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5 Publications
2024 | Published | Conference Paper | IST-REx-ID: 17898
Lechner, M., Hasani, R., Amini, A., Wang, T. H., Henzinger, T. A., & Rus, D. (2024). Overparametrization helps offline-to-online generalization of closed-loop control from pixels. In Proceedings of the 2024 IEEE International Conference on Robotics and Automation (pp. 2774–2782). Yokohama, Japan: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICRA57147.2024.10610284
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2023 | Published | Conference Paper | IST-REx-ID: 12976 | 
Liao, K., Tricard, T., Piovarci, M., Seidel, H.-P., & Babaei, V. (2023). Learning deposition policies for fused multi-material 3D printing. In 2023 IEEE International Conference on Robotics and Automation (Vol. 2023, pp. 12345–12352). London, United Kingdom: IEEE. https://doi.org/10.1109/ICRA48891.2023.10160465
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2022 | Published | Conference Paper | IST-REx-ID: 12010 |
Brunnbauer, A., Berducci, L., Brandstatter, A., Lechner, M., Hasani, R., Rus, D., & Grosu, R. (2022). Latent imagination facilitates zero-shot transfer in autonomous racing. In 2022 International Conference on Robotics and Automation (pp. 7513–7520). Philadelphia, PA, United States: IEEE. https://doi.org/10.1109/ICRA46639.2022.9811650
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| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 10666 |
Lechner, M., Hasani, R., Grosu, R., Rus, D., & Henzinger, T. A. (2021). Adversarial training is not ready for robot learning. In 2021 IEEE International Conference on Robotics and Automation (pp. 4140–4147). Xi’an, China. https://doi.org/10.1109/ICRA48506.2021.9561036
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| arXiv
2020 | Published | Conference Paper | IST-REx-ID: 8704 |
Lechner, M., Hasani, R., Rus, D., & Grosu, R. (2020). Gershgorin loss stabilizes the recurrent neural network compartment of an end-to-end robot learning scheme. In Proceedings - IEEE International Conference on Robotics and Automation (pp. 5446–5452). Paris, France: IEEE. https://doi.org/10.1109/ICRA40945.2020.9196608
[Submitted Version]
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