暂无分享,去创建一个
[1] Jiajun Wu,et al. Unsupervised Learning of Latent Physical Properties Using Perception-Prediction Networks , 2018, UAI.
[2] Jiajun Wu,et al. Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning , 2015, NIPS.
[3] Abhinav Gupta,et al. Environment Probing Interaction Policies , 2019, ICLR.
[4] J. Andrew Bagnell,et al. Perceiving, learning, and exploiting object affordances for autonomous pile manipulation , 2013, Auton. Robots.
[5] J. Andrew Bagnell,et al. Interactive segmentation, tracking, and kinematic modeling of unknown 3D articulated objects , 2013, 2013 IEEE International Conference on Robotics and Automation.
[6] Alec Radford,et al. Proximal Policy Optimization Algorithms , 2017, ArXiv.
[7] Jiajun Wu,et al. Learning to See Physics via Visual De-animation , 2017, NIPS.
[8] Jessica B. Hamrick,et al. Simulation as an engine of physical scene understanding , 2013, Proceedings of the National Academy of Sciences.
[9] Niloy J. Mitra,et al. Taking Visual Motion Prediction To New Heightfields , 2019, Comput. Vis. Image Underst..
[10] Wolfram Burgard,et al. Learning Kinematic Models for Articulated Objects , 2009, IJCAI.
[11] James R. Kubricht,et al. Intuitive Physics: Current Research and Controversies , 2017, Trends in Cognitive Sciences.
[12] Jitendra Malik,et al. Learning Visual Predictive Models of Physics for Playing Billiards , 2015, ICLR.
[13] Daniel L. K. Yamins,et al. Flexible Neural Representation for Physics Prediction , 2018, NeurIPS.
[14] Mario Fritz,et al. Visual Stability Prediction and Its Application to Manipulation , 2016, AAAI Spring Symposia.
[15] Oussama Khatib,et al. A unified approach for motion and force control of robot manipulators: The operational space formulation , 1987, IEEE J. Robotics Autom..
[16] Oliver Brock,et al. Interactive Perception of Articulated Objects , 2010, ISER.
[17] Jiajun Wu,et al. DensePhysNet: Learning Dense Physical Object Representations via Multi-step Dynamic Interactions , 2019, Robotics: Science and Systems.
[18] Abhinav Gupta,et al. The Curious Robot: Learning Visual Representations via Physical Interactions , 2016, ECCV.
[19] Razvan Pascanu,et al. Interaction Networks for Learning about Objects, Relations and Physics , 2016, NIPS.
[20] Wenbin Li,et al. Learning Manipulation under Physics Constraints with Visual Perception , 2019, ArXiv.
[21] Dare A. Baldwin,et al. Infants' ability to draw inferences about nonobvious object properties: evidence from exploratory play. , 1993, Child development.
[22] Katherine D. Kinzler,et al. Core knowledge. , 2007, Developmental science.
[23] Jessica B. Hamrick,et al. Inferring mass in complex scenes by mental simulation , 2016, Cognition.
[24] Abhinav Gupta,et al. Bounce and Learn: Modeling Scene Dynamics with Real-World Bounces , 2019, ICLR.
[25] Yong Yu,et al. Estimation of object inertia parameters on robot pushing operation , 2004, 2004 International Conference on Intelligent Mechatronics and Automation, 2004. Proceedings..
[26] Leslie Pack Kaelbling,et al. Augmenting Physical Simulators with Stochastic Neural Networks: Case Study of Planar Pushing and Bouncing , 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[27] Greg Turk,et al. Preparing for the Unknown: Learning a Universal Policy with Online System Identification , 2017, Robotics: Science and Systems.
[28] Abhinav Gupta,et al. Interpretable Intuitive Physics Model , 2018, ECCV.
[29] Sergey Levine,et al. Deep visual foresight for planning robot motion , 2016, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[30] Wolfram Burgard,et al. Learning to Singulate Objects using a Push Proposal Network , 2017, ISRR.
[31] Oliver Brock,et al. Learning to Manipulate Articulated Objects in Unstructured Environments Using a Grounded Relational Representation , 2008, Robotics: Science and Systems.
[32] Jason J. Corso,et al. Learning Kinematic Descriptions using SPARE: Simulated and Physical ARticulated Extendable dataset , 2018, ArXiv.
[33] Oliver Kroemer,et al. Maximally informative interaction learning for scene exploration , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[34] Jitendra Malik,et al. Learning to Poke by Poking: Experiential Learning of Intuitive Physics , 2016, NIPS.
[35] Laura Schulz,et al. The Efficiency of Infants' Exploratory Play Is Related to Longer-Term Cognitive Development , 2018, Front. Psychol..
[36] Jan Peters,et al. Model learning for robot control: a survey , 2011, Cognitive Processing.
[37] Jessica B. Hamrick. Internal physics models guide probabilistic judgments about object dynamics , 2011 .
[38] Joshua B. Tenenbaum,et al. A Compositional Object-Based Approach to Learning Physical Dynamics , 2016, ICLR.
[39] Karen Liu. Dynamic Animation and Robotics Toolkit , 2014 .
[40] Siddhartha S. Srinivasa,et al. DART: Dynamic Animation and Robotics Toolkit , 2018, J. Open Source Softw..