Abstract
The ability to autonomously navigate in an unknown and dynamic environment avoiding obstacles while, at the same time, classify various types of terrain are challenges that have been mainly faced by researchers from the computer vision area. Solutions to these problems are of great interest for collaborative autonomous navigation robots. For example an Unmanned Aerial Vehicle (UAV) may be used to determine the path which an Unmanned Surface Vehicle (USV) has to navigate to reach the intended destination. This paper presents a novel vision based algorithm that allows for independent navigation with on flight obstacle avoidance planning, while simultaneously classifying different terrain type using a Wiener-Khinchin (W-K) Filter.
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Notes
- 1.
The source code is available at https://github.com/pdmfc-public/UAVNavigation.
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Acknowledgment
This work is supported by the European Regional Development Fund (FEDER), through the Regional Operational Programme of Lisbon (POR LISBOA 2020) and the Competitiveness and Internationalization Operational Programme (COMPETE 2020) of the Portugal 2020 framework [Project 5G with Nr. 024539 (POCI-01-0247-FEDER-024539)].
This project has also received funding from the ECSEL Joint Undertaking (JU) under grant agreement No. 783221.
The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Austria, Belgium, Czech Republic, Finland, Germany, Greece, Italy, Latvia, Norway, Poland, Portugal, Spain, Sweden.
And also by FCT Strategic Program UID/EEA/00066/203 of UNINOVA, CTS.
In last, this work was not possible without the support and commitment of PDMFC Research group.
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Matos-Carvalho, J.P., Pedro, D., Campos, L.M., Fonseca, J.M., Mora, A. (2020). Terrain Classification Using W-K Filter and 3D Navigation with Static Collision Avoidance. In: Bi, Y., Bhatia, R., Kapoor, S. (eds) Intelligent Systems and Applications. IntelliSys 2019. Advances in Intelligent Systems and Computing, vol 1038. Springer, Cham. https://doi.org/10.1007/978-3-030-29513-4_81
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