Abstract
Forest soil ripping is a practice that involves revolving the soil in a forest area to prepare it for planting or sowing operations. Advanced sensing systems may help in this kind of forestry operation to assure ideal ripping depth and intensity, as these are important aspects that have potential to minimise the environmental impact of forest soil ripping. In this work, a cost-effective contactless system - capable of detecting and mapping soil ripping depth in real-time - was developed and tested in laboratory and in a realistic forest scenario. The proposed system integrates two single-point LiDARs and a GNSS sensor. To evaluate the system, ground-truth data was manually collected on the field during the operation of the machine with a ripping implement. The proposed solution was tested in real conditions, and the results showed that the ripping depth was estimated with minimal error. The accuracy and mapping ripping depth ability of the low-cost sensor justify their use to support improved soil preparation with machines or robots toward sustainable forest industry.
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Notes
- 1.
https://www.raspberrypi.com/products/raspberry-pi-4-model-b, last accessed on 18/07/2023
- 2.
https://www.simcom.com/product/SIM7600X.html, last accessed on 18/07/2023
- 3.
http://en.benewake.com/TFminiPlus, last accessed on 18/07/2023
- 4.
https://www.qgis.org/en/site, last accessed on 18/07/2023
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Acknowledgements
This work is financed by National Funds through the Portuguese funding agency, FCT - Fundac̨ão para a Ciência e a Tecnologia, within project LA/P/0063/2020. This work was also co-financed by the ERDF - European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 under the PORTUGAL 2020 Partnership Agreement, as a part of project “Project Replant - POCI-01-0247-FEDER-046081”. Daniel Queirós da Silva thanks the FCT-Foundation for Science and Technology, Portugal for the Ph.D. Grant UI/BD/152564/2022.
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da Silva, D.Q. et al. (2024). Assessing Soil Ripping Depth for Precision Forestry with a Cost-Effective Contactless Sensing System. In: Marques, L., Santos, C., Lima, J.L., Tardioli, D., Ferre, M. (eds) Robot 2023: Sixth Iberian Robotics Conference. ROBOT 2023. Lecture Notes in Networks and Systems, vol 978. Springer, Cham. https://doi.org/10.1007/978-3-031-59167-9_25
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