暂无分享,去创建一个
Thomas Lampe | Francesco Nori | Abbas Abdolmaleki | Martin Riedmiller | Markus Wulfmeier | Roland Hafner | Michael Neunert | Rae Jeong | Giulia Vezzani | Noah Siegel
[1] Ian Taylor,et al. Robotic pick-and-place of novel objects in clutter with multi-affordance grasping and cross-domain image matching , 2017, 2018 IEEE International Conference on Robotics and Automation (ICRA).
[2] Jakub W. Pachocki,et al. Learning dexterous in-hand manipulation , 2018, Int. J. Robotics Res..
[3] Sergey Levine,et al. QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation , 2018, CoRL.
[4] Marcin Andrychowicz,et al. Overcoming Exploration in Reinforcement Learning with Demonstrations , 2017, 2018 IEEE International Conference on Robotics and Automation (ICRA).
[5] Emanuel Todorov,et al. Reinforcement learning for non-prehensile manipulation: Transfer from simulation to physical system , 2018, 2018 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR).
[6] Oleg O. Sushkov,et al. Scaling data-driven robotics with reward sketching and batch reinforcement learning , 2019, Robotics: Science and Systems.
[7] Yuval Tassa,et al. Maximum a Posteriori Policy Optimisation , 2018, ICLR.
[8] Nando de Freitas,et al. Reinforcement and Imitation Learning for Diverse Visuomotor Skills , 2018, Robotics: Science and Systems.
[9] Jackie Kay,et al. Modelling Generalized Forces with Reinforcement Learning for Sim-to-Real Transfer , 2019, ArXiv.
[10] Wei Gao,et al. kPAM: KeyPoint Affordances for Category-Level Robotic Manipulation , 2019, ISRR.
[11] Oleg O. Sushkov,et al. A Practical Approach to Insertion with Variable Socket Position Using Deep Reinforcement Learning , 2018, 2019 International Conference on Robotics and Automation (ICRA).
[12] Russ Tedrake,et al. Self-Supervised Correspondence in Visuomotor Policy Learning , 2019, IEEE Robotics and Automation Letters.
[13] Sergey Levine,et al. Sim-To-Real via Sim-To-Sim: Data-Efficient Robotic Grasping via Randomized-To-Canonical Adaptation Networks , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[14] Martin A. Riedmiller,et al. Acquiring visual servoing reaching and grasping skills using neural reinforcement learning , 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).
[15] Martin A. Riedmiller,et al. Learning by Playing - Solving Sparse Reward Tasks from Scratch , 2018, ICML.
[16] Jan Peters,et al. Learning robot in-hand manipulation with tactile features , 2015, 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids).
[17] Sergey Levine,et al. Deep Reinforcement Learning for Industrial Insertion Tasks with Visual Inputs and Natural Reward Signals , 2019 .
[18] Sergey Levine,et al. Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations , 2017, Robotics: Science and Systems.
[19] Nikolaos G. Tsagarakis,et al. Detecting object affordances with Convolutional Neural Networks , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[20] Alberto Rodriguez,et al. Learning Synergies Between Pushing and Grasping with Self-Supervised Deep Reinforcement Learning , 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[21] Sergey Levine,et al. Deep Dynamics Models for Learning Dexterous Manipulation , 2019, CoRL.
[22] Martin A. Riedmiller,et al. Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning , 2020, ICLR.
[23] Jackie Kay,et al. Self-Supervised Sim-to-Real Adaptation for Visual Robotic Manipulation , 2019, 2020 IEEE International Conference on Robotics and Automation (ICRA).
[24] Sergey Levine,et al. Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection , 2016, Int. J. Robotics Res..
[25] Sergey Levine,et al. End-to-End Training of Deep Visuomotor Policies , 2015, J. Mach. Learn. Res..
[26] Marcin Andrychowicz,et al. Solving Rubik's Cube with a Robot Hand , 2019, ArXiv.
[27] Yuval Tassa,et al. MuJoCo: A physics engine for model-based control , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[28] Peter Englert,et al. Multi-task policy search for robotics , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).
[29] Henry Zhu,et al. Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost , 2018, 2019 International Conference on Robotics and Automation (ICRA).
[30] Wojciech Zaremba,et al. Domain randomization for transferring deep neural networks from simulation to the real world , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[31] Martin A. Riedmiller,et al. Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics , 2020, CoRL.