Domain Randomization and Generative Models for Robotic Grasping
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[1] Van-Duc Nguyen,et al. Constructing force-closure grasps , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.
[2] Richard M. Murray,et al. A Mathematical Introduction to Robotic Manipulation , 1994 .
[3] Nick Jakobi,et al. Evolutionary Robotics and the Radical Envelope-of-Noise Hypothesis , 1997, Adapt. Behav..
[4] 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).
[5] Henrik I. Christensen,et al. Automatic grasp planning using shape primitives , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).
[6] Antonio Morales,et al. Using Experience for Assessing Grasp Reliability , 2004, Int. J. Humanoid Robotics.
[7] Peter K. Allen,et al. An SVM learning approach to robotic grasping , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.
[8] Peter K. Allen,et al. Graspit! A versatile simulator for robotic grasping , 2004, IEEE Robotics & Automation Magazine.
[9] Peter K. Allen,et al. Grasp Planning via Decomposition Trees , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.
[10] Manuel Lopes,et al. Learning Object Affordances: From Sensory--Motor Coordination to Imitation , 2008, IEEE Transactions on Robotics.
[11] Lawson L. S. Wong,et al. Learning Grasp Strategies with Partial Shape Information , 2008, AAAI.
[12] Ashutosh Saxena,et al. Robotic Grasping of Novel Objects using Vision , 2008, Int. J. Robotics Res..
[13] Matei T. Ciocarlie,et al. Towards Reliable Grasping and Manipulation in Household Environments , 2010, ISER.
[14] Quoc V. Le,et al. Learning to grasp objects with multiple contact points , 2010, 2010 IEEE International Conference on Robotics and Automation.
[15] Hugo Larochelle,et al. The Neural Autoregressive Distribution Estimator , 2011, AISTATS.
[16] Vincent Lepetit,et al. Multimodal templates for real-time detection of texture-less objects in heavily cluttered scenes , 2011, 2011 International Conference on Computer Vision.
[17] Pieter Abbeel,et al. Grasping and Fixturing as Submodular Coverage Problems , 2011, ISRR.
[18] Peter K. Allen,et al. Pose error robust grasping from contact wrench space metrics , 2012, 2012 IEEE International Conference on Robotics and Automation.
[19] Alberto Rodriguez,et al. From caging to grasping , 2011, Int. J. Robotics Res..
[20] Anis Sahbani,et al. An overview of 3D object grasp synthesis algorithms , 2012, Robotics Auton. Syst..
[21] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[22] Yuval Tassa,et al. MuJoCo: A physics engine for model-based control , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[23] Antonio Bicchi,et al. On the synthesis of feasible and prehensile robotic grasps , 2012, 2012 IEEE International Conference on Robotics and Automation.
[24] Hugo Larochelle,et al. A Neural Autoregressive Topic Model , 2012, NIPS.
[25] Antonio Bicchi,et al. On the manipulability ellipsoids of underactuated robotic hands with compliance , 2012, Robotics Auton. Syst..
[26] Kenneth Y. Goldberg,et al. Cloud-based robot grasping with the google object recognition engine , 2013, 2013 IEEE International Conference on Robotics and Automation.
[27] Pieter Abbeel,et al. Multimodal blending for high-accuracy instance recognition , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[28] Danica Kragic,et al. Data-Driven Grasp Synthesis—A Survey , 2013, IEEE Transactions on Robotics.
[29] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[30] Daan Wierstra,et al. Deep AutoRegressive Networks , 2013, ICML.
[31] Emanuel Todorov,et al. Ensemble-CIO: Full-body dynamic motion planning that transfers to physical humanoids , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[32] Honglak Lee,et al. Deep learning for detecting robotic grasps , 2013, Int. J. Robotics Res..
[33] Jitendra Malik,et al. Aligning 3D models to RGB-D images of cluttered scenes , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[34] Hugo Larochelle,et al. MADE: Masked Autoencoder for Distribution Estimation , 2015, ICML.
[35] Leonidas J. Guibas,et al. ShapeNet: An Information-Rich 3D Model Repository , 2015, ArXiv.
[36] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[37] Siddhartha S. Srinivasa,et al. The YCB object and Model set: Towards common benchmarks for manipulation research , 2015, 2015 International Conference on Advanced Robotics (ICAR).
[38] Alex Graves,et al. Conditional Image Generation with PixelCNN Decoders , 2016, NIPS.
[39] Koray Kavukcuoglu,et al. Pixel Recurrent Neural Networks , 2016, ICML.
[40] 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).
[41] Heiga Zen,et al. WaveNet: A Generative Model for Raw Audio , 2016, SSW.
[42] Kate Saenko,et al. Learning a visuomotor controller for real world robotic grasping using simulated depth images , 2017, CoRL.
[43] Kuan-Ting Yu,et al. Multi-view self-supervised deep learning for 6D pose estimation in the Amazon Picking Challenge , 2016, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[44] Anders Grunnet-Jepsen,et al. Intel RealSense Stereoscopic Depth Cameras , 2017, CVPR 2017.
[45] Kate Saenko,et al. Learning a visuomotor controller for real world robotic grasping using easily simulated depth images , 2017, ArXiv.
[46] 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.
[47] 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).
[48] Arkanath Pathak,et al. Learning Grasping Interaction with Geometry-aware 3D Representations , 2017, ArXiv.
[49] Peter I. Corke,et al. Sim-to-real Transfer of Visuo-motor Policies for Reaching in Clutter: Domain Randomization and Adaptation with Modular Networks , 2017, ArXiv.
[50] James Davidson,et al. Supervision via competition: Robot adversaries for learning tasks , 2016, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[51] Sergey Levine,et al. (CAD)$^2$RL: Real Single-Image Flight without a Single Real Image , 2016, Robotics: Science and Systems.
[52] Sergey Levine,et al. Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection , 2016, Int. J. Robotics Res..
[53] Arkanath Pathak,et al. Learning 6-DOF Grasping Interaction via Deep Geometry-Aware 3D Representations , 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).
[54] 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).
[55] 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.
[56] Michael Milford,et al. Adversarial discriminative sim-to-real transfer of visuo-motor policies , 2017, Int. J. Robotics Res..