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Learning Differentiable Safety-Critical Control using Control Barrier Functions for Generalization to Novel Environments

4 January 2022

Papers citing "Learning Differentiable Safety-Critical Control using Control Barrier Functions for Generalization to Novel Environments"

21 / 21 papers shown

Title
Learning to Refine Input Constrained Control Barrier Functions via Uncertainty-Aware Online Parameter Adaptation Taekyung Kim Robin Inho Kee Dimitra Panagou 91 8 0 22 Sep 2024
Safety Assurances for Human-Robot Interaction via Confidence-aware Game-theoretic Human Models Ran Tian Liting Sun Andrea V. Bajcsy Masayoshi Tomizuka Anca Dragan 103 56 0 29 Sep 2021
Recursive Feasibility Guided Optimal Parameter Adaptation of Differential Convex Optimization Policies for Safety-Critical Systems Hardik Parwana Dimitra Panagou 42 18 0 22 Sep 2021
Safe Nonlinear Control Using Robust Neural Lyapunov-Barrier Functions Charles Dawson Zengyi Qin Sicun Gao Chuchu Fan 146 176 0 14 Sep 2021
Safe Pontryagin Differentiable Programming Wanxin Jin Shaoshuai Mou George J. Pappas 80 41 0 31 May 2021
Enforcing robust control guarantees within neural network policies P. Donti Melrose Roderick Mahyar Fazlyab J. Zico Kolter OOD 77 65 0 16 Nov 2020
Provably Safe Control of Lagrangian Systems in Obstacle-Scattered Environments Fernando S Barbosa Lars Lindemann Dimos V. Dimarogonas Jana Tumova 27 18 0 04 Sep 2020
Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings Jesse Zhang Brian Cheung Chelsea Finn Sergey Levine Dinesh Jayaraman 68 60 0 15 Aug 2020
Safety-Critical Model Predictive Control with Discrete-Time Control Barrier Function Jun Zeng Bike Zhang Koushil Sreenath 63 277 0 22 Jul 2020
Learning Constrained Adaptive Differentiable Predictive Control Policies With Guarantees Ján Drgoňa Aaron Tuor D. Vrabie 54 18 0 23 Apr 2020
Reinforcement Learning for Safety-Critical Control under Model Uncertainty, using Control Lyapunov Functions and Control Barrier Functions Jason J. Choi F. Castañeda Claire Tomlin Koushil Sreenath 43 185 0 16 Apr 2020
Learning Control Barrier Functions from Expert Demonstrations Alexander Robey Haimin Hu Lars Lindemann Hanwen Zhang Dimos V. Dimarogonas Stephen Tu Nikolai Matni 103 208 0 07 Apr 2020
Learning for Safety-Critical Control with Control Barrier Functions Andrew J. Taylor Andrew W. Singletary Yisong Yue Aaron D. Ames 113 244 0 20 Dec 2019
Differentiable Convex Optimization Layers Akshay Agrawal Brandon Amos Shane T. Barratt Stephen P. Boyd Steven Diamond Zico Kolter 90 664 0 28 Oct 2019
Meta-Learning with Differentiable Convex Optimization Kwonjoon Lee Subhransu Maji Avinash Ravichandran Stefano Soatto 96 1,269 0 07 Apr 2019
Differentiable MPC for End-to-end Planning and Control Brandon Amos I. D. Rodriguez Jacob Sacks Byron Boots J. Zico Kolter 85 376 0 31 Oct 2018
PAC-Bayes Control: Learning Policies that Provably Generalize to Novel Environments Anirudha Majumdar M. Goldstein Anoopkumar Sonar 86 18 0 11 Jun 2018
A Lyapunov-based Approach to Safe Reinforcement Learning Yinlam Chow Ofir Nachum Edgar A. Duénez-Guzmán Mohammad Ghavamzadeh 163 507 0 20 May 2018
OptNet: Differentiable Optimization as a Layer in Neural Networks Brandon Amos J. Zico Kolter 171 972 0 01 Mar 2017
Multi-objective Compositions for Collision-Free Connectivity Maintenance in Teams of Mobile Robots Li Wang Aaron D. Ames M. Egerstedt 52 113 0 24 Aug 2016
Probabilistically Safe Vehicle Control in a Hostile Environment Igor Cizelj X. Ding Morteza Lahijanian A. Pinto C. Belta 68 12 0 21 Mar 2011