Project Details
Description
Agricultural robotics solutions can integrate a variety of robots for a variety of monitoring and targeted intervention tasks, to increase farm productivity, efficiency and sustainability through support of automated precision farming operations. Despite the rising farmer investment in farm/agricultural robots, most deployable robotic systems are meant to automate only specific tasks. The wide variety of tasks that need to be fulfilled in a single precision agriculture operation or mission makes it extremely unprofitable to address its automation with task-specific robots. These challenges result in a lack of flexibility of current heterogeneous multi-robot systems that poses low returns on investment and high risks for farmers. In order to become cost-effective, heterogeneous multi-robot systems needs to become more flexible by employing more versatile (e.g. multi-task) robots which collaborate to accomplish complex missions; ensuring scalable human oversight and intervention through adaptive mission control mechanisms (e.g. without information overload /overwhelming effort from the farmer); allowing the farmer to profit from robotics operational data. FlexiGroBots proposes a Platform for developing heterogeneous multi-robot systems and applications which allows for i) more versatility by using the same robots for different observation and intervention tasks, in different missions, throughout the crop life cycle, ii) more cooperation between heterogeneous (ground and aerial) robots to accomplish more complex missions; iii) more valuable data to generate accurate insights into the fields, crops and robotics operations by combining data from IoT sensors, satellites and data collected by the robots; iv) more autonomy for real-time adaptation of mission plans as well as robot behaviour at the crop level, given operational conditions and real-time insights; v) more precision to carry out specific tasks in a very localized way, gaining accuracy and lowering costs.
| Acronym | FLEXIGROBOTS |
|---|---|
| Status | Finished |
| Effective start/end date | 1/01/21 → 31/12/23 |
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Research output
- 8 Article
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Comparative analysis of single-view and multiple-view data collection strategies for detecting partially-occluded grape bunches: Field trials
Ariza Sentis, M., Baja, H., Velez Martin, S., van Essen, R. & Valente, J., 1 Mar 2025, In: Journal of Agriculture and Food Research. 19, 101736.Research output: Contribution to journal › Article › Academic › peer-review
Open Access1 Link opens in a new tab Citation (Scopus) -
EscaYard: Precision viticulture multimodal dataset of vineyards affected by Esca disease consisting of geotagged smartphone images, phytosanitary status, UAV 3D point clouds and Orthomosaics
Vélez, S., Ariza-Sentís, M. & Valente, J., Jun 2024, In: Data in Brief. 54, 110497.Research output: Contribution to journal › Article › Academic › peer-review
Open Access12 Link opens in a new tab Citations (Scopus) -
Object detection and tracking in Precision Farming: a systematic review
Ariza-Sentís, M., Vélez, S., Martínez-Peña, R., Baja, H. & Valente, J., Apr 2024, In: Computers and Electronics in Agriculture. 219, 108757.Research output: Contribution to journal › Article › Academic › peer-review
Open Access113 Link opens in a new tab Citations (Scopus)
Datasets
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Dataset on UAV RGB videos acquired over a vineyard property of Bodegas Terras Gauda at an early stage of Botrytis cinerea infection in 2021
Ariza Sentís, M. D. M. (Creator), Velez Martin, S. (Creator) & Pereira Valente, J. (Creator), Wageningen University & Research, 8 Nov 2021
Dataset
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MOTS-annotated UAV Vineyard Dataset captured using Multiple Perspectives to avoid Leaf Occlusion for Object Detection and Tracking
Ariza Sentis, M. (Creator), Wang, K. (Creator), Cao, Z. (Creator), Velez Martin, S. (Creator) & Pereira Valente, J. (Creator), Wageningen University & Research, 7 Feb 2024
Dataset
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UAV multispectral imagery dataset over a vineyard affected by Botrytis in 'Tomiño', Pontevedra, Spain. It includes GPS location of vine trunks, diseases and GCP points.
Vélez, S. (Creator), Ariza-Sentís, M. (Creator) & Valente, J. (Creator), Wageningen University & Research, 9 Sept 2022
Dataset