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Guaranteeing safety of perception-based learning systems is challenging due to the absence of ground-truth state information unlike in state-aware control scenarios.
Alvinn: An autonomous land vehicle in a neural network
Dean A Pomerleau · 1989
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Nonlinear Systems
Hassan K. Khalil · 2002
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A framework for worst-case and stochastic safety verification using barrier certificates
Stephen Prajna, Ali Jadbabaie, and George J. Pappas · 2007
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Constructive safety using control barrier functions
Peter Wieland and Frank Allgöwer · 2007
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Viability theory
Jean-Pierre Aubin · 2009
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Barrier lyapunov functions for the control of output-constrained nonlinear systems
Keng Peng Tee, Shuzhi Sam Ge, and Eng Hock Tay · 2009
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Multi-objective control for multi-agent systems using lyapunov-like barrier functions
Dimitra Panagou, Dušan M. Stipanovič, and Petros G. Voulgaris · 2013
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Converse barrier certificate theorem
Rafael Wisniewski and Christoffer Sloth · 2013
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Control barrier function based quadratic programs with application to adaptive cruise control
Aaron D Ames, Jessy W Grizzle, and Paulo Tabuada · 2014
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An efficient minimum-time trajectory generation strategy for two-track car vehicles
Alessandro Rucco, Giuseppe Notarstefano, and John Hauser · 2015
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End to end learning for self-driving cars
Mariusz Bojarski, Davide Del Testa, Daniel Dworakowski, Bernhard Firner, Beat Flepp, Prasoon Goyal, Lawrence D Jackel, Mathew Monfort, Urs Muller, Jiakai Zhang, et al · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Exponential control barrier functions for enforcing high relative-degree safety-critical constraints
Quan Nguyen and Koushil Sreenath · 2016
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Optnet: Differentiable optimization as a layer in neural networks
Brandon Amos and J. Zico Kolter · 2017
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Sensor Fusion for Robot Control through Deep Reinforcement Learning
Steven Bohez, Tim Verbelen, Elias De Coninck, Bert Vankeirsbilck, Pieter Simoens, and Bart Dhoedt · 2017
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Sensor Modality Fusion with CNNs for UGV Autonomous Driving in Indoor Environments
Naman Patel, Anna Choromanska, Prashanth Krishnamurthy, and Farshad Khorrami · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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End-to-End Learning of Driving Models from Large-Scale Video Datasets
Huazhe Xu, Yang Gao, Fisher Yu, and Trevor Darrell · 2017
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Differentiable mpc for end-to-end planning and control
Brandon Amos, Ivan Dario Jimenez Rodriguez, Jacob Sacks, Byron Boots, and J. Zico Kolter · 2018
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End-to-End Driving via Conditional Imitation Learning
Felipe Codevilla, Matthias Miiller, Antonio López, Vladlen Koltun, and Alexey Dosovitskiy · 2018
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End to end vehicle lateral control using a single fisheye camera
Marin Toromanoff, Emilie Wirbel, Frédéric Wilhelm, Camilo Vejarano, Xavier Perrotton, and Fabien Moutarde · 2018
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Safe learning of quadrotor dynamics using barrier certificates
Li Wang, Evangelos A Theodorou, and Magnus Egerstedt · 2018
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Variational end-to-end navigation and localization
Alexander Amini, Guy Rosman, Sertac Karaman, and Daniela Rus · 2019
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Learning deep neural network controllers for dynamical systems with safety guarantees: Invited paper
Neural certificates for safe control policies
Wanxin Jin, Zhaoran Wang, Zhuoran Yang, and Shaoshuai Mou · 2020
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Neural circuit policies enabling auditable autonomy
Mathias Lechner, Ramin Hasani, Alexander Amini, Thomas A Henzinger, Daniela Rus, and Radu Grosu · 2020
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Safe optimal control using stochastic barrier functions and deep forward-backward sdes
Marcus Aloysius Pereira, Ziyi Wang, Ioannis Exarchos, and Evangelos A. Theodorou · 2020
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Learning control barrier functions from expert demonstrations
Alexander Robey, Haimin Hu, Lars Lindemann, Hanwen Zhang, Dimos V. Dimarogonas, Stephen Tu, and Nikolai Matni · 2020
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Learning for safety-critical control with control barrier functions
Andrew Taylor, Andrew Singletary, Yisong Yue, and Aaron Ames · 2020
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Jyotirmoy V. Deshmukh, James P. Kapinski, Tomoya Yamaguchi, and Danil Prokhorov · 2019
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Designing worm-inspired neural networks for interpretable robotic control
Mathias Lechner, Ramin Hasani, Manuel Zimmer, Thomas A Henzinger, and Radu Grosu · 2019
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Aads: Augmented autonomous driving simulation using data-driven algorithms
Wei Li, Chengwei Pan, Rong Zhang, Jiaping Ren, Yuexin Ma, Jin Fang, Feilong Yan, Qichuan Geng, Xinyu Huang, Huajun Gong, et al · 2019
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Control barrier functions for systems with high relative degree
Wei Xiao and Calin Belta · 2019
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Multimodal End-to-End Autonomous Driving
Yi Xiao, Felipe Codevilla, Akhil Gurram, Onay Urfalioglu, and Antonio M López · 2019
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Self-triggered control for safety critical systems using control barrier functions
Guang Yang, Calin Belta, and Roberto Tron · 2019
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Learning robust control policies for end-to-end autonomous driving from data-driven simulation
Alexander Amini, Igor Gilitschenski, Jacob Phillips, Julia Moseyko, Rohan Banerjee, Sertac Karaman, and Daniela Rus · 2020
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Feasibility guided learning for constrained optimal control problems
Wei Xiao, Calin Belta, and Christos G. Cassandras · 2020
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Training neural network controllers using control barrier functions in the presence of disturbances
Shakiba Yaghoubi, Georgios Fainekos, and Sriram Sankaranarayanan · 2020
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Alexander Amini, Tsun-Hsuan Wang, Igor Gilitschenski, Wilko Schwarting, Zhijian Liu, Song Han, Sertac Karaman, and Daniela Rus · 2021
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Latent imagination facilitates zero-shot transfer in autonomous racing
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Gotube: Scalable stochastic verification of continuous-depth models
Sophie Gruenbacher, Mathias Lechner, Ramin Hasani, Daniela Rus, Thomas A Henzinger, Scott Smolka, and Radu Grosu · 2021
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Mixed-memory rnns for learning long-term dependencies in irregularly sampled time series
Mathias Lechner and Ramin Hasani · 2021
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Comparison between safety methods control barrier function vs. reachability analysis
Zhichao Li · 2021
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Hardik Parwana and Dimitra Panagou · 2021
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Learning interactive driving policies via data-driven simulation
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Adaptive control barrier functions
Wei Xiao, Calin Belta, and Christos G. Cassandras · 2021
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Learning safe neural network controllers with barrier certificates
Hengjun Zhao, Xia Zeng, Taolue Chen, Zhiming Liu, and Jim Woodcock · 2021
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Sufficient conditions for feasibility of optimal control problems using control barrier functions
W. Xiao, C. Belta, and C. G. Cassandras · 2022
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Dreaming with transformers
Catherine Zeng, Jordan Docter, Alexander Amini, Igor Gilitschenski, Ramin Hasani, and Daniela Rus · 2022
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