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[1] Lee E. Weiss,et al. Dynamic sensor-based control of robots with visual feedback , 1987, IEEE Journal on Robotics and Automation.
[2] Patrick Rives,et al. A new approach to visual servoing in robotics , 1992, IEEE Trans. Robotics Autom..
[3] Peter Corke,et al. VISUAL CONTROL OF ROBOT MANIPULATORS – A REVIEW , 1993 .
[4] Minoru Asada,et al. Versatile visual servoing without knowledge of true Jacobian , 1994, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94).
[5] Peter K. Allen,et al. Active, uncalibrated visual servoing , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.
[6] Geoffrey J. Gordon. Stable Function Approximation in Dynamic Programming , 1995, ICML.
[7] Peter I. Corke,et al. A tutorial on visual servo control , 1996, IEEE Trans. Robotics Autom..
[8] William J. Wilson,et al. Relative end-effector control using Cartesian position based visual servoing , 1996, IEEE Trans. Robotics Autom..
[9] Olac Fuentes,et al. Experimental evaluation of uncalibrated visual servoing for precision manipulation , 1997, Proceedings of International Conference on Robotics and Automation.
[10] E. Malis,et al. 2 1/2 D Visual Servoing , 1999 .
[11] Avinash C. Kak,et al. Vision for Mobile Robot Navigation: A Survey , 2002, IEEE Trans. Pattern Anal. Mach. Intell..
[12] Danica Kragic,et al. Survey on Visual Servoing for Manipulation , 2002 .
[13] G LoweDavid,et al. Distinctive Image Features from Scale-Invariant Keypoints , 2004 .
[14] Martin A. Riedmiller. Neural Fitted Q Iteration - First Experiences with a Data Efficient Neural Reinforcement Learning Method , 2005, ECML.
[15] Pierre Geurts,et al. Tree-Based Batch Mode Reinforcement Learning , 2005, J. Mach. Learn. Res..
[16] Shie Mannor,et al. A Tutorial on the Cross-Entropy Method , 2005, Ann. Oper. Res..
[17] Warren E. Dixon,et al. Homography-based visual servo tracking control of a wheeled mobile robot , 2006, IEEE Transactions on Robotics.
[18] François Chaumette,et al. Visual servo control. I. Basic approaches , 2006, IEEE Robotics & Automation Magazine.
[19] Christophe Collewet,et al. Visual servoing set free from image processing , 2008, 2008 IEEE International Conference on Robotics and Automation.
[20] Shie Mannor,et al. Regularized Fitted Q-Iteration for planning in continuous-space Markovian decision problems , 2009, 2009 American Control Conference.
[21] Christopher Hunt,et al. Notes on the OpenSURF Library , 2009 .
[22] Fei-Fei Li,et al. ImageNet: A large-scale hierarchical image database , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[23] Christophe Collewet,et al. Photometric Visual Servoing , 2011, IEEE Transactions on Robotics.
[24] Ethan Rublee,et al. ORB: An efficient alternative to SIFT or SURF , 2011, 2011 International Conference on Computer Vision.
[25] Martin A. Riedmiller,et al. Autonomous reinforcement learning on raw visual input data in a real world application , 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).
[26] Rs Roel Pieters,et al. Visual Servo Control , 2012 .
[27] Alex Graves,et al. Playing Atari with Deep Reinforcement Learning , 2013, ArXiv.
[28] 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).
[29] Éric Marchand,et al. Photometric visual servoing for omnidirectional cameras , 2013, Auton. Robots.
[30] Trevor Darrell,et al. Caffe: Convolutional Architecture for Fast Feature Embedding , 2014, ACM Multimedia.
[31] Vijay Kumar,et al. Vision-based control of a quadrotor for perching on lines , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).
[32] Trevor Darrell,et al. DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition , 2013, ICML.
[33] Richard M. Murray,et al. Bootstrapping bilinear models of Simple Vehicles , 2015, Int. J. Robotics Res..
[34] Sergey Levine,et al. Trust Region Policy Optimization , 2015, ICML.
[35] David Calvert,et al. Self-Learning Visual Servoing of Robot Manipulator Using Explanation-Based Fuzzy Neural Networks and Q-Learning , 2015, J. Intell. Robotic Syst..
[36] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[37] Martin A. Riedmiller,et al. Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images , 2015, NIPS.
[38] Honglak Lee,et al. Action-Conditional Video Prediction using Deep Networks in Atari Games , 2015, NIPS.
[39] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[40] Yuval Tassa,et al. Continuous control with deep reinforcement learning , 2015, ICLR.
[41] Yann LeCun,et al. Deep multi-scale video prediction beyond mean square error , 2015, ICLR.
[42] Jiajun Wu,et al. Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks , 2016, NIPS.
[43] Martial Hebert,et al. An Uncertain Future: Forecasting from Static Images Using Variational Autoencoders , 2016, ECCV.
[44] Michael Felsberg,et al. Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking , 2016, ECCV.
[45] Vladlen Koltun,et al. Multi-Scale Context Aggregation by Dilated Convolutions , 2015, ICLR.
[46] Luc Van Gool,et al. Dynamic Filter Networks , 2016, NIPS.
[47] Sergey Levine,et al. End-to-End Training of Deep Visuomotor Policies , 2015, J. Mach. Learn. Res..
[48] Antonio Torralba,et al. Generating Videos with Scene Dynamics , 2016, NIPS.
[49] Gabriel Kreiman,et al. Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning , 2016, ICLR.
[50] Omer Levy,et al. Published as a conference paper at ICLR 2018 S IMULATING A CTION D YNAMICS WITH N EURAL P ROCESS N ETWORKS , 2018 .