暂无分享,去创建一个
[1] Scott Niekum,et al. Efficient Hierarchical Robot Motion Planning Under Uncertainty and Hybrid Dynamics , 2018, CoRL.
[2] Marc Toussaint,et al. Hierarchical POMDP Controller Optimization by Likelihood Maximization , 2008, UAI.
[3] Leslie Pack Kaelbling,et al. LQR-RRT*: Optimal sampling-based motion planning with automatically derived extension heuristics , 2012, 2012 IEEE International Conference on Robotics and Automation.
[4] Sergey Levine,et al. Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning , 2019, CoRL.
[5] Oliver Kroemer,et al. A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms , 2019, J. Mach. Learn. Res..
[6] Michael Gleicher,et al. Recognizing Geometric Constraints in Human Demonstrations Using Force and Position Signals , 2018, IEEE Robotics and Automation Letters.
[7] A. Lynn Abbott,et al. Category-Level Articulated Object Pose Estimation , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[8] Leslie Pack Kaelbling,et al. Continuous-State POMDPs with Hybrid Dynamics , 2008, ISAIM.
[9] P. Fearnhead,et al. On‐line inference for multiple changepoint problems , 2007 .
[10] Christopher G. Atkeson,et al. Online Bayesian changepoint detection for articulated motion models , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).
[11] Oliver Brock,et al. Online interactive perception of articulated objects with multi-level recursive estimation based on task-specific priors , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[12] Oliver Brock,et al. Manipulating articulated objects with interactive perception , 2008, 2008 IEEE International Conference on Robotics and Automation.
[13] Pieter Abbeel,et al. Prediction and Control with Temporal Segment Models , 2017, ICML.
[14] Stefanie Tellex,et al. Learning to Generalize Kinematic Models to Novel Objects , 2019, CoRL.
[15] Julie A. Shah,et al. C-LEARN: Learning geometric constraints from demonstrations for multi-step manipulation in shared autonomy , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[16] Wolfram Burgard,et al. A Probabilistic Framework for Learning Kinematic Models of Articulated Objects , 2011, J. Artif. Intell. Res..
[17] John N. Tsitsiklis,et al. The Complexity of Markov Decision Processes , 1987, Math. Oper. Res..
[18] Gaurav S. Sukhatme,et al. Active articulation model estimation through interactive perception , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).
[19] Faramarz Fekri,et al. Accelerating Reinforcement Learning Agent with EEG-based Implicit Human Feedback , 2020, ArXiv.
[20] Dieter Fox,et al. SE3-nets: Learning rigid body motion using deep neural networks , 2016, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[21] Matthew R. Walter,et al. Learning Articulated Motions From Visual Demonstration , 2014, Robotics: Science and Systems.
[22] Andrew Zisserman,et al. MLESAC: A New Robust Estimator with Application to Estimating Image Geometry , 2000, Comput. Vis. Image Underst..
[23] Danica Kragic,et al. SimTrack: A simulation-based framework for scalable real-time object pose detection and tracking , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[24] Joelle Pineau,et al. Policy-contingent abstraction for robust robot control , 2002, UAI.
[25] Sergey Levine,et al. Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning , 2017, 2018 IEEE International Conference on Robotics and Automation (ICRA).
[26] Martin A. Riedmiller,et al. Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images , 2015, NIPS.
[27] Sergey Levine,et al. One-shot learning of manipulation skills with online dynamics adaptation and neural network priors , 2015, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[28] Oliver Brock,et al. Coupled recursive estimation for online interactive perception of articulated objects , 2019, Int. J. Robotics Res..
[29] 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.
[30] Wolfram Burgard,et al. Learning Kinematic Models for Articulated Objects , 2009, IJCAI.
[31] Nolan Wagener,et al. Learning contact-rich manipulation skills with guided policy search , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).
[32] Michael Gleicher,et al. Inferring geometric constraints in human demonstrations , 2018, CoRL.
[33] Franziska Meier,et al. SE3-Pose-Nets: Structured Deep Dynamics Models for Visuomotor Control , 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).
[34] Leslie Pack Kaelbling,et al. Interactive Bayesian identification of kinematic mechanisms , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).