Agricultural and Field Robotics

The Section “Agricultural and Field Robotics” publishes original peer-reviewed papers in the field of autonomous and semi-autonomous robotic systems designed to operate in outdoor, unstructured, and dynamic environments such as forests, farms, and natural landscapes. Theoretical and experimental studies, as well as comprehensive reviews, are considered. This Section seeks to advance the state of the art in robotic systems that support agriculture, forestry, and environmental monitoring by leveraging innovations in perception, mapping, control, and AI-driven decision-making. Special emphasis is placed on systems that address real-world constraints, including rough terrain, variable weather, safety, and the need for robust human–robot collaboration.

This Section provides a platform for scientists, engineers, and practitioners to share the latest results in agricultural and field robotics and to foster discussions on present challenges and future directions. It aims to connect contributions spanning from fundamental research to application-driven deployments, enabling technology transfer into practical agricultural and forestry practices.

Topics addressed in this Section include but are not limited to the following:

• Robust robotic design for harsh environments, including protective systems for electronics;
• Energy-efficient and sustainable design for field robots;
• Drive systems, locomotion strategies and maneuverability for unstructured outdoor environments;
• Robotic manipulation for agricultural and forestry tasks;
• Weeding, planting, spraying, and harvesting with autonomous or semi-autonomous machines;
• Soil analysis, irrigation, and nutrient management supported by robotics;
• Crop monitoring, yield estimation, and phenotyping using robotic platforms;
• Robotics for aquaculture, horticulture, and livestock monitoring;
• Aerial, ground, and hybrid robotic platforms for monitoring, mapping, and intervention;
• Autonomous systems for wildfire prevention, forest cleaning, and fuel management;
• Traversability analysis and terrain classification;
• Path planning, obstacle avoidance, and autonomous navigation in outdoor settings;
• Human–robot interaction and safety in agricultural and forestry applications;
• Multisensory systems and sensor fusion (LIDAR, depth cameras, multispectral imaging, etc.).
• Cooperative perception, and multi-robot systems in field operations;
• Sensing, perception and learning (e.g., neural networks for perception) in unstructured outdoor environments;
• Robot localization and outdoor entity tracking and detection in complex terrains;
• 3D registration, semantic segmentation, and metric-semantic mapping for field robotics;
• AI-driven control, planning, and optimization in field robotics;
• Integration of UAVs, UGVs, and sensor networks for agricultural automation;
• Digital twins and simulation environments for agricultural and forestry robotics;
• Long-term autonomy and reliability in changing environmental conditions;
• Datasets, benchmarking, and performance evaluation for agricultural and field robotics;
• Applications of robotics in precision agriculture, agroforestry, wildfire management, landscape clearing, and environmental monitoring;
• Case studies, prototyping, and deployment of agricultural and forestry robotic systems.
• Regulatory, ethical, legal, societal, economic and safety aspects of autonomous agroforestry machinery operation and development.