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This work studies the problem of stochastic dynamic filtering and state propagation with complex beliefs.
Nonlinear bayesian estimation using gaussian sum approximations
Alspach, D., Sorenson, H.: · 1972
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Mechanics and Planning of Manipulator Pushing Operations
Mason, M.T.: · 1986
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Planar Sliding with Dry Friction Part 1 . Limit Surface and Moment Function
Goyal, S., Ruina, A., Papadopoulos, J.: · 1991
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Monte carlo filter and smoother for non-gaussian nonlinear state space models
Kitagawa, G.: · 1996
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Stable Pushing: Mechanics, Controllability, and Planning
Lynch, K.M., Mason, M.T.: · 1996
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Nonlinear adaptive control using nonparametric gaussian process prior models
Murray-Smith, R., Sbarbaro, D.: · 2002
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Gaussian sum particle filtering
Kotecha, J., Djuric, P.: · 2003
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Multiple hypothesis tracking for multiple target tracking
Blackman, S.S.: · 2004
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Dynamic systems identification with gaussian processes
Kocijan, J., Girard, A., Banko, B., Murray-Smith, R.: · 2005
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Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)
Thrun, S., Burgard, W., Fox, D.: · 2005
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Gaussian Processes for Machine Learning
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Nonlinear system identification: From multiple-model networks to gaussian processes
Gregorčič, G., Lightbody, G.: · 2008
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Analytic moment-based gaussian process filtering
Deisenroth, M., Huber, M., Hanebeck, U.: · 2009
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Gp-bayesfilters: Bayesian filtering using gaussian process prediction and observation models
Ko, J., Fox, D.: · 2009
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Push-Grasping with Dexterous Hands: Mechanics and a Method
Dogar, M.R., Srinivasa, S.S.: · 2010
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A Data-Driven Statistical Framework for Post-Grasp Manipulation
Paolini, R., Rodriguez, A., Srinivasa, S.S., Mason, M.T.: · 2014
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More than a Million Ways to be Pushed. A High-Fidelity Experimental Data Set of Planar Pushing
Yu, K.T., Bauza, M., Fazeli, N., Rodriguez, A.: · 2016
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Gaussian process motion planning
Mukadam, M., Yan, X., Boots, B.: · 2016
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A probabilistic data-driven model for planar pushing
Bauza, M., Rodriguez, A.: · 2017
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Empirical Evaluation of Common Impact Models on a Planar Impact Task
Fazeli, N., Donlon, E., Drumwright, E., Rodriguez, A.: · 2017
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Prediction under uncertainty in sparse spectrum gaussian processes with applications to filtering and control
Pan, Y., Yan, X.: · 2017
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Dynamical systems identification using gaussian process models with incorporated local models
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Bridging the ensemble kalman filter and particle filters: the adaptive gaussian mixture filter
Stordal, A.S., Karlsen, H.A., Nævdal, G., Skaug, H.J., Vallès, B.: · 2011
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Learning to control a low-cost manipulator using data-efficient reinforcement learning
Deisenroth, M., Rasmussen, C., Fox, D.: · 2012
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Koval, M.C., Klingensmith, M., Srinivasa, S.S., Pollard, N.S., Kaess, M.: · 2017
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Friction variability in planar pushing data: Anisotropic friction and data-collection bias
Ma, D., Rodriguez, A.: · 2018
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Nguyen-Tuong, D., Seeger, M., Peters, J.: · 2034
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