Abstract
Millions of vehicles are transported every year, tightly parked in vessels or boats. To reduce the risks of associated safety issues like fires, knowing the location of vehicles is essential, since different vehicles may need different mitigation measures, e.g. electric cars. This work is aimed at creating a solution based on a nano-drone that navigates across rows of parked vehicles and detects their license plates. We do so via a wall-following algorithm, and a CNN trained to detect license plates. All computations are done in real-time on the drone, which just sends position and detected images that allow the creation of a 2D map with the position of the plates. Our solution is capable of reading all plates across eight test cases (with several rows of plates, different drone speeds, or low light) by aggregation of measurements across several drone journeys.
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Acknowledgements
This work has been carried out by M. Arvidsson and S. Sawirot in the context of their Master Thesis at Halmstad University (Computer Science and Engineering). The authors acknowledge the Swedish Innovation Agency (VINNOVA) for funding their research. Author F. A.-F. also thanks the Swedish Research Council (VR).
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Arvidsson, M., Sawirot, S., Englund, C., Alonso-Fernandez, F., Torstensson, M., Duran, B. (2024). Drone Navigation and License Place Detection for Vehicle Location in Indoor Spaces. In: Hernández Heredia, Y., Milián Núñez, V., Ruiz Shulcloper, J. (eds) Progress in Artificial Intelligence and Pattern Recognition. IWAIPR 2023. Lecture Notes in Computer Science, vol 14335. Springer, Cham. https://doi.org/10.1007/978-3-031-49552-6_31
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DOI: https://doi.org/10.1007/978-3-031-49552-6_31
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