To break through the technical bottlenecks of traditional UAVs in scene reproduction accuracy, situational awareness efficiency, and real-time data processing, and to promote the development of UAV technology towards intelligence, collaboration, and high precision, this paper systematically develops and elaborates on three core technology systems: real-scene multi-modal AI fusion modeling technology, global situational intelligent perception and collaboration technology, and multi-modal data real-time fusion technology based on sparse representation. In terms of technical performance, the real-scene modeling accuracy reaches the centimeter level, and the global perception response speed is increased to the millisecond level. By building a hardware verification platform and a software simulation system, application tests have been completed in scenarios such as smart cities, power inspection, and geological exploration. The results show that this technology system can achieve an equipment defect recognition rate of 97.8% and improve the inspection path planning efficiency by 40%, providing key technical support for the efficient operation of UAVs in complex environments. At present, the relevant technologies have been piloted in a number of power enterprises and municipal units, with potential for large-scale promotion, and are of great significance for promoting the upgrading of the UAV industry and the development of the digital economy.
Yang et al. (Sat,) studied this question.
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