Vision-based automatic fruit counting with UAV
Fuente:
arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Acceso en línea: | |
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| _version_ | 1866910878792679424 |
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| author | Szolc, Hubert Wasala, Mateusz Mietla, Remigiusz Iwicki, Kacper Kryjak, Tomasz |
| author_facet | Szolc, Hubert Wasala, Mateusz Mietla, Remigiusz Iwicki, Kacper Kryjak, Tomasz |
| contents | The use of unmanned aerial vehicles (UAVs) for smart agriculture is becoming increasingly popular. This is evidenced by recent scientific works, as well as the various competitions organised on this topic. Therefore, in this work we present a system for automatic fruit counting using UAVs. To detect them, our solution uses a vision algorithm that processes streams from an RGB camera and a depth sensor using classical image operations. Our system also allows the planning and execution of flight trajectories, taking into account the minimisation of flight time and distance covered. We tested the proposed solution in simulation and obtained an average score of 87.27/100 points from a total of 500 missions. We also submitted it to the UAV Competition organised as part of the ICUAS 2024 conference, where we achieved an average score of 84.83/100 points, placing 6th in a field of 23 teams and advancing to the finals. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_13080 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Vision-based automatic fruit counting with UAV Szolc, Hubert Wasala, Mateusz Mietla, Remigiusz Iwicki, Kacper Kryjak, Tomasz Robotics Computer Vision and Pattern Recognition Image and Video Processing The use of unmanned aerial vehicles (UAVs) for smart agriculture is becoming increasingly popular. This is evidenced by recent scientific works, as well as the various competitions organised on this topic. Therefore, in this work we present a system for automatic fruit counting using UAVs. To detect them, our solution uses a vision algorithm that processes streams from an RGB camera and a depth sensor using classical image operations. Our system also allows the planning and execution of flight trajectories, taking into account the minimisation of flight time and distance covered. We tested the proposed solution in simulation and obtained an average score of 87.27/100 points from a total of 500 missions. We also submitted it to the UAV Competition organised as part of the ICUAS 2024 conference, where we achieved an average score of 84.83/100 points, placing 6th in a field of 23 teams and advancing to the finals. |
| title | Vision-based automatic fruit counting with UAV |
| topic | Robotics Computer Vision and Pattern Recognition Image and Video Processing |
| url | https://arxiv.org/abs/2503.13080 |