Learning inverse dynamics models with contacts
暂无分享,去创建一个
Jan Peters | Serena Ivaldi | Marc Peter Deisenroth | Roberto Calandra | Elmar A. Rückert | Jan Peters | M. Deisenroth | R. Calandra | E. Rückert | S. Ivaldi
[1] Oussama Khatib,et al. Springer Handbook of Robotics , 2007, Springer Handbooks.
[2] Vincent Padois,et al. Tools for simulating humanoid robot dynamics: A survey based on user feedback , 2014, 2014 IEEE-RAS International Conference on Humanoid Robots.
[3] Giulio Sandini,et al. Computing robot internal/external wrenches by means of inertial, tactile and F/T sensors: Theory and implementation on the iCub , 2011, 2011 11th IEEE-RAS International Conference on Humanoid Robots.
[4] Stefan Schaal,et al. Locally Weighted Projection Regression: Incremental Real Time Learning in High Dimensional Space , 2000, ICML.
[5] Gentiane Venture,et al. Dynamic parameters identification of a humanoid robot using joint torque sensors and/or contact forces , 2014, 2014 IEEE-RAS International Conference on Humanoid Robots.
[6] Katsu Yamane,et al. Practical kinematic and dynamic calibration methods for force-controlled humanoid robots , 2011, 2011 11th IEEE-RAS International Conference on Humanoid Robots.
[7] Shuuji Kajita,et al. Legged Robots , 2008, Springer Handbook of Robotics.
[8] Jan Peters,et al. Toward fast policy search for learning legged locomotion , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[9] Giulio Sandini,et al. An embedded artificial skin for humanoid robots , 2008, 2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems.
[10] Marc Toussaint,et al. Learning discontinuities with products-of-sigmoids for switching between local models , 2005, ICML.
[11] Giulio Sandini,et al. Force feedback exploiting tactile and proximal force/torque sensing , 2012, Auton. Robots.
[12] Giulio Sandini,et al. The iCub Platform: A Tool for Studying Intrinsically Motivated Learning , 2013, Intrinsically Motivated Learning in Natural and Artificial Systems.
[13] Olivier Stasse,et al. METAPOD — Template META-programming applied to dynamics: CoP-CoM trajectories filtering , 2014, 2014 IEEE-RAS International Conference on Humanoid Robots.
[14] Advait Jain,et al. Reaching in clutter with whole-arm tactile sensing , 2013, Int. J. Robotics Res..
[15] Lorenzo Molinari Tosatti,et al. Robot-dynamic calibration improvement by local identification , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).
[16] Giorgio Metta,et al. Control of contact forces: The role of tactile feedback for contact localization , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[17] Jan Peters,et al. Model learning for robot control: a survey , 2011, Cognitive Processing.
[18] G. Oriolo,et al. Robotics: Modelling, Planning and Control , 2008 .
[19] Advait Jain,et al. Manipulation in Clutter with Whole-Arm Tactile Sensing , 2013, ArXiv.
[20] Carl E. Rasmussen,et al. Gaussian Processes for Data-Efficient Learning in Robotics and Control , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[21] Duy Nguyen-Tuong,et al. Local Gaussian Process Regression for Real Time Online Model Learning , 2008, NIPS.
[22] Jan Peters,et al. Bayesian Gait Optimization for Bipedal Locomotion , 2014, LION.
[23] Riccardo Muradore,et al. Inertial parameter identification including friction and motor dynamics , 2014, 2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids).
[24] Marc H. Raibert,et al. Legged robots , 1986, CACM.
[25] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[26] Carl E. Rasmussen,et al. Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.
[27] Emanuel Todorov,et al. Trajectory optimization for domains with contacts using inverse dynamics , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[28] Fulvio Mastrogiovanni,et al. Skin spatial calibration using force/torque measurements , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.