Advanced Navigation and Artificial Intelligence Techniques: Team Carbonite's Winning Strategies at the Field Robot Event 2023
DOI:
https://doi.org/10.18690/agricsci.22.1-2.2Keywords:
agricultural robotics, precision agriculture, sustainability, artificial intelligenceAbstract
An approach to address current challenges in agriculture caused by climate change, the increasing global population and the loss of biodiversity is precision farming, for which agricultural robotics is a key enabler. The Field Robot Event (FRE) 2023 has challenged student teams to develop and improve autonomous agricultural robots. This paper presents the improvements to our field robot “Carbonite,” which is developed at the Schülerforschungszentrum (SFZ) Südwürttemberg. Our lightweight and compact robot design, supported by our advanced and efficient navigation algorithm, enabled our robot to quickly move through fields. Additionally, we introduced our newly developed system for targeted and precise application of water, fertilizer and herbicides, based on an intelligent gap detection algorithm to avoid wasting resources. Also, we trained an object recognition AI model based on the You Only Look Once (YOLO) models, allowing the robot to appropriately respond based on the type of obstacle. Carbonite managed to secure the first place in both the navigation task and the plant treatment task, benefiting from the lightweight design and the resulting high robot driving speed, enabling us to win the overall FRE 2023 contest.
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References
1. ASUSTeK Computer Inc. (n.d.). EA-AC87—Support. Retrieved March 29, 2025, from https://www.asus.com/supportonly/eaac87/helpdesk_knowledge/
2. Benenson, R., Popov, S., & Ferrari, V. (2019). Large-scale interactive object segmentation with human annotators. arXiv:1903.10830. https://doi.org/10.48550/arXiv.1903.10830
3. Bjelonic, M. (2016). Leggedrobotics/darknet_ros [C++]. Robotic Systems Lab - Legged Robotics at ETH Zürich. https://github.com/leggedrobotics/darknet_ros
4. Bochkovskiy, A. (2013). AlexeyAB/darknet [C]. https://github.com/AlexeyAB/darknet
5. Bosch Sensortec GmbH. (n.d.). Smart Sensor BNO055. Bosch Sensortec. Retrieved from https://www.bosch-sensortec.com/products/smart-sensor-systems/bno055/
6. Cardinale, B. J., Duffy, J. E., Gonzalez, A., Hooper, D. U., Perrings, C., Venail, P., Narwani, A., Mace, G. M., Tilman, D., Wardle, D. A., Kinzig, A. P., Daily, G. C., Loreau, M., Grace, J. B., Larigauderie, A., Srivastava, D. S., & Naeem, S. (2012). Biodiversity loss and its impact on humanity. Nature, 486(7401), 59–67. https://doi.org/10.1038/nature11148
7. Field Robot Event. (2022, October 21). Field Robot Event 2023 in Slovenia! – Field Robot Event. https://fieldrobot.nl/event/index.php/2022/10/21/field-robot-event-goes-to-slovenia/
8. Field Robot Event. (2023a). FRE2023-RESULTS_FINAL.pdf. Field Contest 13.06.2023 – 15.06.2023 FRE 2023 Results. Retrieved from: https://fieldrobot.nl/event/wp-content/uploads/2023/06/FRE2023-RESULTS_FINAL.pdf
9. Field Robot Event. (2023b). Task 1 Navigation – Field Robot Event. Retrieved from: https://fieldrobot.nl/event/index.php/contest-hybrid/tasks-h/
10. Field Robot Event. (2023c). Task 2 treating (spraying) the plants – Field Robot Event. Retrieved from: https://fieldrobot.nl/event/index.php/contest-hybrid/task-h1/
11. Field Robot Event. (2023d). Task 3 sensing and recognizing possible obstacles – Field Robot Event. Retrieved from: https://fieldrobot.nl/event/index.php/contest-hybrid/task-h2/
12. Field Robot Event (2023e). Task 4 Static and dynamic obstacles – Field Robot Event. https://fieldrobot.nl/event/index.php/contest-hybrid/task-h3/
13. Field Robot Event (2023f). Task 5 Freestyle – Field Robot Event. Retrieved from: https://fieldrobot.nl/event/index.php/task-5-freestyle/
14. Foley, J. A., Ramankutty, N., Brauman, K. A., Cassidy, E. S., Gerber, J. S., Johnston, M., Mueller, N. D., O’Connell, C., Ray, D. K., West, P. C., Balzer, C., Bennett, E. M., Carpenter, S. R., Hill, J., Monfreda, C., Polasky, S., Rockström, J., Sheehan, J., Siebert, S., Tilman, D., & Zaks, D. P. M. (2011). Solutions for a cultivated planet. Nature, 478(7369), 337–342. https://doi.org/10.1038/nature10452
15. Gil, G., Casagrande, D. E., Cortés, L. P., & Verschae, R. (2023). Why the low adoption of robotics in the farms? Challenges for the establishment of commercial agricultural robots. Smart Agricultural Technology, 3, 100069. https://doi.org/10.1016/j.atech.2022.100069
16. Intel Corporation. (n.d.). Introducing the Intel® RealSenseTM Depth Camera D455. Intel® RealSenseTM Depth and Tracking Cameras. Retrieved from: https://www.intelrealsense.com/depth-camera-d455/
17. Keenso. (n.d.). Mini-Wasserpumpe, 12 V DC, 6 W, Tauchpumpe, ohne Bürste, energiesparend, für Aquarium, Brunnen, kleine Fischteiche, Solarsystem: Amazon.de: Haustier. Retrieved from: https://www.amazon.de/Submersible-Without-Energy-Aquarium-Fountain/dp/B07VGQ8KJV
18. Kuznetsova, A., Rom, H., Alldrin, N., Uijlings, J., Krasin, I., Pont-Tuset, J., Kamali, S., Popov, S., Malloci, M., Kolesnikov, A., Duerig, T., & Ferrari, V. (2020). The open images dataset V4: Unified image classification, object detection, and visual relationship detection at scale. International Journal of Computer Vision, 128(7), 1956–1981. https://doi.org/10.1007/s11263-020-01316-z
19. Lin, T.-Y., Maire, M., Belongie, S., Bourdev, L., Girshick, R., Hays, J., Perona, P., Ramanan, D., Zitnick, C. L., & Dollár, P. (2015). Microsoft COCO: Common Objects in Context. arXiv:1405.0312. https://doi.org/10.48550/arXiv.1405.0312
20. Malhi, G. S., Kaur, M., & Kaushik, P. (2021). Impact of climate change on agriculture and its mitigation strategies: A review. Sustainability, 13(3), 1318. https://doi.org/10.3390/su13031318
21. Mayer, J., Fauser, K., Schupp, J., & Locher, L. (2022). Carbonite–Team Carbonite. Proceedings of the 18th Field Robot Event 2021, 51–57. Retrieved from: https://www.fieldrobot.com/event/wp-content/uploads/2022/02/Proceedings_FRE2021.pdf
22. Nelson, G. C., Rosegrant, M. W., Koo, J., Robertson, R. D., Sulser, T., Zhu, T., Ringler, C., Msangi, S., Palazzo, A., Batka, M., Magalhaes, M., Valmonte-Santos, R., Ewing, M., & Lee, D. R. (2009). Climate change: Impact on agriculture and costs of adaptation. International Food Policy Research Institute. https://doi.org/10.2499/0896295354
23. NVIDIA Corporation. (n.d.). Jetson AGX Xavier Developer Kit by NVIDIA | 945-82972-0045-000. Arrow.Com.
Retrieved March 29, 2025, from https://www.arrow.com/en/products/945-82972-0045-000/nvidia
24. Open Robotics. (2024a, January 9). actionlib—ROS Wiki. Retrieved from: https://wiki.ros.org/actionlib
25. Open Robotics. (2024b, August 31). noetic—ROS Wiki. https://wiki.ros.org/noetic
26. OpenAI. (n.d.). Overview—OpenAI API. Retrieved from: https://platform.openai.com
27. Redmon, J. (2013, 2016). Darknet: Open Source Neural Networks in C.
28. Redmon, J., & Farhadi, A. (2018). YOLOv3: An Incremental Improvement. arXiv:1804.02767. https://doi.org/10.48550/arXiv.1804.02767
29. Robitronic Electronic Ges.m.b.H. (n.d.). Robitronic Platinium Brushless Motor 1/8 10.5T. Robitronic RC Car Online Shop - Power for Winners. Retrieved from: https://shop.robitronic.com/en/robitronic-platinium-brushless-motor-r03204
30. Rusu, R. B., & Cousins, S. (2011). 3D is here: Point Cloud Library (PCL). IEEE International Conference on Robotics and Automation (ICRA), Shanghai, China. Retrieved from: https://github.com/PointCloudLibrary/pcl
31. SICK AG. (n.d.). TiM571-2050101—TiM | SICK. Retrieved from: https://www.sick.com/us/en/catalog/products/lidar-and-radar-sensors/lidar-sensors/tim/tim571-2050101/p/p412444
32. The Qt Company. (n.d.). Qt 5.15. Retrieved from: https://doc.qt.io/qt-5/
33. Wang, C.-Y., Bochkovskiy, A., & Liao, H.-Y. M. (2022). YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors. arXiv:2207.02696. Retrieved from: https://doi.org/10.48550/arXiv.2207.02696
34. Worldsemi. (n.d.). WS2812B.pdf. Retrieved from: https://cdn-shop.adafruit.com/datasheets/WS2812B.pdf
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Copyright (c) 2025 Samuel Mannchen, Jonas Mayer, Janis Lion Schőnegg, Klara Fauser
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