This paper presents the identification of the functional requirements and development of a preliminary concept of the AgriRover, a low-cost, modular autonomous vehicle intended to support sustainable practices in traditional vineyards in developing countries, focusing on the Ica region of Peru. Viticulture in this region faces acute challenges such as soil salinity, climate variability, labour shortages, and low technological readiness. Rather than offering a ready-made technological integration, this study adopts a step-by-step design approach grounded in the realities of smallholder farmers. The authors mapped the phenological stages of grapevines using the BBCH scale and systematically reviewed available sensing and monitoring technologies to determine the most context-appropriate solutions. Virtual modelling and preliminary analysis validate AgriRover’s geometric configuration and path-following capabilities within narrow vineyard rows. The proposed platform is meant to be adaptable, scalable, and maintainable using locally available material and human resources. AgriRover offers a practical and affordable foundation for precision agriculture in resource-constrained settings by aligning viticultural challenges with sensor deployment strategies and sustainability criteria. The sustainability analysis of the initial AgriRover concept was evaluated using the CML methodology, accounting for local waste processing rates and energy mixes to reflect environmental realities in Peru.

The current global context demands the development of new solutions that prioritize energy efficiency, time optimization, safety, and sustainability. Urban transportation is one of the sectors undergoing significant transformation. Pursuing new urban transportation solutions has become increasingly intense, involving research institutions and companies. Considering this context, this study focused on the optimization procedures for designing a new vehicle capable of vertical take-off for urban air mobility applications. This paper reports on the optimization process of a thruster deployment mechanism using statistical techniques. In particular, the authors tested the use of Design of Experiments (DOE) techniques for the optimal design of a structural component of a new vehicle for urban mobility purposes under development at the Applied Mechanics laboratory of the Department of Industrial Engineering of the University of Salerno. For this reason, it was decided that a parametric multibody model would be developed in the Simscape Multibody environment for structural optimization using designed experiment plans to “guide” the designer in the analysis phase and search for an optimal configuration using a minimum number of configurations. Finally, employing FEM analysis, the chosen configuration was validated. This study allowed us to test the use of DOE techniques to design new systems. It allowed us to evaluate different configurations, the static and dynamic behavior, the constraining reactions present in the joints, and the active forces and torques of the actuators, highlighting the correlation between factors that can guide the designer in identifying optimal solutions.

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.