Special Session Ⅶ

Intelligent Robotic Technologies for Empowering Future Agriculture

Chair
Zhongzhi Han Qingdao Agricultural University, China
Co-Chairs
Haidong You Qingdao Agricultural University, China		Lin Li Qingdao Agricultural University, China

Keywords: Agricultural Robotics, Intelligent Perception and Decision-Making, Autonomous Unmanned Systems, Multi-Robot Collaboration, Precision Agriculture, Agricultural Automation

Special Session Information: 

Intelligent robots face a unique set of complex challenges in perception, decision-making, and execution within agricultural environments. These include achieving robust visual perception and navigation in unstructured and dynamically changing field conditions; performing dexterous manipulation for randomly distributed crops with diverse morphologies, while balancing efficiency and success rates; coordinating multi-platform systems (e.g., UAVs and UGVs) for collaborative task allocation and formation control under field uncertainties; and enabling end-to-end intelligent decision-making from perceptual data to operational policies for large-scale and diversified farming scenarios. These challenges impose stringent requirements on the environmental adaptability, task intelligence, and operational economy of robotic systems.

This session aims to concentrate on employing advanced intelligent robotic technologies to address the aforementioned challenges. We encourage submissions on cutting-edge methods that enhance the environmental interaction capabilities of agricultural robots, including robust decision-making frameworks that fuse multi-modal perception, AI large-scale models, and prior knowledge; the development of lifelong learning and meta-learning control strategies that adapt to crop growth cycles and dynamic field conditions; and the construction of integrated robotic systems incorporating specialized mechanism design, intelligent actuation, and low-power computing. We cordially invite high-quality research contributions in mechanism innovation, algorithm design, system integration, and field application validation, collectively advancing robotic technologies that can tangibly empower the future of agriculture.

Topics of interest include but are not limited to:

• Robust Perception and Navigation in Agricultural Unstructured Environments

• Crop Recognition and Dexterous Manipulation for Autonomous Operations

• Multi-Platform Collaboration and Swarm Control for Agricultural Robots

• Data-Driven and AI Large Model-Empowered Decision-Making for Agricultural Robots

• Specialized Mechanism Design and Intelligent Actuation for Field Operations

• Continuous Learning and Adaptive Control for Agricultural Robots

• Integration, Verification, and Economic Analysis of Agricultural Robot Systems

• Paradigms and Interfaces for Human-Robot Collaboration in Complex Agricultural Tasks