Research On UAV Cloud Control System Based On Ant Colony Algorithm

With the advent of the cloud era,high-tech technologies such as cloud computing,big data,and the Internet of Things are developing rapidly.The processing of massive data through cloud servers to achieve system control has become a very important research direction in the future.Cloud computing is applied to control.In the field,cloud control came into being.UAVs are the focus of research in various countries and have broad application prospects in many fields.However,with the increase in UAV clusters and perception data,it is difficult for UAVs to process data in time and cannot meet the requirements of real-time control.Cloud-controlled The emergence has just solved the difficulties faced by the development of UAVs,so it is of great significance to study the cloud control of UAVs.This paper uses Qt software to design the client interface of the UAV cloud control,introduces the artificial potential field method into the ant colony algorithm for UAV path planning and obstacle avoidance,and deploys the improved potential field ant colony algorithm to the cloud server to achieve control.The cloud control of man-machine was finally verified.The main work of this paper includes the following aspects:First,the overall requirements of the UAV cloud control system are designed.The system contains three main parts,namely,the UAV cloud control client design,the cloud man-machine cloud control server-side design,and the improvement of the ant colony path planning algorithm.According to the main content of the research,the overall structure of the UAV cloud control system is designed,and the working mode of the system is designed and studied.Then,the ant colony algorithm is improved to establish an environmental model for UAV navigation.Aiming at the shortcomings of the ant colony algorithm that is easy to fall into local optimum and the early convergence speed is slow,the artificial potential field method is introduced in the update strategy of pheromone,potential field function and The ant colony algorithm is improved from three aspects of the heuristic function,and the improved strategy of the improved algorithm is designed.The final simulation results show that the improved potential field ant colony algorithm shortens the optimal path distance by 6.7%and the algorithm running time by 39.3%compared with the previous improvement.the stability is increased by 24.1%,which proves the effectiveness of the improved algorithm in this paper for UAV path planning.The improved algorithm is deployed to the cloud to reduce the delay caused by the system operation,so that the system can better control the system in real time.Then,according to the functional requirements of the UAV cloud control system client,three modules of data management,map realization,and data communication are designed.The MySQL database is used to realize the data storage management,the WebEngineView control is used to realize the embedded map function,and the design is based on TCP./IP protocol and multi-threaded working mode of socket programming for data communication.Finally,the focus is on the design of the cloud server,the structure of the UAV cloud control system is designed based on the C/S model,the specific Alibaba Cloud ECS instance specifications are configured,the file upload and the deployment of the cloud environment are realized based on xshell,and the unmanned system is designed on the server.The monitoring function of the machine cloud control system ensures the normal operation of the system.The different structures of the data tables in the MySQL database are designed to facilitate the storage of the data of the UAV.Design the server-side multi-threaded program and communication data format to facilitate receiving client data,and design the communication completion port to avoid communication blockage.The communication test of the system showed that the data packet loss rate was 0.2%,and the average network delay was 29ms.The overall experiment realized remote cloud control of the UAV.It is of great significance to the remote control and large-scale application of drones in the era of big data.