AGRHOUND Operational Group: Intelligent robotics for monitoring and agronomic decision-making in high-value crops.
- Type Operational group
- Status In progress
- Execution 2026 -2029
- Assigned Budget 594.129,00 €
- Scope Supraautonómico
- Autonomous community Andalucía; Extremadura; Rioja, La
- Main source of financing CAP 2023-2027
Onboard sensor system: The robot will incorporate integrated and calibrated sensors that will allow measuring the physiological state of the crop in the field (maturity, vigor and associated variables) with reliable data comparable to traditional analysis methods.
Georeferenced ripening map platform: A cloud-based system will be developed that will convert the data collected by the robot into clear and operational maps, facilitating practical decisions for the farmer regarding harvesting, zoning, and differential management within the plot.
Autonomous guidance system for intelligent sampling: The robot will be able to automatically select and traverse the most representative areas of the crop to perform optimized sampling, reducing working times and improving the representativeness of the data obtained.
Artificial vision models for yield estimation: Algorithms will be implemented that will allow automatic estimation of production and maturity level from images captured in the field, reducing dependence on manual counts and improving harvest planning.
Comprehensive validation of the system in real-world operation: The complete system will be tested under real production conditions, demonstrating its accuracy, robustness, and replicability in other farms with similar characteristics.
Dissemination Plan. Effective Internal Communication. A structured communication strategy is established that unifies the project's message, defines responsibilities, and sets specific dissemination tools. All partners work under the same visual identity and narrative, using common materials and a coordinated schedule. Furthermore, stable internal coordination mechanisms are implemented (regular meetings, shared digital tools, and continuous monitoring), which allows for the detection of deviations, anticipation of risks, and maintenance of technical and communicative consistency throughout the project's execution.
Dissemination and technology transfer are achieved through participation in events and the organization of project-specific workshops. The developed technology is presented directly to the agricultural sector at leading agricultural fairs and at dedicated demonstration workshops. This allows for showcasing real-world progress, explaining how the system works under practical conditions, and gathering direct feedback from producers and technicians. Intermediate workshops validate the sector's interest before the project's completion, while the final workshop consolidates the results and facilitates their adoption.
Project dissemination through virtual activities. Continuous dissemination is maintained through digital media, ensuring that project progress is accessible throughout its execution. Publication on the web, the EU-FarmBook platform, social media, and newsletters allows access to both specialized and general audiences. Audiovisual material facilitates understanding of the robotic system and its benefits, demonstrating its operation in a real-world environment.
Publications. The knowledge generated is transformed into formal and structured content, disseminated through press releases, technical and scientific articles, and a final publication of results. This allows the innovation to be transferred to both the professional and scientific spheres, reinforcing the project's technical credibility and ensuring that the results remain available beyond its completion.
A fully operational and validated quadruped robot for autonomous or guided movement in two real-world agricultural systems: open-air vineyards and blackberry cultivation in macro-tunnels. An onboard system of machine vision sensors capable of obtaining precise data on the physiological state of the fruit in the field. Remote processing software for quickly generating and visualizing georeferenced maps of ripening and vigor status by plot. User interface. An autonomous guidance system for selecting and traversing sampling areas, based on spatial variability patterns and agronomic logic. Onboard machine vision algorithms for estimating yields in vineyards and blackberry orchards, validated against manual counts and actual production. Technical evaluation of the complete system under real production conditions, including metrics for effectiveness, robustness, accuracy, replicability, and scalability.
In the first phase, the design and adaptation of the robotic platform are addressed, optimizing its structure, stability, and movement capabilities in open-air vineyards and blackberry orchards under macro-tunnels. This is followed by performance trials under real-world conditions and the prototyping of at least two replicable functional units. Subsequently, the onboard sensors are integrated, and the data capture and synchronization systems are developed, including their validation and calibration in the laboratory and field to ensure accuracy and reliability. In parallel, interpolation algorithms and georeferenced map generation are implemented, along with a remote visualization platform to facilitate agronomic decision-making. The project also incorporates the development of advanced navigation and autonomous guidance systems, based on spatial variability criteria and agronomic logic, enabling intelligent routes, precise plant approach, and autonomous execution of inspection and sampling tasks. Finally, the agronomic characterization of the pilot plots is carried out, the training of artificial vision models for estimation of production and quality, and the comprehensive validation of the system in real production environments, evaluating its effectiveness, precision, robustness and scalability.
Develop and validate a quadruped robotic system as an example of Agriculture 5.0, with onboard sensors and intelligent processing for autonomous decisions in high-value crops.
- Coordinator/Entity Name: JUAN JOSÉ MANZANERO INIESTO/BUSINESS ASSOCIATION FOR RESEARCH NATIONAL AGRO-FOOD TECHNOLOGICAL CENTER EXTREMADURA (CTAEX)
- Postal address: CRTA VILLAFRANCO-BALBOA, KM 1.2, 06005, BADAJOZ
- Email coordinator/entity: proyectos@ctaex.com
- Telephone: +34 924448077
- JUAN JOSÉ MANZANERO INIESTO/ASOCIACIÓN EMPRESARIAL DE INVESTIGACIÓN CENTRO TECNOLÓGICO NACIONAL AGROALIMENTARIO EXTREMADURA (CTAEX)
- SOLTEL IT SOLUTIONS SL
- DRONICA SOLUTIONS SL
- BODEGA MATARROMERA SL
- SOCIAL BERRIES 4.0 SA