Abstract
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.
Highlights
With the continuous development of artificial intelligence technology, unmanned aerial vehicle (UAV) autonomous flight technology has been widely concerned and studied by the academic community
If the time limit is considered, the scale will be increased to four dimensions, which will cause the problem of “scale disaster” in the planning process. erefore, how to choose an appropriate algorithm to develop an optimal path planning system for multiple UAVs is the main problem in the field of UAV research
Xu proposed a distributed 3D AOA target tracking method which is composed of a distributed estimator and multi-UAV path optimization algorithm and a new 3D distributed pseudolinear Kalman filter (DPLKF) to Mathematical Problems in Engineering improve the stability of the solution of the extended Kalman filter
Summary
With the continuous development of artificial intelligence technology, unmanned aerial vehicle (UAV) autonomous flight technology has been widely concerned and studied by the academic community. The six algorithms of Chen were compared and simulated, and the problem of angle of arrival tracking using multiple UAVs in three-dimensional space was studied [2]. En, according to the different requirements of mission UAV, Li proposed a path optimization method for relay UAV based on the weighted and ergodic capacity maximization criteria [5]. On this basis, the exact outage probability and closed-form ergodic capacity of relay links are derived to quantify the system performance. The optimal path of the relay UAV in the two simulation scenarios is given
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