Amer, Abdelhakim, Mohit Mehndiratta, Jonas le Fevre Sejersen, Huy Xuan Pham, and Erdal Kayacan. “Visual Tracking Nonlinear Model Predictive Control Method for Autonomous Wind Turbine Inspection.”https://doi.org/10.1109/icar58858.2023.10406329__In 2023 21st International Conference on Advanced Robotics (ICAR). IEEE, 2024.https://doi.org/10.1109/icar58858.2023.10406329 .

Amer, Abdelhakim, Olaya Álvarez-Tuñón, Halil brahim Ufurlu, Jonas Le Fevre Sejersen, Yury Brodskiy, and Erdal Kayacan. “UNav-Sim: A Visually Realistic Underwater Robotics Simulator and Synthetic Data-Generation Framework.”https://doi.org/10.1109/icar58858.2023.10406819__In 2023 21st International Conference on Advanced Robotics (ICAR). IEEE, 2024.https://doi.org/10.1109/icar58858.2023.10406819 .

Álvarez-Tuñón, Olaya, Yury Brodskiy, and Erdal Kayacan. “Monocular Visual Simultaneous Localization and Mapping: (R)Evolution from Geometry to Deep Learning-Based Pipelines.”https://doi.org/10.1109/tai.2023.3321032__IEEE Transactions on Artificial Intelligence, 2023, 1–21.https://doi.org/10.1109/tai.2023.3321032 .

Álvarez-Tuñón, Olaya, Hemanth Kanner, Luiza Ribeiro Marnet, Huy Xuan Pham, Jonas le Fevre Sejersen, Yury Brodskiy, and Erdal Kayacan. “MIMIR-UW: A Multipurpose Synthetic Dataset for Underwater Navigation and Inspection.”https://doi.org/10.1109/iros55552.2023.10341436__In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2023.https://doi.org/10.1109/iros55552.2023.10341436 .

Heiß, Micha, Jakob Grimm Hansen, Dengyun Li, Micha Kozowski, and Erdal Kayacan. “PredictiveSLAM - Robust Visual SLAM Through Trajectory-Aware Object Masking.”https://doi.org/10.1109/icuas57906.2023.10155806__In 2023 International Conference on Unmanned Aircraft Systems (ICUAS). IEEE, 2023.https://doi.org/10.1109/icuas57906.2023.10155806 .

Fevre Sejersen, Jonas le, and Erdal Kayacan. “CAMETA: Conflict-Aware Multi-Agent Estimated Time of Arrival Prediction for Mobile Robots.”https://doi.org/10.1109/iros55552.2023.10341937__In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2023.https://doi.org/10.1109/iros55552.2023.10341937 .

Protte, Marius, Rene Fahr, and Daniel E. Quevedo. “Behavioral Economics for Human-in-the-Loop Control Systems Design: Overconfidence and the Hot Hand Fallacy.”https://doi.org/10.1109/mcs.2020.3019723__IEEE Control Systems 40, no. 6 (2022): 57–76.https://doi.org/10.1109/mcs.2020.3019723 .

Weber, Daniel, Stefan Heid, Henrik Bode, Jarren Lange, Eyke Hüllermeier, and Oliver Wallscheid. “Safe Bayesian Optimization for Data-Driven Power Electronics Control Design in Microgrids: From Simulations to Real-World Experiments.”https://doi.org/10.1109/ACCESS.2021.3062144__IEEE Access 9 (2021): 35654–35669.https://doi.org/10.1109/ACCESS.2021.3062144 .

Wallscheid, Oliver. “Thermal Monitoring of Electric Motors: State-of-the-Art Review and Future Challenges.” IEEE Open Journal of Industry Applications, 2021.

Schenke, Maximilian, and Oliver Wallscheid. “Improved Exploring Starts by Kernel Density Estimation-Based State-Space Coverage Acceleration in Reinforcement Learning.” ArXiv Preprint ArXiv:2105.08990, 2021.

Dragicevic, Tomislav, Alessandra Parisio, Jose Rodriguez, Colin Jones, Daniel Quevedo, Luca Ferrarini, Matthias Preindl, Qobad Shafiee, and Thomas Morstyn. “Guest Editorial Model Predictive Control in Energy Conversion Systems.”https://doi.org/10.1109/tec.2021.3076279__IEEE Transactions on Energy Conversion 36, no. 2 (2021): 1311–12.https://doi.org/10.1109/tec.2021.3076279 .

Lu, Jingyi, and Daniel E. Quevedo. “A Jointly Optimal Design of Control and Scheduling in Networked Systems  under Denial-of-Service Attacks.” ArXiv:2103.05893, 2021.

Heid, Stefan, Daniel Weber, Henrik Bode, Eyke Hüllermeier, and Oliver Wallscheid. “OMG: A Scalable and Flexible Simulation and Testing Environment Toolbox for Intelligent Microgrid Control.” Journal of Open Source Software 5, no. 54 (2020): 2435.

Lu, Jingyi, Alex S. Leong, and Daniel E. Quevedo. “Optimal Eventtriggered Transmission Scheduling for Privacypreserving Wireless State Estimation.”https://doi.org/10.1002/rnc.4910__International Journal of Robust and Nonlinear Control 30, no. 11 (2020): 4205–24.https://doi.org/10.1002/rnc.4910 .

Noroozi, Navid, Roxanne Jackson, Daniel E. Quevedo, Fabian R. Wirth, and Rolf Findeisen. “On Noise-to-State Stability of Stochastic Discrete-Time Systems via Finite-Step Lyapunov Functions.”https://doi.org/10.1109/cdc40024.2019.9030178__In 2019 IEEE 58th Conference on Decision and Control (CDC). IEEE, 2020.https://doi.org/10.1109/cdc40024.2019.9030178 .

Ding, K., X. Ren, D. E. Quevedo, S. Dey, and L. Shi. “Defensive Deception against Reactive Jamming Attacks in Remote State Estimation.” Automatica 113 (2020).

Leong, Alex S., Arunselvan Ramaswamy, Daniel E. Quevedo, Holger Karl, and Ling Shi. “Deep Reinforcement Learning for Wireless Sensor Scheduling in Cyber–Physical Systems.”https://doi.org/10.1016/j.automatica.2019.108759__Automatica, 2019.https://doi.org/10.1016/j.automatica.2019.108759 .

Leong, Alex S., Arunselvan Ramaswamy, Daniel E. Quevedo, Holger Karl, and Ling Shi. “Deep Reinforcement Learning for Wireless Sensor Scheduling in Cyber–Physical Systems.”https://doi.org/10.1016/j.automatica.2019.108759__Automatica 113 (2019).https://doi.org/10.1016/j.automatica.2019.108759 .

Ding, Kemi, Xiaoqiang Ren, Daniel E. Quevedo, Subhrakanti Dey, and Ling Shi. “Defensive Deception against Reactive Jamming Attacks in Remote State Estimation.”https://doi.org/10.1016/j.automatica.2019.108680__Automatica 113 (2019).https://doi.org/10.1016/j.automatica.2019.108680 .

Guo, Z., D. Shi, D. E. Quevedo, and L. Shi. “Secure State Estimation Against Integrity Attacks: A Gaussian Mixture Model Approach Secure State Estimation Against Integrity Attacks: A Gaussian Mixture Model Approach.” Trans. Signal Processing 67, no. 1 (2019): 194–207.