Deep reinforcement learning with enhanced safety for autonomous highway driving A Baheri, S Nageshrao, HE Tseng, I Kolmanovsky, A Girard, D Filev 2020 IEEE Intelligent Vehicles Symposium (IV), 1550-1555, 2020 | 51 | 2020 |
Real-time control using Bayesian optimization: A case study in airborne wind energy systems A Baheri, S Bin-Karim, A Bafandeh, C Vermillion Control Engineering Practice 69, 131-140, 2017 | 42 | 2017 |
A survey on reinforcement learning in aviation applications P Razzaghi, A Tabrizian, W Guo, S Chen, A Taye, E Thompson, ... arXiv preprint arXiv:2211.02147, 2022 | 28 | 2022 |
Altitude optimization of airborne wind energy systems: A Bayesian optimization approach A Baheri, C Vermillion 2017 American Control Conference (ACC), 1365-1370, 2017 | 27 | 2017 |
Spatiotemporal optimization through gaussian process-based model predictive control: A case study in airborne wind energy S Bin-Karim, A Bafandeh, A Baheri, C Vermillion IEEE Transactions on Control Systems Technology 27 (2), 798-805, 2017 | 26 | 2017 |
Iterative 3d layout optimization and parametric trade study for a reconfigurable ocean current turbine array using Bayesian optimization A Baheri, P Ramaprabhu, C Vermillion Renewable energy 127, 1052-1063, 2018 | 20 | 2018 |
Safe reinforcement learning with mixture density network, with application to autonomous driving A Baheri Results in Control and Optimization 6, 100095, 2022 | 18 | 2022 |
Combined plant and controller design using Bayesian optimization: A case study in airborne wind energy systems A Baheri, J Deese, C Vermillion Dynamic Systems and Control Conference 58295, V003T40A003, 2017 | 16 | 2017 |
Combined plant and controller design using batch bayesian optimization: a case study in airborne wind energy systems A Baheri, C Vermillion Journal of Dynamic Systems, Measurement, and Control 141 (9), 091013, 2019 | 14 | 2019 |
Waypoint optimization using Bayesian optimization: A case study in airborne wind energy systems A Baheri, C Vermillion 2020 American Control Conference (ACC), 5102-5017, 2020 | 12 | 2020 |
A comparative assessment of hierarchical control structures for spatiotemporally-varying systems, with application to airborne wind energy A Bafandeh, S Bin-Karim, A Baheri, C Vermillion Control Engineering Practice 74, 71-83, 2018 | 12 | 2018 |
Iterative in-situ 3D layout optimization of a reconfigurable ocean current turbine array using Bayesian optimization A Baheri, P Ramaprabhu, C Vermillion Dynamic Systems and Control Conference 58295, V003T40A002, 2017 | 11 | 2017 |
Black-Box Safety Validation of Autonomous Systems: A Multi-Fidelity Reinforcement Learning Approach JJ Beard, A Baheri arXiv preprint arXiv:2203.03451, 2022 | 9 | 2022 |
Vision-based autonomous driving: A model learning approach A Baheri, I Kolmanovsky, A Girard, HE Tseng, D Filev 2020 American Control Conference (ACC), 2520-2525, 2020 | 9 | 2020 |
Falsification of learning-based controllers through multi-fidelity Bayesian optimization Z Shahrooei, MJ Kochenderfer, A Baheri 2023 European Control Conference (ECC), 1-6, 2023 | 5 | 2023 |
A verification framework for certifying learning-based safety-critical aviation systems A Baheri, H Ren, B Johnson, P Razzaghi, P Wei AIAA AVIATION 2022 Forum, 3965, 2022 | 5 | 2022 |
Waypoint optimization using Bayesian optimization: A case study in airborne wind energy systems. In 2020 Amer. Control Conf.(ACC), 5102–5017 A Baheri, C Vermillion IEEE, 2020 | 4 | 2020 |
Safe reinforcement learning with mixture density network: A case study in autonomous highway driving A Baheri arXiv preprint arXiv:2007.01698, 2020 | 3 | 2020 |
Context-dependent Bayesian Optimization in real-time optimal control: A case study in airborne wind energy systems A Baheri, C Vermillion NIPS Workshop on Bayesian Optimization, 2017 | 3 | 2017 |
Concurrent design of unity-magnitude input shapers and proportional-derivative feedback controllers A Baheri, J Vaughan 2015 American Control Conference (ACC), 1211-1216, 2015 | 3 | 2015 |