| On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2021 | 1545 | 2021 |
| Data-driven grasp synthesis—a survey J Bohg, A Morales, T Asfour, D Kragic IEEE Transactions on robotics 30 (2), 289-309, 2013 | 1083 | 2013 |
| Making sense of vision and touch: Learning multimodal representations for contact-rich tasks MA Lee, Y Zhu, P Zachares, M Tan, K Srinivasan, S Savarese, L Fei-Fei, ... IEEE Transactions on Robotics 36 (3), 582-596, 2020 | 441* | 2020 |
| Leveraging big data for grasp planning D Kappler, J Bohg, S Schaal 2015 IEEE international conference on robotics and automation (ICRA), 4304-4311, 2015 | 285 | 2015 |
| Interactive perception: Leveraging action in perception and perception in action J Bohg, K Hausman, B Sankaran, O Brock, D Kragic, S Schaal, ... IEEE Transactions on Robotics 33 (6), 1273-1291, 2017 | 284 | 2017 |
| Learning grasping points with shape context J Bohg, D Kragic Robotics and Autonomous Systems 58 (4), 362-377, 2010 | 218* | 2010 |
| Meteornet: Deep learning on dynamic 3d point cloud sequences X Liu, M Yan, J Bohg Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 187 | 2019 |
| Automatic LQR tuning based on Gaussian process global optimization A Marco, P Hennig, J Bohg, S Schaal, S Trimpe 2016 IEEE international conference on robotics and automation (ICRA), 270-277, 2016 | 161 | 2016 |
| Opengrasp: a toolkit for robot grasping simulation B León, S Ulbrich, R Diankov, G Puche, M Przybylski, A Morales, T Asfour, ... Simulation, Modeling, and Programming for Autonomous Robots: Second …, 2010 | 161 | 2010 |
| Variable impedance control in end-effector space: An action space for reinforcement learning in contact-rich tasks R Martín-Martín, MA Lee, R Gardner, S Savarese, J Bohg, A Garg 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019 | 159 | 2019 |
| Learning of grasp selection based on shape-templates A Herzog, P Pastor, M Kalakrishnan, L Righetti, J Bohg, T Asfour, ... Autonomous Robots 36, 51-65, 2014 | 146 | 2014 |
| Mind the gap-robotic grasping under incomplete observation J Bohg, M Johnson-Roberson, B León, J Felip, X Gratal, N Bergström, ... 2011 IEEE international conference on robotics and automation, 686-693, 2011 | 126 | 2011 |
| Probabilistic 3d multi-object tracking for autonomous driving H Chiu, A Prioletti, J Li, J Bohg arXiv preprint arXiv:2001.05673, 2020 | 122 | 2020 |
| Self-supervised learning of state estimation for manipulating deformable linear objects M Yan, Y Zhu, N Jin, J Bohg IEEE robotics and automation letters 5 (2), 2372-2379, 2020 | 120 | 2020 |
| Concept2Robot: Learning Manipulation Concepts from Instructions and Human Demonstrations JB Lin Shao, Toki Migimatsu, Qiang Zhang, Kaiyuan Yang Robotics: Science and Systems, 2020 | 116* | 2020 |
| Three-dimensional object reconstruction of symmetric objects by fusing visual and tactile sensing J Ilonen, J Bohg, V Kyrki The International Journal of Robotics Research 33 (2), 321-341, 2014 | 110* | 2014 |
| Combining learned and analytical models for predicting action effects A Kloss, S Schaal, J Bohg arXiv preprint arXiv:1710.04102 11, 2017 | 94* | 2017 |
| Vision-only robot navigation in a neural radiance world M Adamkiewicz, T Chen, A Caccavale, R Gardner, P Culbertson, J Bohg, ... IEEE Robotics and Automation Letters 7 (2), 4606-4613, 2022 | 86 | 2022 |
| Probabilistic object tracking using a range camera M Wüthrich, P Pastor, M Kalakrishnan, J Bohg, S Schaal 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2013 | 86 | 2013 |
| Real-time perception meets reactive motion generation D Kappler, F Meier, J Issac, J Mainprice, CG Cifuentes, M Wüthrich, ... IEEE Robotics and Automation Letters 3 (3), 1864-1871, 2018 | 82 | 2018 |
Stefan SchaalRobotics, Machine Learning, AI, NeuroscienceVerified email at google.com
