The invention discloses an unmanned aerial vehicle autonomous inspection
system and method based on AI identification, the
system comprises an unmanned aerial vehicle body carrying a high-power optical
zoom lens, an
edge computing device and a function module, and the autonomous inspection of a power distribution
tower is realized by fusing front-end AI identification and
edge computing technologies. A Yolo structure is adopted to construct a lightweight
tower recognition model, a dynamic
route planning module is combined to realize single-point reference
route generation and three
obstacle crossing modes, and real-time coordinate correction in an RTK-free environment is supported. The
edge computing device integrates a semi-
supervised learning engine and a multi-sensor data fusion module, meets
miniaturization design, and supports
breakpoint continuous flight control and precise landing. The method covers automatic
route generation, visual tracking,
zoom cooperative control and self-adaptive task scheduling, solves the problems that a traditional unmanned aerial vehicle depends on manual operation, the
data quality is poor and the efficiency is low, realizes whole-course
automation of
tower inspection in a complex environment, and is high in inspection efficiency, and the picture definition reaches the pin level.