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The transfer of reinforcement learning (RL) techniques into real-world applications is challenged by safety requirements in the presence of physical limitations.
Karg, B., Alamo, T. and Lucia, S. (2019) · 1910
Earlier work this paper cites.
Li, S. and Bastani, O. (2019) · 1910
Earlier work this paper cites.
Tolerance regions for a multivariate normal population, Annals of the Institute of Statistical Mathematics
Slotani, M. (1964) · 1964
Earlier work this paper cites.
Shrinking horizon model predictive control applied to autoclave curing of composite laminate materials, Proceedings of the American Control Conference
Thomas, M. M., Kardos, J. L. and Joseph, B. (1994) · 1994
Earlier work this paper cites.
A quasi-infinite horizon nonlinear model predictive control scheme with guaranteed stability, Automatica
Chen, H. and Allgöwer, F. (1998) · 1998
Earlier work this paper cites.
The simplex architecture for safe on-line control system upgrades, Proceedings of the American Control Conference
Seto, D., Krogh, B., Sha, L. and Chutinan, A. (1998) · 1998
Earlier work this paper cites.
Safety verification of hybrid systems using barrier certificates, Lecture Notes in Computer Science
Prajna, S. and Jadbabaic, A. (2004) · 2004
Earlier work this paper cites.
Gaussian Processes for Machine Learning
Rasmussen, C. and Williams, C. (2006) · 2006
Earlier work this paper cites.
On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming, Mathematical programming
Wächter, A. and Biegler, L. T. (2006) · 2006
Earlier work this paper cites.
Constructive safety using control barrier functions, IFAC Proceedings Volumes
Wieland, P. and Allgöwer, F. (2007) · 2007
Earlier work this paper cites.
LQR-trees: Feedback motion planning via sums-of-squares verification, The International Journal of Robotics Research
Tedrake, R., Manchester, I. R., Tobenkin, M. and Roberts, J. W. (2010) · 2010
Earlier work this paper cites.
Guaranteed safe online learning of a bounded system, Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on
Gillula, J. H. and Tomlin, C. J. (2011) · 2011
Earlier work this paper cites.
Statistical Learning Theory: Models, Concepts, and Results
von Luxburg, U. and Schölkopf, B. (2011) · 2011
Earlier work this paper cites.
Learning-based model predictive control on a quadrotor: Onboard implementation and experimental results, 2012 IEEE International Conference on Robotics and Automation
Bouffard, P., Aswani, A. and Tomlin, C. (2012) · 2012
Earlier work this paper cites.
Efficient interior point methods for multistage problems arising in receding horizon control, 51st IEEE Conference on Decision and Control (CDC)
Domahidi, A., Zgraggen, A. U., Zeilinger, M. N., Morari, M. and Jones, C. N. (2012) · 2012
Earlier work this paper cites.
Adaptive model predictive control for constrained linear systems, Control Conference (ECC), 2013 European
Tanaskovic, M., Fagiano, L., Smith, R., Goulart, P. and Morari, M. (2013) · 2013
Earlier work this paper cites.
Reachability-based safe learning with Gaussian processes, Proceedings of the IEEE Conference on Decision and Control
Akametalu, A. K., Kaynama, S., Fisac, J. F., Zeilinger, M. N., Gillula, J. H. and Tomlin, C. J. (2014) · 2014
Cited alongside, same era.
On the Benefit of Re-optimization in Optimal Control under Perturbations, Proceedings of the 21st International Symposium on Mathematical Theory of Networks and Systems – MTNS 2014
Grune, L. and Palma, V. G. (2014) · 2014
Cited alongside, same era.
Model predictive control: Recent developments and future promise, Automatica
Mayne, D. Q. (2014) · 2014
Cited alongside, same era.
A comprehensive survey on safe reinforcement learning, Journal of Machine Learning Research
Garcıa, J. and Fernández, F. (2015) · 2015
Cited alongside, same era.
Concrete problems in AI safety, arXiv preprint arXiv:1606.06565
Amodei, D., Olah, C., Steinhardt, J., Christiano, P., Schulman, J. and Mané, D. (2016) · 2016
Learning an Approximate Model Predictive Controller with Guarantees, IEEE Control Systems Letters
Hertneck, M., Kohler, J., Trimpe, S. and Allgöwer, F. (2018) · 2018
Closest in time.
Cautious NMPC with Gaussian process dynamics for autonomous miniature race cars, 2018 European Control Conference (ECC)
Hewing, L., Liniger, A. and Zeilinger, M. N. (2018) · 2018
Closest in time.
Real-Time Tube MPC Applied to a 10-State Quadrotor Model, Proceedings of the American Control Conference
Hu, H., Feng, X., Quirynen, R., Villanueva, M. E. and Houska, B. (2018) · 2018
Closest in time.
A novel constraint tightening approach for nonlinear robust model predictive control, 2018 Annual American Control Conference (ACC)
Köhler, J., Müller, M. A. and Allgöwer, F. (2018b) · 2018
Closest in time.
Learning-based model predictive control for safe exploration, 2018 IEEE Conference on Decision and Control (CDC)
Koller, T., Berkenkamp, F., Turchetta, M. and Krause, A. (2018) · 2018
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Cited alongside, same era.
Safe learning of regions of attraction for uncertain, nonlinear systems with Gaussian Processes, 55th IEEE Conference on Decision and Control (CDC)
Berkenkamp, F., Moriconi, R., Schoellig, A. P. and Krause, A. (2016) · 2016
Cited alongside, same era.
RotorS-A modular gazebo MAV simulator framework, Studies in Computational Intelligence
Furrer, F., Burri, M., Achtelik, M. and Siegwart, R. (2016) · 2016
Cited alongside, same era.
End-to-end training of deep visuomotor policies, The Journal of Machine Learning Research
Levine, S., Finn, C., Darrell, T. and Abbeel, P. (2016) · 2016
Cited alongside, same era.
Robust constrained learning-based NMPC enabling reliable mobile robot path tracking, The International Journal of Robotics Research
Ostafew, C. J., Schoellig, A. P. and Barfoot, T. D. (2016) · 2016
Cited alongside, same era.
Constrained policy optimization, International Conference on Machine Learning
Achiam, J., Held, D., Tamar, A. and Abbeel, P. (2017) · 2017
Cited alongside, same era.
Control Barrier Function Based Quadratic Programs for Safety Critical Systems, IEEE Transactions on Automatic Control
Ames, A. D., Xu, X., Grizzle, J. W. and Tabuada, P. (2017) · 2017
Cited alongside, same era.
On kernelized multi-armed bandits, International Conference on Machine Learning (ICML)
Chowdhury, S. R. and Gopalan, A. (2017) · 2017
Cited alongside, same era.
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Mannucci, T., van Kampen, E. J., de Visser, C. and Chu, Q. (2018) · 2018
Closest in time.
Learning-based robust model predictive control with state-dependent uncertainty, IFAC-PapersOnLine
Soloperto, R., Müller, M. A., Trimpe, S. and Allgöwer, F. (2018) · 2018
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Linear model predictive safety certification for learning-based control, 2018 IEEE Conference on Decision and Control (CDC)
Wabersich, K. P. and Zeilinger, M. N. (2018a) · 2018
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Wang, L., Han, D. and Egerstedt, M. (2018) · 2018
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Control barrier functions: Theory and applications, 2019 18th European Control Conference, ECC 2019
Ames, A. D., Coogan, S., Egerstedt, M., Notomista, G., Sreenath, K. and Tabuada, P. (2019) · 2019
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Ohnishi, M., Wang, L., Notomista, G. and Egerstedt, M. (2019) · 2019
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