农业无人机在丘陵山地环境中的技术适应性与优化路径综述OA

Hilly and mountainous areas are important production regions for grain and oil crops,fruits,vegetables,tea,and characteristic cash crops in China.However,complex terrain,fragmented plots,dense low-altitude obstacles,and unstable local wind fields have long restricted the trafficability,continuity,and efficiency of conventional ground-based agricultural machinery.Agricultural unmanned aerial vehicles have the advantages of vertical takeoff and landing,high maneuverability,and low dependence on ground traffic conditions,providing important equipment support for mechanized and intelligent agricultural operations in hilly and mountainous environments.Focusing on the technical adaptability and optimization pathways of agricultural UAVs in such environments,this review systematically summarizes domestic and international research progress and analyzes the environmental characteristics of hilly and mountainous farmland in terms of terrain and spatial structure,operational complexity,microclimatic conditions,and their influence mechanisms on UAV operations.Furthermore,the adaptability of key technologies is discussed from the perspectives of flight platforms,power systems,navigation and positioning,terrain-following flight,precision spraying,environmental perception,and obstacle avoidance.The analysis indicates that agricultural UAVs in hilly and mountainous areas still face several challenges,including insufficient flight stability,degraded positioning reliability,fluctuating operation accuracy,low path-planning efficiency,limited edge intelligence,and high application costs.Future development should focus on specialized platform design,multi-source fusion positioning,terrain-following flight control,variable-rate precision operation,multi-UAV cooperative scheduling,data-driven service systems,and the construction of operational standards.These efforts are expected to improve the safety,precision,and large-scale application capability of agricultural UAVs in hilly and mountainous environments.