Author
Listed:
- Mohammad Naim
(UniLaSalle, INTERACT - Innovation, Territoire, Agriculture et Agro-industrie, Connaissance et Technologie - UniLaSalle, UTC - Université de Technologie de Compiègne)
- Davide Rizzo
(UMR LISAH - Laboratoire d'étude des Interactions Sol - Agrosystème - Hydrosystème - IRD - Institut de Recherche pour le Développement - AgroParisTech - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement)
- Maryem Cherni
(UniLaSalle, INTERACT - Innovation, Territoire, Agriculture et Agro-industrie, Connaissance et Technologie - UniLaSalle)
- Marco Medici
(UniLaSalle, INTERACT - Innovation, Territoire, Agriculture et Agro-industrie, Connaissance et Technologie - UniLaSalle)
- Loïc Sauvée
(UniLaSalle, INTERACT - Innovation, Territoire, Agriculture et Agro-industrie, Connaissance et Technologie - UniLaSalle)
Abstract
The poster presents the doctoral research of Mohammad Naim, conducted within the French national project NINSAR (New ItiNerarieS for Agroecology using cooperative Robots), and outlines how the thesis contributes to this broader research programme. The NINSAR project, as framed in the poster title and structure, is positioned as a national effort to define agroecological routes using robotics, integrating technological innovation with ecological, social, and economic sustainability goals. Within this context, the thesis investigates how autonomous agricultural systems can be designed, evaluated, and adopted without compromising core agroecological principles. The thesis analyzes the transition from Agriculture 4.0 to Agriculture 5.0 through the thirteen agroecological principles defined by the High Level Panel of Experts, assessing how emerging robotic and data-driven systems can support more sustainable production models. It evaluates three major categories of robotic field operations (data collection, soil and crop management, and navigation/communication) and links them to four principle-level agroecological indicators, finding strong contributions to soil health and synergy and weaker support for recycling. The work also conducts an empirical study of French farmers using the Technology Acceptance Model 2, identifying perceived usefulness as the central predictor of adoption, complemented by ease of use and social influence. A complementary technical study clusters 71 agricultural robots into five functional categories, illustrating the increasing specialization of robotic platforms and cost differences between electric and endothermic systems. The thesis further extends to the economic and industrial dimension of the NINSAR project by engaging manufacturers through semi-structured interviews to construct business model canvases aimed at identifying viable pathways for scaling agroecological robots. Taken together, the poster shows that Naim's thesis forms a core component of NINSAR by integrating agronomic, technological, social, and economic analyses to support the development of robotics aligned with agroecological transition goals.
Suggested Citation
Mohammad Naim & Davide Rizzo & Maryem Cherni & Marco Medici & Loïc Sauvée, 2025.
"NINSAR Project: Defining Agroecological Routes Using Robots [Projet NINSAR : Définition des itinéraires agroécologiques utilisant les robots],"
Post-Print
hal-05380224, HAL.
Handle:
RePEc:hal:journl:hal-05380224
DOI: 10.5281/zenodo.17700793
Note: View the original document on HAL open archive server: https://hal.science/hal-05380224v1
Download full text from publisher
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