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In this paper, we propose a deep learning based control synthesis framework for fast and online computation of controllers that guarantees the safety of general nonlinear control systems with unknown dynamics in the presence of input constraints.
Quadrotor dynamics and control
Randal W Beard · 2008
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Discrete control barrier functions for safety-critical control of discrete systems with application to bipedal robot navigation
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Neural ordinary differential equations
Ricky TQ Chen, Yulia Rubanova, Jesse Bettencourt, and David K Duvenaud · 2018
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Rasheed Hussain and Sherali Zeadally · 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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Safe policy synthesis in multi-agent pomdps via discrete-time barrier functions
Mohamadreza Ahmadi, Andrew Singletary, Joel W Burdick, and Aaron D Ames · 2019
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Control barrier functions: Theory and applications
Aaron D Ames, Samuel Coogan, Magnus Egerstedt, Gennaro Notomista, Koushil Sreenath, and Paulo Tabuada · 2019
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End-to-end safe reinforcement learning through barrier functions for safety-critical continuous control tasks
Richard Cheng, Gábor Orosz, Richard M Murray, and Joel W Burdick · 2019
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Imitation learning via off-policy distribution matching, 2019
Ilya Kostrikov, Ofir Nachum, and Jonathan Tompson · 2019
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Safety-critical control for non-affine nonlinear systems with application on autonomous vehicle
Tong Duy Son and Quan Nguyen · 2019
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Integral control barrier functions for dynamically defined control laws
Aaron D Ames, Gennaro Notomista, Yorai Wardi, and Magnus Egerstedt · 2020
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Primal wasserstein imitation learning
Rahman Dadashi, Loic Hussenot, Mathieu Geist, and Olivier Pietquin · 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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Synthesis of control barrier functions using a supervised machine learning approach
Mohit Srinivasan, Amogh Dabholkar, Samuel Coogan, and Patricio A Vela · 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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Safe nonlinear control using robust neural lyapunov-barrier functions
Charles Dawson, Zengyi Qin, Sicun Gao, and Chuchu Fan · 2022
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Adversarial imitation learning from video using a state observer
Haresh Karnan, Faraz Torabi, Garrett Warnell, and Peter Stone · 2022
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Safety-critical control with nonaffine control inputs via a relaxed control barrier function for an autonomous vehicle
Joohwan Seo, Joonho Lee, Eunkyu Baek, Roberto Horowitz, and Jongeun Choi · 2022
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Imitation learning: Progress, taxonomies and challenges
Boyuan Zheng, Sunny Verma, Jianlong Zhou, Ivor W Tsang, and Fang Chen · 2022
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Mitchell Black and Dimitra Panagou · 2023
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