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The use of UAVs for geographic information mapping is a relatively mature technology. It has the advantages of a large measurement range, fast data collection speed and high efficiency. It is gradually becoming an important technical means that can partially replace traditional field measurement. 3D modeling of UAV image data is an important aspect of UAV surveying and mapping applications. Under the current background of “real China” and “digital twin”, UAV modeling will have very broad application prospects. The current UAV modeling is mainly based on large fixed-wing UAVs or professional rotary-wing UAVs, but their prices are relatively high, so this paper tries to use a relatively low-priced consumer-grade UAV-DJI Yu 2, the professional version of the UAV performs image control-free 3D modeling without ground control points and analyzes the accuracy of the results to verify its applicability in geographic information data collection.

Workshop facility layout belongs to a kind of combinational optimization problem, which has the characteristics of nonlinearity and not being easily solved with conventional methods, therefore it is regarded as a typical NP hard problem. This paper proposed a crowding niche cellular genetic algorithm. By introducing niche crowding technology to select the best individuals, the population diversity was well maintained. On the other hand, neighbors in cellular automata were adopted to study more on the cellular topological optimization structure, which enhanced the global searching ability of the algorithm. In addition, multi-line workshop facility layout problem has been optimized in the paper, which verified that the crowding niche cellular genetic algorithm was effective and applicable.