Han Wang, Bingjing Yan, Xiaoxia Li, Xuejing Luo, Qiang Yang, W. Yan
{"title":"On optimal path planning for UAV based patrolling in complex 3D topographies","authors":"Han Wang, Bingjing Yan, Xiaoxia Li, Xuejing Luo, Qiang Yang, W. Yan","doi":"10.1109/ICINFA.2016.7831962","DOIUrl":null,"url":null,"abstract":"The unmanned aerial vehicles (UAVs) have been considered an efficient platform for monitoring critical infrastructures spanning over a large geographical area. In this paper, a novel UAV optimal path planning approach based on the combination of A∗ search algorithm (AS) and ant colony optimization (ACO) algorithm for UAV patrolling is presented. The proposed path planning solution aims to identify the optimal patrolling path in a complex 3D topography given a set of patrolling positions. This study adopts the multiple normal distribution functions to produce the complex topography for the numerical simulation experiments. A set of simulations are carried out to validate and assess the performance of the proposed path planning algorithmic solution. The numerical result demonstrates that the calculated flight path can meet the requirement of UAV patrolling task with the minimized cost.","PeriodicalId":389619,"journal":{"name":"2016 IEEE International Conference on Information and Automation (ICIA)","volume":"15 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Information and Automation (ICIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICINFA.2016.7831962","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
The unmanned aerial vehicles (UAVs) have been considered an efficient platform for monitoring critical infrastructures spanning over a large geographical area. In this paper, a novel UAV optimal path planning approach based on the combination of A∗ search algorithm (AS) and ant colony optimization (ACO) algorithm for UAV patrolling is presented. The proposed path planning solution aims to identify the optimal patrolling path in a complex 3D topography given a set of patrolling positions. This study adopts the multiple normal distribution functions to produce the complex topography for the numerical simulation experiments. A set of simulations are carried out to validate and assess the performance of the proposed path planning algorithmic solution. The numerical result demonstrates that the calculated flight path can meet the requirement of UAV patrolling task with the minimized cost.