Author
Listed:
- Zandra Betzabe Rivera Chavez
(Department of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 84084 Fisciano, Italy)
- Alessia Porcaro
(MEID4, University Spin-Off and Research Institution for AI-Based Innovation, Via Rosa Jemma 2, 84091 Battipaglia, Italy)
- Marco Claudio De Simone
(Department of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 84084 Fisciano, Italy)
- Domenico de Falco
(Department of Engineering, University of Campania “Luigi Vanvitelli”, Via Roma 29, 81031 Aversa, Italy)
- Domenico Guida
(Department of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 84084 Fisciano, Italy)
Abstract
AgriRover was developed to address key operational constraints faced by smallholder vineyards in Peru, including sandy and saline soils, labor shortages, and limited access to advanced agricultural machinery. The platform features an articulated, all-wheel-drive chassis designed to ensure mobility and stability on loose terrain while minimizing soil compaction. This study presents the simulation-driven development of a digital pre-twin, conceived as a virtual prototype prepared for future sensor integration but currently operating without real-time data feedback. The pre-twin was implemented in MATLAB/Simulink (vers. 2024b) using a multibody dynamics model and evaluated through eight scenario-based simulations, varying field geometry, soil type, and slope conditions. The results show stable operation on slopes up to 10°, wheel sinkage values ranging between approximately 20 and 45 mm depending on terrain conditions, and a moderate battery state-of-charge reduction across most scenarios, with higher power demand observed on sandy soils. A scenario-based comparison indicates a potential reduction of approximately 50% in total monitoring time relative to manual field scouting, while advanced sensing, autonomous navigation, and AI-based analytics remain part of future developments. The current pre-twin provides a validated, low-cost foundation for context-specific phenological monitoring and early-stage precision agriculture applications in developing regions.
Suggested Citation
Zandra Betzabe Rivera Chavez & Alessia Porcaro & Marco Claudio De Simone & Domenico de Falco & Domenico Guida, 2026.
"A Low-Cost Autonomous Rover for Proximal Phenological Monitoring in Vineyards: Design and Virtual Evaluation,"
Sustainability, MDPI, vol. 18(5), pages 1-27, February.
Handle:
RePEc:gam:jsusta:v:18:y:2026:i:5:p:2269-:d:1872653
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