Work

Towards Human-Robot Interaction in Agriculture Using Large Language Models

Year: 2025

Type: conference-paper

Abstract: Labor shortages and usability challenges limit the adoption of robotics in agriculture.This work explores how Large Language Models (LLMs) and Vision-Language Models (VLMs) can bridge this gap by enabling non-expert users to command robots using natural language.A modular system was developed to interpret instructions, execute tasks, and generate visual field reports.Evaluations in a simulated field showed that hybrid prompting strategies yielded reliable plans, while VLMs supported effective object detection and contextual reporting.This approach reduces entry barriers to robotics and promotes accessible, intelligent agricultural automation.

Source: Annals of Computer Science and Information Systems

DOI: 10.15439/2025f0373

Authors: Lavanyan Rathy, Håvard Pedersen Brandal, Weria Khaksar

Institution: Norwegian University of Life Sciences

Language: English

Topic: Smart Agriculture and AI

Subfield: Plant Science

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDG: Zero hunger

Open Access status: diamond

Funders: Science Foundation Ireland, Norges Forskningsråd