Publications

Pezzato, C., Salmi, C., Spahn, M., Trevisan, E., Alonso-Mora, J., Hernández, C. (2023). Sampling-Based Model Predictive Control Leveraging Parallelizable Physics Simulation. Under review IEEE Robotics and Automation Letters. https://doi.org/10.48550/arXiv.2307.09105

Pezzato, C., Hernández, C., Wisse, M. (2023). Active Inference and Behavior Trees for Reactive Action Planning and Execution in Robotics. IEEE Transactions on Robotics, 39(2):1050-1069. https://doi.org/10.1109/TRO.2022.3226144

Bozhinoski, D., Oviedo, M. G., Garcia, N. H., Deshpande, H., van der Hoorn, G., Tjerngren, J., Wasowski, A., Hernández, C. (2022). MROS: Runtime Adaptation for Robot Control Architectures. Advanced Robotics,  36(11):502-518. https://doi.org/10.1080/01691864.2022.2039761

Aguado, E., Milosevic, Z., Hernández, C., Sanz, R., Garzon, M., Bozhinoski, D., Rossi, C. (2021). Functional Self-Awareness and Metacontrol for Underwater Robot Autonomy. Sensors, 21(4):1210. https://doi.org/10.3390/s21041210

Pezzato, C., Ferrari, R. M. G., Hernández, C. (2020). A Novel Adaptive Controller for Robot Manipulators Based on Active Inference. IEEE Robotics and Automation Letters, 5(2):2973-2980. https://doi.org/10.1109/LRA.2020.2974451

Hernández, C., Bharatheesha, M., van Egmond, J., Ju, J., Wisse, M. (2018). Integrating Different Levels of Automation: Lessons from Winning the Amazon Robotics Challenge 2016. IEEE Transactions on Industrial Informatics, 14(11):4916-4926. https://doi.org/10.1109/TII.2018.2800744

Pezzato, C., Salmi, C., Trevisan, E., Mora, J.A., Hernández, C. (2023). Sampling-Based MPC Using a GPU-Parallelizable Physics Simulator as Dynamic Model: An Open Source Implementation with IsaacGym. In: Embracing Contacts-Workshop at ICRA 2023. https://openreview.net/forum?id=fvfZKL1hCx

Silva, G.R., Päßler, J., Zwanepol, J., Alberts, E., Tarifa, S.L.T., Gerostathopoulos, I., Johnsen, E.B., Hernández, C. (2023). SUAVE: An Exemplar for Self-Adaptive Underwater Vehicles. In: 2023 IEEE/ACM 18th Symposium on Software Engineering for Adaptive and Self-Managing Systems, 181-187. https://doi.org/10.48550/arXiv.2303.09220

Silva, G.R., Garcia, N.H., Bozhinoski, D., Deshpande, H., Oviedo, M.G., Wasowski, A., Montero, M.R., Hernández, C. (2023). MROS: A Framework for Robot Self-Adaptation. In: 2023 IEEE/ACM 45th International Conference on Software Engineering: Companion Proceedings, 151-155. https://doi.org/10.1109/ICSE-Companion58688.2023.00044

Päßler, J., Aguado, E., Silva, G.R., Tarifa, S.L.T., Hernández, C., Johnsen, E.B. (2022). A Formal Model of Metacontrol in Maude. In: Margaria, T., Steffen, B. (Eds). Leveraging Applications of Formal Methods, Verification and Validation. Verification Principles. ISoLA 2022. Lecture Notes in Computer Science, 13701. Springer, Cham. https://doi.org/10.1007/978-3-031-19849-6_32

Fernandez, J. L., Hernández, C. (2019). Practical Model-Based Systems Engineering. Artech House Technology Management and Professional Development Series. Artech House. https://uk.artechhouse.com/Practical-Model-Based-Systems-Engineering-P2003.aspx

Sanz, R., Hernández, C., Gómez-Ramirez, J. (2011). Introduction. In: Hernández, C., et al. (Eds.), From Brains to Systems. Advances in Experimental Medicine and Biology, vol 718. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-0164-3_1

Sanz, R., Gómez Rivas, J., Hernández, C., Alarcón, I. (2008). Thinking with the Body: Towards Hierarchical, Scalable Cognition. In: P. Calvo, A. Gomila (Eds.), Handbook of Cognitive Science, 395-421. Elsevier. https://doi.org/10.1016/B978-0-08-046616-3.00020-7

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