China is a country with frequent earthquake disasters. After the occurrence of earthquake disasters, the key to disaster monitoring and rescue is to quickly obtain images of postdisaster areas. Unmanned aerial vehicle (UAV) path planning is the core of multi-UAV cooperative control. With the increasing popularity of UAVs, people with more complex living environments contact with UAVs more frequently, which also poses a challenge to the overall control of UAVs, making single UAV and even multi-UAV cooperative path planning become a hot research issue in recent years. The complexity of communication between aircraft in three-dimensional flight space and multidegree of freedom navigation makes multi-UAV cooperation more challenging. According to the research results at home and abroad, this paper takes multitarget tracking algorithm, ant colony algorithm, and hybrid particle swarm optimization algorithm as research methods. Based on virtual reality technology, by comparing the advantages and disadvantages of several algorithms, the research model of path optimization is established, and a multitarget detection method based on virtual reality technology is established. Through the analysis and improvement of multitarget tracking algorithm, ant colony algorithm, and hybrid particle swarm optimization algorithm, the path optimization problem of UAV after an earthquake based on virtual reality technology is studied. The results show that, compared with the previous research models, the overall optimization efficiency of UAV route is improved by 15%, which is more practical.
The problem of structural deformation monitoring has always been a research hotspot in engineering architecture. Research on structural deformation monitoring is the main way to solve the risk of engineering construction. Based on using close-range photogrammetry technology to monitor structural deformation, combining with image recognition technology to collect and process image data, and using the conditions of direct linear transformation and collinear equation to calculate based on the extracted coordinates of the measuring point, finally, according to the coordinates of the measuring point and the deflection value of the bridge structure, the study is carried out. Experiment: first, five sets of data are used to calibrate the close-range photogrammetry equipment of measurement point accuracy are analyzed, then the bridge piers and the measurement point coordinates, the lasso, under different load on the accuracy of close-range photogrammetry technology is analyzed, according to the relevant data of the error of the close-range photogrammetry technology are analyzed, and through the calculation of different measurement methods to analyze the direct linear transformation manifested in the article. The final results show that the X-axis coordinate range of the measured points in the auxiliary spatial coordinate system is 25∼40, Y-axis coordinate range is 8∼36, and Z-axis coordinate range is 10∼35. The coordinates of measuring points of bridge cables are distributed in the fourth quadrant of the spatial coordinate system. The accuracy values of all coordinates of the measuring points under the close-range photogrammetry equipment are less than 0.1 mm, indicating that the close-range photogrammetry equipment has a good effect on the calibration of measuring points, and the error generated when the load action of each measuring point of the bridge cable is 10 N is greater than that generated when the load action is 20 N. In different calculation and measurement methods, the results obtained by total station measurement and calculation method are reduced by about 0.04∼0.07 m compared with the actual value; the results obtained by direct linear transformation method are increased by about 0.02∼0.04 m compared with the actual value; and the results obtained by other measurement and calculation methods are increased by about 0.04∼0.06 m compared with the actual value.
The number of fragments and the variety of primitive cultural relics unearthed in archaeology, especially the mixed fragments of several dynasties unearthed in Qinglong town, Shanghai, pose a great challenge to the manual splicing. The traditional manual comparison method is easy to cause the second damage to the cultural relics. In this paper, the edge feature is extracted based on removing the noise of point cloud, a bilateral filtering point cloud denoising algorithm based on salient features is proposed. By changing the step size and field of view, the Improved Artificial Fish Swarm Algorithm is used to get the matching strategy, and the point cloud is used to reconstruct 3D model by the Dual Quaternion Transformation method. The pairing of fragments and virtual reconstruction can effectively avoid the secondary damage of cultural relic fragments. It provides a feasible artificial intelligence solution for the protection and restoration of similar archaeological excavations.
Due to the existence of environmental or human factors, and because of the instrument itself, there are many uncertainties in point clouds, which directly affect the data quality and the accuracy of subsequent processing, such as point cloud segmentation, 3D modeling, etc. In this paper, to address this problem, stochastic information of point cloud coordinates is taken into account, and on the basis of the scanner observation principle within the Gauss–Helmert model, a novel general point-based self-calibration method is developed for terrestrial laser scanners, incorporating both five additional parameters and six exterior orientation parameters. For cases where the instrument accuracy is different from the nominal ones, the variance component estimation algorithm is implemented for reweighting the outliers after the residual errors of observations obtained. Considering that the proposed method essentially is a nonlinear model, the Gauss–Newton iteration method is applied to derive the solutions of additional parameters and exterior orientation parameters. We conducted experiments using simulated and real data and compared them with those two existing methods. The experimental results showed that the proposed method could improve the point accuracy from 10−4 to 10−8 (a priori known) and 10−7 (a priori unknown), and reduced the correlation among the parameters (approximately 60% of volume). However, it is undeniable that some correlations increased instead, which is the limitation of the general method.
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