Model Free Barrier Functions via Implicit Evading Maneuvers

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2015

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C. Blundell, J. Cornebise, K. Kavukcuoglu, and D. Wierstra, “Weight uncertainty in neural network,” in Proceedings of the 32nd International Conference on Machine Learning , ser. Proceedings of Machine Learning Research, F. Bach and D. Blei, Eds., vol. 37. Lille, France: PMLR, 07–09 Jul 2015, pp. 1613–1622

2015

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Y. Gal, “Uncertainty in deep learning,” University of Cambridge , vol. 1, no. 3, 2016

2016

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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, 2017

2017

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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 Proceedings of Robotics: Science and Systems , Cambridge, Massachusetts, July 2017, pp. 73–82

2017

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P. Glotfelter, J. Cortés, and M. Egerstedt, “Nonsmooth barrier functions with applications to multi-robot systems,” IEEE Control Systems Letters , vol. 1, no. 2, pp. 310–315, 2017

2017

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L. Wang, D. Han, and M. Egerstedt, “Permissive barrier certificates for safe stabilization using sum-of-squares,” in 2018 Annual American Control Conference (ACC) , 2018, pp. 585–590

2018

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A. Nagabandi, G. Kahn, R. S. Fearing, and S. Levine, “Neural network dynamics for model-based deep reinforcement learning with model-free fine-tuning,” in 2018 IEEE International Conference on Robotics and Automation (ICRA) , 2018, pp. 7559–7566

2018

Cited alongside, same era.

T. Gurriet, M. Mote, A. D. Ames, and E. Feron, “An online approach to active set invariance,” in 2018 IEEE Conference on Decision and Control (CDC) , 2018, pp. 3592–3599

2018

Cited alongside, same era.

L. Wang, E. A. Theodorou, and M. Egerstedt, “Safe learning of quadrotor dynamics using barrier certificates,” in 2018 IEEE International Conference on Robotics and Automation (ICRA) , 2018

2018

Cited alongside, same era.

R. Cheng, G. Orosz, R. M. Murray, and J. W. Burdick, “End-to-end safe reinforcement learning through barrier functions for safety-critical continuous control tasks,” Proceedings of the AAAI Conference on Artificial Intelligence , vol. 33, no. 01, pp. 3387–3395, Jul. 2019

2019

Z. Qin, K. Zhang, Y. Chen, J. Chen, and C. Fan, “Learning safe multi-agent control with decentralized neural barrier certificates,” arXiv preprint arXiv:2101.05436 , 2021

Original

2021

Closest in time.

H. Ma, J. Chen, S. E. Li, Z. Lin, Y. Guan, Y. Ren, and S. Zheng, “Model-based constrained reinforcement learning using generalized control barrier function,” arXiv preprint arXiv:2103.01556 , 2021

Original

2021

Closest in time.

A. Robey, L. Lindemann, S. Tu, and N. Matni, “Learning robust hybrid control barrier functions for uncertain systems,” arXiv preprint arXiv:2101.06492 , 2021

Original

2021

Closest in time.

E. G. Squires, “Barrier functions and model free safety with applications to fixed wing collision avoidance,” Ph.D. dissertation, Georgia Institute of Technology, 2021

2021

Closest in time.