Research Progress on Autonomous Navigation and Multi-Robot Cooperative Operation of Intelligent Agricultural Machinery

This paper introduces the research progress of path planning, trajectory tracking control, and multi-machine collaborative operation systems for agricultural robots. It summarizes the development laws of 3D terrain modeling and adaptive path planning algorithms for complex agricultural environments such as hills and mountains, and analyzes the dynamic disturbance characteristics of agricultural machinery under slip, sideslip, and dynamic load changes. Through comprehensive analysis, it is found that traditional kinematic control models have limitations in complex and unstructured environments. Combining soil mechanics mechanisms, variable load identification, and robust control strategies is key to improving trajectory tracking stability and operational quality. In terms of multi-machine collaboration, this paper discusses master–slave collaboration, distributed control, and task allocation modes. It further identifies that the stability of collaboration and interoperability standards between devices in weak network environments are currently the main bottlenecks limiting the large-scale application of this technology. Finally, this paper provides prospects for future research directions and suggests strengthening the closed-loop integration of perception, decision-making, and dynamic models, establishing industry unified standards, and enhancing the safety of the entire lifecycle of operations, providing suggestions for the unmanned application of agricultural robots.