Accelerating Grasp Exploration by Leveraging Learned Priors
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Ashwin Balakrishna | Ken Goldberg | Vishal Satish | Michael Danielczuk | Han Yu Li | Ken Goldberg | V. Satish | Michael Danielczuk | A. Balakrishna | Han Yu Li
[1] Xinyu Liu,et al. Dex-Net 3.0: Computing Robust Robot Suction Grasp Targets in Point Clouds using a New Analytic Model and Deep Learning , 2017, ArXiv.
[2] Mathieu Aubry,et al. Dex-Net 1.0: A cloud-based network of 3D objects for robust grasp planning using a Multi-Armed Bandit model with correlated rewards , 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).
[3] Xinyu Liu,et al. Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics , 2017, Robotics: Science and Systems.
[4] Stefan Leutenegger,et al. Deep learning a grasp function for grasping under gripper pose uncertainty , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[5] Lihong Li,et al. An Empirical Evaluation of Thompson Sampling , 2011, NIPS.
[6] Peter Corke,et al. Closing the Loop for Robotic Grasping: A Real-time, Generative Grasp Synthesis Approach , 2018, Robotics: Science and Systems.
[7] Ashutosh Saxena,et al. Robotic Grasping of Novel Objects using Vision , 2008, Int. J. Robotics Res..
[8] Sergey Levine,et al. Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping , 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).
[9] Karol Hausman,et al. Quantile QT-Opt for Risk-Aware Vision-Based Robotic Grasping , 2019, Robotics: Science and Systems.
[10] Richard M. Murray,et al. A Mathematical Introduction to Robotic Manipulation , 1994 .
[11] Dinesh Manocha,et al. Deep Differentiable Grasp Planner for High-DOF Grippers , 2020, RSS 2020.
[12] Ken Goldberg,et al. Learning ambidextrous robot grasping policies , 2019, Science Robotics.
[13] M. Kendall. The treatment of ties in ranking problems. , 1945, Biometrika.
[14] Vijay Kumar,et al. Robotic grasping and contact: a review , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).
[15] Joel W. Burdick,et al. The Mechanics of Robot Grasping , 2019 .
[16] Sergey Levine,et al. Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection , 2016, Int. J. Robotics Res..
[17] Abhinav Gupta,et al. Supersizing self-supervision: Learning to grasp from 50K tries and 700 robot hours , 2015, 2016 IEEE International Conference on Robotics and Automation (ICRA).
[18] Honglak Lee,et al. Deep learning for detecting robotic grasps , 2013, Int. J. Robotics Res..
[19] Kate Saenko,et al. Learning a visuomotor controller for real world robotic grasping using simulated depth images , 2017, CoRL.
[20] Danica Kragic,et al. Data-Driven Grasp Synthesis—A Survey , 2013, IEEE Transactions on Robotics.
[21] G. G. Stokes. "J." , 1890, The New Yale Book of Quotations.
[22] Jeannette Bohg,et al. Leveraging big data for grasp planning , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).
[23] Sergey Levine,et al. QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation , 2018, CoRL.
[24] Ken Goldberg,et al. Adversarial Grasp Objects , 2019, 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE).
[25] M. Kendall. A NEW MEASURE OF RANK CORRELATION , 1938 .
[26] François Chaumette,et al. Grasping Unknown Objects by Coupling Deep Reinforcement Learning, Generative Adversarial Networks, and Visual Servoing , 2020, 2020 IEEE International Conference on Robotics and Automation (ICRA).
[27] Danica Kragic,et al. Multi-armed bandit models for 2D grasp planning with uncertainty , 2015, 2015 IEEE International Conference on Automation Science and Engineering (CASE).
[28] 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).