on Robotics and Automation (ICRA), Seattle, Washington, USA, May 26-30, 2015.
Hang, K. , Stork, J. A. , Pokorny, F. T. & Kragic, D. (2014). Combinatorial optimization for hierarchical contact-level grasping. In: 2014 IEEE International Conference on Robotics and Automation (ICRA). Paper presented at IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, May 31 - June 7, 2014. (pp. 381-388). IEEE.
Marzinotto, A. , Stork, J. A. , Dimarogonas, D. V. & Kragic, D. (2014). Cooperative grasping through topological object representation. In: 2014 IEEE-RAS International Conference on Humanoid Robots. Paper presented at 14th IEEE-RAS International Conference on Humanoid Robots (Humanoids), Madrid, Spain, November 18-20, 2014. (pp. 685-692). IEEE.
Hang, K. , Stork, J. A. & Kragic, D. (2014). Hierarchical fingertip space for multi-fingered precision grasping. In: 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems. Paper presented at IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Chicago, IL, USA, September 14-18, 2014. (pp. 1641-1648). IEEE Press.
Hang, K. , Li, M. , Stork, J. A. , Bekiroglu, Y. , Billard, A. & Kragic, D. (2014). Hierarchical Fingertip Space for Synthesizing Adaptable Fingertip Grasps. Paper presented at International Conference on Robotics and Automation (ICRA), Hong Kong, China, May 31 - June 5, 2014.
Stork, J. A. , Pokorny, F. T. & Kragic, D. (2013). A topology-based object representation for clasping, latching and hooking. In: 2013 13TH IEEE-RAS INTERNATIONAL CONFERENCE ON HUMANOID ROBOTS (HUMANOIDS). Paper presented at IEEE-RAS International Conference on Humanoid Robots, Atlanta, United States, October 15-17, 2013. (pp. 138-145). IEEE conference proceedings.
Pokorny, F. T. , Stork, J. A. & Kragic, D. (2013). Grasping Objects with Holes: A Topological Approach. In: 2013 IEEE International Conference on Robotics and Automation. Paper presented at IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, May 6-10, 2013. (pp. 1100-1107). IEEE conference proceedings.
Stork, J. A. , Pokorny, F. T. & Kragic, D. (2013). Integrated motion and clasp planning with virtual linking. In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems. Paper presented at IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon (IROS 2013), Tokyo, Japan, November 3-8, 2013. (pp. 3007-3014). IEEE Press.
Stork, J. A. , Pokorny, F. T. & Kragic, D. (2013). Towards Postural Synergies for Caging Grasps. Paper presented at IEEE International Conference on Robotics and Automation (ICRA 2013): Hand Synergies - how to tame the complexity of grasping, Karlsruhe, Germany, May 6-10, 2013.
Stork, J. A. , Spinello, L. , Silva, J. & Arras, K. O. (2012). 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. Paper presented at 21st IEEE International Symposium on Robot and Human Interactive Communication, Paris, France, September 9-13, 2012. (pp. 509-514). IEEE conference proceedings.
Stork, J. A. , Silva, J. , Spinello, L. & Arras, K. O. (2011). Audio-Based Human Activity Recognition with Robots. Paper presented at International Conference on Social Robotics (ICSR), Amsterdam, The Netherlands, November 24-25, 2011.
Luber, M. , Stork, J. A. , Tipaldi, G. D. & Arras, K. O. (2010). People tracking with human motion predictions from social forces. In: 2010 IEEE International Conference on Robotics and Automation, Proceedings. Paper presented at IEEE International Conference on Robotics and Automation (ICRA), Anchorage, AK, USA, May 3-7, 2010. (pp. 464-469). IEEE conference proceedings.

Manuscripts

Haustein, J. A. , Arnekvist, I. , Stork, J. A. , Hang, K. & Kragic, D. Learning Manipulation States and Actions for Efficient Non-prehensile Rearrangement Planning.
Yuan, W. , Hang, K. , Song, H. , Kragic, D. , Wang, M. Y. & Stork, J. A. Reinforcement Learning in Topology-based Representation for Human Body Movement with Whole Arm Manipulation.
Arnekvist, I. , Kragic, D. & Stork, J. A. VPE: Variational Policy Embedding for Transfer Reinforcement Learning.
Mitsioni, I. , Karayiannidis, Y. , Stork, J. A. & Kragic, D. Data-Driven Model Predictive Control for Food-Cutting.
Song, H. , Haustein, J. A. , Yuan, W. , Hang, K. , Wang, M. Y. , Kragic, D. & Stork, J. A. Multi-Object Rearrangement with Monte Carlo Tree Search : A Case Study on Planar Nonprehensile Sorting.
Haustein, J. A. , Hang, K. , Stork, J. A. & Kragic, D. Object placement planning and optimization for robot manipulators.
Yang, Y. , Stork, J. A. & Stoyanov, T. Tracking Branched Deformable Linear Objects Using Particle Filtering on Depth Images.

Reports

Marzinotto, A. & Stork, J. A. (2016). Rope through Loop Insertion for Robotic Knotting: A Virtual Magnetic Field Formulation. Stockholm: .