EPI Consortium members published “OctoPath: An OcTree-Based Self-Supervised Learning Approach to Local Trajectory Planning for Mobile Robots” in Sensors.

Here you can find a link to an open access version of the article:

https://www.mdpi.com/1424-8220/21/11/3606

DOI: https://doi.org/10.3390/s21113606

EPI Consortium members published “LVD-NMPC: A learning-based vision dynamics approach to nonlinear model predictive control for autonomous vehicles” in International Journal of Advanced Robotic Systems.

Here you can find a link to an open access version of the article: https://journals.sagepub.com/doi/full/10.1177/17298814211019544.

DOI: https://doi.org/10.1177%2F17298814211019544.

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This project has received funding from the European High Performance Computing Joint Undertaking (JU) under Framework Partnership Agreement No 800928 and Specific Grant Agreement No 101036168 (EPI SGA2). The JU receives support from the European Union’s Horizon 2020 research and innovation programme and from Croatia, France, Germany, Greece, Italy, Netherlands, Portugal, Spain, Sweden, and Switzerland.

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