AI-Driven Optimization in Robotics and Precision Agriculture

Dear Colleagues,

This Special Issue aims to highlight cutting-edge advancements in the integration of artificial intelligence, robotics, and precision agriculture, with a particular focus on computational optimization and intelligent automation. We invite high-quality original research, reviews, and case studies that explore how AI-driven methodologies can be leveraged to enhance agricultural robotics, decision-making, and field operations.

As modern agriculture increasingly relies on robotics, embedded systems, and real-time decision-making, the integration of AI with high-performance computing (HPC), heterogeneous architectures (including CPUs, GPUs, and FPGAs), and IoT-enabled platforms has become essential. This Special Issue seeks to showcase contributions that harness AI to optimize robotic performance, enhance autonomy, and improve the overall efficiency and sustainability of precision farming operations.

Topics of interest include, but are not limited to, the following:

• AI-based optimization algorithms for agricultural robotics;
• Embedded and real-time AI systems in field environments;
• FPGA and heterogeneous acceleration for robotics applications;
• Sensor fusion, perception, and decision-making in precision agriculture;
• IoT and edge computing frameworks for smart farming;
• Reinforcement learning and computer vision for autonomous systems;
• Scalable HPC architectures for agricultural data analysis;
• Generative AI for simulation, synthetic data generation, and predictive modeling in agricultural systems;
• Augmented reality (AR) for operator training, remote supervision, and interactive agricultural planning;
• Serious games for modeling, simulation, and stakeholder engagement in smart farming and robotics education;
• Digital twins for modeling, simulation, and real-time optimization of agricultural environments and robotic systems;
• Field-level implementations and deployments of AI-powered robotic platforms in real agricultural settings;
• Case studies on operational installations demonstrating practical challenges and performance of AI-integrated systems in precision farming.

Dr. Dimitris Ziouzios
Dr. Minas Dasygenis
Guest Editors

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