Home Dissemination Communication Press Repository OctoPath: An OcTree-Based Self-Supervised Learning Approach to Local Trajectory Planning for Mobile Robots

OctoPath: An OcTree-Based Self-Supervised Learning Approach to Local Trajectory Planning for Mobile Robots

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

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Publication Type: Journal Article
Year of Publication: 2021
Authors: Bogdan Trasnea - Claudiu Pozna - Cosmin Ginerica - Gigel Macesanu - Mihai Zaha - Sorin Grigorescu
Publisher: MDPI
Name of publication/Event:
ISSN Number: 1424-8220
Keywords:
URL:

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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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