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This paper presents an approach for learning vision-based planners that provably generalize to novel environments (i.e., environments unseen during training).
Some PAC-Bayesian theorems
D. A. McAllester · 1999
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Sequential composition of dynamically dexterous robot behaviors
R. R. Burridge, A. A. Rizzi, and D. E. Koditschek · 1999
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Randomized algorithms for robust controller synthesis using statistical learning theory
M. Vidyasagar · 2001
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A note on the PAC Bayesian theorem
A. Maurer · 2004
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Convex Optimization
S. Boyd and L. Vandenberghe · 2004
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Maneuver-based motion planning for nonlinear systems with symmetries
E. Frazzoli, M. A. Dahleh, and E. Feron · 2005
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Grasp planning in complex scenes
D. Berenson, R. Diankov, K. Nishiwaki, S. Kagami, and J. Kuffner · 2007
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Learning maneuver dictionaries for ground robot planning
P. Sermanet, M. Scoffier, C. Crudele, U. Muller, and Y. LeCun · 2008
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Standing balance control using a trajectory library
C. Liu and C. G. Atkeson · 2009
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Lqr-trees: Feedback motion planning via sums-of-squares verification
R. Tedrake, I. R. Manchester, M. Tobenkin, and J. W. Roberts · 2010
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Minimum snap trajectory generation and control for quadrotors
D. Mellinger and V. Kumar · 2011
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Natural evolution strategies
D. Wierstra, T. Schaul, T. Glasmachers, Y. Sun, J. Peters, and J. Schmidhuber · 2014
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Understanding Machine Learning: From Theory to Algorithms
S. Shalev-Shwartz and S. Ben-David · 2014
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Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2014
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Embed to control: A locally linear latent dynamics model for control from raw images
M. Watter, J. Springenberg, J. Boedecker, and M. Riedmiller · 2015
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Probabilistically valid stochastic extensions of deterministic models for systems with uncertainty
K. Karydis, I. Poulakakis, J. Sun, and H. G. Tanner · 2015
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End to end learning for self-driving cars
M. Bojarski, D. Del Testa, D. Dworakowski, B. Firner, B. Flepp, P. Goyal, L. D. Jackel, M. Monfort, U. Muller, et al · 2016
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Composing limit cycles for motion planning of 3d bipedal walkers
M. S. Motahar, S. Veer, and I. Poulakakis · 2016
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Visual foresight: Model-based deep reinforcement learning for vision-based robotic control
F. Ebert, C. Finn, S. Dasari, A. Xie, A. Lee, and S. Levine · 2018
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Recurrent world models facilitate policy evolution
D. Ha and J. Schmidhuber · 2018
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PAC-Bayes Control: synthesizing controllers that provably generalize to novel environments
A. Majumdar and M. Goldstein · 2018
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Pybullet, a python module for physics simulation for games, robotics and machine learning, 2018
E. Coumans and Y. Bai · 2018
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Robot motion planning in learned latent spaces
B. Ichter and M. Pavone · 2019
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Motion planning networks
A. H. Qureshi, A. Simeonov, M. J. Bency, and M. C. Yip · 2019
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Scenario Optimization for MPC , pages 445–463
M. C. Campi, S. Garatti, and M. Prandini · 2019
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O. Rivasplata, V. M. Tankasali, and C. Szepesvari · 2019
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