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Modern approaches to autonomous driving rely heavily on learned components trained with large amounts of human driving data via imitation learning.
ALVINN: an autonomous land vehicle in a neural network
Dean A. Pomerleau · 1989
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The dynamic window approach to collision avoidance
Dieter Fox, Wolfram Burgard, and Sebastian Thrun · 1997
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Rapidly-exploring random trees : a new tool for path planning
Steven M. LaValle · 1998
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Hierarchical reinforcement learning with the MAXQ value function decomposition
Thomas G. Dietterich · 1999
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Between mdps and semi-mdps: A framework for temporal abstraction in reinforcement learning
Richard S Sutton, Doina Precup, and Satinder Singh · 1999
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The stochastic motion roadmap: A sampling framework for planning with markov motion uncertainty
Ron Alterovitz, Thierry Siméon, and Ken Goldberg · 2008
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Differentially constrained mobile robot motion planning in state lattices
Mihail Pivtoraiko, Ross A Knepper, and Alonzo Kelly · 2009
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Lqr-trees: Feedback motion planning via sums-of-squares verification
Russ Tedrake, Ian R Manchester, Mark Tobenkin, and John W Roberts · 2010
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Hierarchical task and motion planning in the now
Leslie Pack Kaelbling and Tomás Lozano-Pérez · 2011
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A reduction of imitation learning and structured prediction to no-regret online learning, 2011
Stephane Ross, Geoffrey J. Gordon, and J. Andrew Bagnell · 2011
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Efficient optimization of control libraries
Debadeepta Dey, Tian Liu, Boris Sofman, and James Bagnell · 2012
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Policy gradient for coherent risk measures
Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh, and Shie Mannor · 2015
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End to end learning for self-driving cars, 2016
Mariusz Bojarski, Davide Del Testa, Daniel Dworakowski, Bernhard Firner, Beat Flepp, Prasoon Goyal, Lawrence D. Jackel, Mathew Monfort, Urs Muller, Jiakai Zhang, Xin Zhang, Jake Zhao, and Karol Zieba · 2016
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Constrained policy optimization
Joshua Achiam, David Held, Aviv Tamar, and Pieter Abbeel · 2017
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Multi-step reinforcement learning: A unifying algorithm
Kristopher De Asis, Fernando Hernandez-Garcia, Zach Holland, and Richard S. Sutton · 2017
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Safe trajectory synthesis for autonomous driving in unforeseen environments
Shreyas Kousik, Sean Vaskov, Matthew Johnson-Roberson, and Ram Vasudevan · 2017
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Funnel libraries for real-time robust feedback motion planning
Anirudha Majumdar and Russ Tedrake · 2017
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Frustum pointnets for 3d object detection from RGB-D data
Charles Ruizhongtai Qi, Wei Liu, Chenxia Wu, Hao Su, and Leonidas J. Guibas · 2017
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Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Voxelnet: End-to-end learning for point cloud based 3d object detection
Yin Zhou and Oncel Tuzel · 2017
TNT: target-driven trajectory prediction
Hang Zhao, Jiyang Gao, Tian Lan, Chen Sun, Benjamin Sapp, Balakrishnan Varadarajan, Yue Shen, Yi Shen, Yuning Chai, Cordelia Schmid, Congcong Li, and Dragomir Anguelov · 2020
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Constrained Markov decision processes
Eitan Altman · 2021
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Offline reinforcement learning with implicit q-learning
Ilya Kostrikov, Ashvin Nair, and Sergey Levine · 2021
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Multipath++: Efficient information fusion and trajectory aggregation for behavior prediction, 2021
Balakrishnan Varadarajan, Ahmed Hefny, Avikalp Srivastava, Khaled S. Refaat, Nigamaa Nayakanti, Andre Cornman, Kan Chen, Bertrand Douillard, Chi Pang Lam, Dragomir Anguelov, and Benjamin Sapp · 2021
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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, and Angela P Schoellig · 2022
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Cited alongside, same era.
Safe reinforcement learning via shielding
Mohammed Alshiekh, Roderick Bloem, Rüdiger Ehlers, Bettina Könighofer, Scott Niekum, and Ufuk Topcu · 2018
Cited alongside, same era.
End-to-end driving via conditional imitation learning, 2018
Felipe Codevilla, Matthias Müller, Antonio López, Vladlen Koltun, and Alexey Dosovitskiy · 2018
Cited alongside, same era.
Soft actor-critic algorithms and applications
Tuomas Haarnoja, Aurick Zhou, Kristian Hartikainen, George Tucker, Sehoon Ha, Jie Tan, Vikash Kumar, Henry Zhu, Abhishek Gupta, Pieter Abbeel, and Sergey Levine · 2018
Cited alongside, same era.
Reward constrained policy optimization
Chen Tessler, Daniel J. Mankowitz, and Shie Mannor · 2018
Cited alongside, same era.
Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction
Yuning Chai, Benjamin Sapp, Mayank Bansal, and Dragomir Anguelov · 2019
Cited alongside, same era.
Soft actor-critic for discrete action settings
Petros Christodoulou · 2019
Cited alongside, same era.
Learning to drive in a day
Alex Kendall, Jeffrey Hawke, David Janz, Przemyslaw Mazur, Daniele Reda, John-Mark Allen, Vinh-Dieu Lam, Alex Bewley, and Amar Shah · 2019
Cited alongside, same era.
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Efficient risk-averse reinforcement learning
Ido Greenberg, Yinlam Chow, Mohammad Ghavamzadeh, and Shie Mannor · 2022
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Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers, 2022
Zhiqi Li, Wenhai Wang, Hongyang Li, Enze Xie, Chonghao Sima, Tong Lu, Qiao Yu, and Jifeng Dai · 2022
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Wayformer: Motion forecasting via simple and efficient attention networks, 2022
Nigamaa Nayakanti, Rami Al-Rfou, Aurick Zhou, Kratarth Goel, Khaled S. Refaat, and Benjamin Sapp · 2022
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Motion transformer with global intention localization and local movement refinement
Shaoshuai Shi, Li Jiang, Dengxin Dai, and Bernt Schiele · 2022
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Waymax: An accelerated, data-driven simulator for large-scale autonomous driving research, 2023
Cole Gulino, Justin Fu, Wenjie Luo, George Tucker, Eli Bronstein, Yiren Lu, Jean Harb, Xinlei Pan, Yan Wang, Xiangyu Chen, John D. Co-Reyes, Rishabh Agarwal, Rebecca Roelofs, Yao Lu, Nico Montali, Paul Mougin, Zoey Yang, Brandyn White, Aleksandra Faust, Rowan McAllister, Dragomir Anguelov, and Benjamin Sapp · 2023
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Imitation is not enough: Robustifying imitation with reinforcement learning for challenging driving scenarios, 2023
Yiren Lu, Justin Fu, George Tucker, Xinlei Pan, Eli Bronstein, Rebecca Roelofs, Benjamin Sapp, Brandyn White, Aleksandra Faust, Shimon Whiteson, Dragomir Anguelov, and Sergey Levine · 2023
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Mtr++: Multi-agent motion prediction with symmetric scene modeling and guided intention querying
Shaoshuai Shi, Li Jiang, Dengxin Dai, and Bernt Schiele · 2023
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Robust feedback motion planning via contraction theory
Sumeet Singh, Benoit Landry, Anirudha Majumdar, Jean-Jacques Slotine, and Marco Pavone · 2023
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Multi-constraint safe rl with objective suppression for safety-critical applications, 2024
Zihan Zhou, Jonathan Booher, Khashayar Rohanimanesh, Wei Liu, Aleksandr Petiushko, and Animesh Garg · 2024
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