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This paper addresses the challenge of integrating explicit hard constraints into the control barrier function (CBF) framework for ensuring safety in autonomous systems, including robots.
A. D. Ames, J. W. Grizzle, and P. Tabuada, “Control barrier function based quadratic programs with application to adaptive cruise control,” in Proceedings of the IEEE Conference on Decision and Control , 2014, pp. 6271–6278
2014
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X. Xu, P. Tabuada, J. W. Grizzle, and A. D. Ames, “Robustness of control barrier functions for safety critical control,” IFAC-PapersOnLine , vol. 48, no. 27, pp. 54–61, 2015
2015
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A. D. Ames, X. Xu, J. W. Grizzle, and P. Tabuada, “Control barrier function based quadratic programs for safety critical systems,” IEEE Transactions on Automatic Control , vol. 62, no. 8, pp. 3861–3876, 2016
2016
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Q. Nguyen, A. Hereid, J. W. Grizzle, A. D. Ames, and K. Sreenath, “3d dynamic walking on stepping stones with control barrier functions,” in Proceedings of the IEEE Conference on Decision and Control , 2016, pp. 827–834
2016
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A. Agrawal and K. Sreenath, “Discrete control barrier functions for safety-critical control of discrete systems with application to bipedal robot navigation.” in Robotics: Science and Systems , vol. 13. Cambridge, MA, USA, 2017, pp. 1–10
2017
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S. Bansal, M. Chen, S. Herbert, and C. J. Tomlin, “Hamilton-jacobi reachability: A brief overview and recent advances,” in Proceedings of the IEEE Conference on Decision and Control , 2017, pp. 2242–2253
2017
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M. Jankovic, “Robust control barrier functions for constrained stabilization of nonlinear systems,” Automatica , vol. 96, pp. 359–367, 2018
2018
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J. F. Fisac, A. K. Akametalu, M. N. Zeilinger, S. Kaynama, J. Gillula, and C. J. Tomlin, “A general safety framework for learning-based control in uncertain robotic systems,” IEEE Transactions on Automatic Control , vol. 64, no. 7, pp. 2737–2752, 2018
2018
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A. J. Taylor and A. D. Ames, “Adaptive safety with control barrier functions,” in Proceedings of the American Control Conference , 2020, pp. 1399–1405
2020
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A. Taylor, A. Singletary, Y. Yue, and A. Ames, “Learning for safety-critical control with control barrier functions,” in Learning for Dynamics and Control . PMLR, 2020, pp. 708–717
2020
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M. Srinivasan, A. Dabholkar, S. Coogan, and P. A. Vela, “Synthesis of control barrier functions using a supervised machine learning approach,” in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems , 2020, pp. 7139–7145
2020
Earlier work this paper cites.
S. Yaghoubi, G. Fainekos, and S. Sankaranarayanan, “Training neural network controllers using control barrier functions in the presence of disturbances,” in IEEE International Conference on Intelligent Transportation Systems (ITSC) , 2020, pp. 1–6
2020
Earlier work this paper cites.
A. Robey, H. Hu, L. Lindemann, H. Zhang, D. V. Dimarogonas, S. Tu, and N. Matni, “Learning control barrier functions from expert demonstrations,” in Proceedings of the IEEE Conference on Decision and Control , 2020, pp. 3717–3724
2020
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2020
Cited alongside, same era.
J. Lee, J. Ahn, E. Bakolas, and L. Sentis, “Reachability-based trajectory optimization for robotic systems given sequences of rigid contacts,” in Proceedings of the American Control Conference , 2020, pp. 2158–2165
2020
Cited alongside, same era.
J. Buch, S.-C. Liao, and P. Seiler, “Robust control barrier functions with sector-bounded uncertainties,” IEEE Control Systems Letters , vol. 6, pp. 1994–1999, 2021
2021
Cited alongside, same era.
Z. Marvi and B. Kiumarsi, “Safe reinforcement learning: A control barrier function optimization approach,” International Journal of Robust and Nonlinear Control , vol. 31, no. 6, pp. 1923–1940, 2021
2021
Cited alongside, same era.
Y. Lyu, W. Luo, and J. M. Dolan, “Adaptive safe merging control for heterogeneous autonomous vehicles using parametric control barrier functions,” in IEEE Intelligent Vehicles Symposium (IV) , 2022, pp. 542–547
2022
Later among the works it cites.
J. Seo, J. Lee, E. Baek, R. Horowitz, and J. Choi, “Safety-critical control with nonaffine control inputs via a relaxed control barrier function for an autonomous vehicle,” IEEE Robotics and Automation Letters , vol. 7, no. 2, pp. 1944–1951, 2022
2022
Later among the works it cites.
R. Cosner, M. Tucker, A. Taylor, K. Li, T. Molnar, W. Ubelacker, A. Alan, G. Orosz, Y. Yue, and A. Ames, “Safety-aware preference-based learning for safety-critical control,” in Learning for Dynamics and Control Conference . PMLR, 2022, pp. 1020–1033
2022
Later among the works it cites.
C. Khazoom, D. Gonzalez-Diaz, Y. Ding, and S. Kim, “Humanoid self-collision avoidance using whole-body control with control barrier functions,” in Proceedings of the IEEE-RAS/RSJ International Conference on Humanoid Robots . IEEE, 2022, pp. 558–565
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H. Ma, J. Chen, S. Eben, Z. Lin, Y. Guan, Y. Ren, and S. Zheng, “Model-based constrained reinforcement learning using generalized control barrier function,” in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems , 2021, pp. 4552–4559
2021
Cited alongside, same era.
T. G. Molnar, R. K. Cosner, A. W. Singletary, W. Ubellacker, and A. D. Ames, “Model-free safety-critical control for robotic systems,” IEEE robotics and automation letters , vol. 7, no. 2, pp. 944–951, 2021
2021
Cited alongside, same era.
A. Singletary, K. Klingebiel, J. Bourne, A. Browning, P. Tokumaru, and A. Ames, “Comparative analysis of control barrier functions and artificial potential fields for obstacle avoidance,” in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems , 2021, pp. 8129–8136
2021
Cited alongside, same era.
Y. Chen, M. Jankovic, M. Santillo, and A. D. Ames, “Backup control barrier functions: Formulation and comparative study,” in Proceedings of the IEEE Conference on Decision and Control , 2021, pp. 6835–6841
2021
Cited alongside, same era.
J. J. Choi, D. Lee, K. Sreenath, C. J. Tomlin, and S. L. Herbert, “Robust control barrier–value functions for safety-critical control,” in Proceedings of the IEEE Conference on Decision and Control , 2021, pp. 6814–6821
2021
Cited alongside, same era.
S. Herbert, J. J. Choi, S. Sanjeev, M. Gibson, K. Sreenath, and C. J. Tomlin, “Scalable learning of safety guarantees for autonomous systems using hamilton-jacobi reachability,” in Proceedings of the IEEE International Conference on Robotics and Automation , 2021, pp. 5914–5920
2021
Cited alongside, same era.
E. Daş and R. M. Murray, “Robust safe control synthesis with disturbance observer-based control barrier functions,” in Proceedings of the IEEE Conference on Decision and Control , 2022, pp. 5566–5573
2022
Cited alongside, same era.
D. R. Agrawal and D. Panagou, “Safe and robust observer-controller synthesis using control barrier functions,” IEEE Control Systems Letters , vol. 7, pp. 127–132, 2022
2022
Cited alongside, same era.
2022
Later among the works it cites.
K. Nishimoto, R. Funada, T. Ibuki, and M. Sampei, “Collision avoidance for elliptical agents with control barrier function utilizing supporting lines,” in Proceedings of the American Control Conference , 2022, pp. 5147–5153
2022
Later among the works it cites.
F. Ferraguti, C. T. Landi, A. Singletary, H.-C. Lin, A. Ames, C. Secchi, and M. Bonfè, “Safety and efficiency in robotics: the control barrier functions approach,” IEEE Robotics & Automation Magazine , vol. 29, no. 3, pp. 139–151, 2022
2022
Later among the works it cites.
A. Alan, A. J. Taylor, C. R. He, A. D. Ames, and G. Orosz, “Control barrier functions and input-to-state safety with application to automated vehicles,” IEEE Transactions on Control Systems Technology , 2023
2023
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2023
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Y. Wang and X. Xu, “Disturbance observer-based robust control barrier functions,” in Proceedings of the American Control Conference , 2023, pp. 3681–3687
2023
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2023
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2023
Closest in time.
K. P. Wabersich, A. J. Taylor, J. J. Choi, K. Sreenath, C. J. Tomlin, A. D. Ames, and M. N. Zeilinger, “Data-driven safety filters: Hamilton-jacobi reachability, control barrier functions, and predictive methods for uncertain systems,” IEEE Control Systems Magazine , vol. 43, no. 5, pp. 137–177, 2023
2023
Closest in time.