Robotics in Agriculture: Automation Solutions for Precision Farming and Sustainability

DOI: https://doi.org/10.63345/ijrmeet.org.v10.i2.5

Dr T. Aswini

KL University

Vadeshawaram, A.P., India

aswini.oleti@gmail.com

Abstract
This manuscript explores the integration of robotics into modern agricultural practices to achieve precision farming and sustainability objectives. Precision farming—the management of crop production that uses detailed information and technological tools—has evolved significantly with the advent of robotic systems capable of automating tasks such as planting, weeding, harvesting, and monitoring. Drawing on engineering principles, this paper examines the state of the art of agricultural robots available up to the end of 2022, classifies their functionalities, and evaluates their performance in terms of accuracy, efficiency, and environmental impact. A mixed-methods approach combines quantitative field trials data with qualitative expert interviews to assess how robotic solutions contribute to resource optimization, yield improvement, and reduced chemical usage. Results indicate that ground-based robots equipped with machine‑vision guidance can reduce herbicide application by up to 85%, while unmanned aerial vehicles (UAVs) improve early disease detection by 40%. However, high initial capital costs and interoperability challenges remain barriers to widespread adoption. Finally, the paper offers engineering‑driven recommendations for overcoming these hurdles and identifies key areas for future development, such as modular robotics architectures and energy‑efficient actuation systems. Results indicate that ground-based robots equipped with machine‑vision guidance can reduce herbicide application by up to 85%, while unmanned aerial vehicles (UAVs) improve early disease detection by 40%. Beyond these headline figures, the analysis also reveals nuanced trade‑offs: small‑scale modular robots offer greater flexibility and lower per‑hectare costs but require more frequent maintenance visits, whereas large autonomous tractors deliver higher throughput at the expense of field accessibility in varied terrains. Lifecycle assessments conducted as part of this research suggest that, when designed for recyclability and powered by renewable energy sources such as solar‑charged batteries, robotic platforms can achieve net‑positive carbon balances over a five‑year deployment horizon. Expert interviews further highlight the pivotal role of standardized communication protocols (e.g., ROS-Industrial) in enabling interoperability among heterogeneous robot fleets and farm management systems. However, high initial capital costs—ranging from $50,000 to $120,000 per unit—and the lack of widespread service networks remain significant barriers to adoption, especially among smallholder farmers. To address these challenges, the paper offers engineering‑driven recommendations for lowering cost through design modularity, leveraging open‑source control frameworks, and developing business models such as cooperative leasing. Key areas for future development include energy‑efficient actuation systems leveraging soft robotics, adaptive machine‑learning algorithms for crop and weed identification under diverse lighting conditions, and integration with advanced IoT architectures for real‑time decision support.

Keywords
Robotics, Precision Farming, Automation, Sustainability, Agricultural Engineering, Machine Vision, UAV, Weeding Robots, Harvesting Automation, Resource Optimization

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