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内蒙古自治区呼和浩特市赛罕区大学西街235号 邮编: 010021
作者机构:School of Intelligent Science and EngineeringHarbin Engineering UniversityHarbin 150001China
出 版 物:《Journal of Systems Engineering and Electronics》 (系统工程与电子技术(英文版))
年 卷 期:2022年第33卷第4期
页 面:805-811页
核心收录:
学科分类:12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 081105[工学-导航、制导与控制] 082503[工学-航空宇航制造工程] 0835[工学-软件工程] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术(可授工学、理学学位)]
基 金:supported by the Natural Science Foundation of Heilongjiang Province (LH2021E045)
主 题:ant colony algorithm potential field method cloud server path planning
摘 要:In the cloud era, the control objects are becoming larger and the information processing is more complex, and it is difficult for traditional control systems to process massive data in a timely manner. In view of the difficulty of data processing in the cloud era, it is extremely important to perform massive data operations through cloud servers. Unmanned aeriel vehicle(UAV) control is the representative of the intelligent field. Based on the ant colony algorithm and incorporating the potential field method, an improved potential field ant colony algorithm is designed. To deal with the path planning problem of UAVs, the potential field ant colony algorithm shortens the optimal path distance by 6.7%, increases the algorithm running time by39.3%, and increases the maximum distance by 24.1% compared with the previous improvement. The cloud server is used to process the path problem of the UAV and feedback the calculation results in real time. Simulation experiments verify the effectiveness of the new algorithm in the cloud environment.