Learning Provably Robust Motion Planners Using Funnel Libraries

Learning Provably Robust Motion Planners Using Funnel Libraries

16 November 2021

Anirudha Majumdar

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Papers citing "Learning Provably Robust Motion Planners Using Funnel Libraries"

16 / 16 papers shown

Title
Safe Learning in Robotics: From Learning-Based Control to Safe Reinforcement Learning Lukas Brunke Melissa Greeff Adam W. Hall Zhaocong Yuan Siqi Zhou Jacopo Panerati Angela P. Schoellig OffRL 63 629 0 13 Aug 2021
Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning Rishabh Agarwal Marlos C. Machado Pablo Samuel Castro Marc G. Bellemare OffRL 96 168 0 13 Jan 2021
Backpropagation through Signal Temporal Logic Specifications: Infusing Logical Structure into Gradient-Based Methods Karen Leung Nikos Arechiga Marco Pavone 50 94 0 31 Jul 2020
Learning Invariant Representations for Reinforcement Learning without Reconstruction Amy Zhang R. McAllister Roberto Calandra Y. Gal Sergey Levine OOD SSL 114 478 0 18 Jun 2020
Invariant Policy Optimization: Towards Stronger Generalization in Reinforcement Learning Anoopkumar Sonar Vincent Pacelli Anirudha Majumdar 91 54 0 01 Jun 2020
Probably Approximately Correct Vision-Based Planning using Motion Primitives Sushant Veer Anirudha Majumdar 3DV 61 21 0 28 Feb 2020
Solving Rubik's Cube with a Robot Hand OpenAI Ilge Akkaya Marcin Andrychowicz Maciek Chociej Ma-teusz Litwin ... Peter Welinder Lilian Weng Qiming Yuan Wojciech Zaremba Lei Zhang ODL 121 1,232 0 16 Oct 2019
Improving Generalization in Meta Reinforcement Learning using Learned Objectives Louis Kirsch Sjoerd van Steenkiste Jürgen Schmidhuber OffRL 89 119 0 09 Oct 2019
PAC-Bayes Control: Learning Policies that Provably Generalize to Novel Environments Anirudha Majumdar M. Goldstein Anoopkumar Sonar 86 18 0 11 Jun 2018
A Study on Overfitting in Deep Reinforcement Learning Chiyuan Zhang Oriol Vinyals Rémi Munos Samy Bengio OffRL OnRL 59 391 0 18 Apr 2018
The Limits and Potentials of Deep Learning for Robotics Niko Sünderhauf Oliver Brock Walter J. Scheirer R. Hadsell Dieter Fox ... B. Upcroft Pieter Abbeel Wolfram Burgard Michael Milford Peter Corke 80 530 0 18 Apr 2018
Evolved Policy Gradients Rein Houthooft Richard Y. Chen Phillip Isola Bradly C. Stadie Filip Wolski Jonathan Ho Pieter Abbeel 98 227 0 13 Feb 2018
DARLA: Improving Zero-Shot Transfer in Reinforcement Learning I. Higgins Arka Pal Andrei A. Rusu Loic Matthey Christopher P. Burgess Alexander Pritzel M. Botvinick Charles Blundell Alexander Lerchner DRL 110 417 0 26 Jul 2017
Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data Gintare Karolina Dziugaite Daniel M. Roy 109 819 0 31 Mar 2017
Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World Joshua Tobin Rachel Fong Alex Ray Jonas Schneider Wojciech Zaremba Pieter Abbeel 259 2,972 0 20 Mar 2017
Monte Carlo Motion Planning for Robot Trajectory Optimization Under Uncertainty Lucas Janson Edward Schmerling Marco Pavone 80 102 0 30 Apr 2015

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