{"title":"基于图像的四轴飞行器高度变化识别算法的开发","authors":"N. Pah, Henry Hermawan","doi":"10.1109/ICITEED.2015.7408916","DOIUrl":null,"url":null,"abstract":"Quadcopter, a popular Unmanned Aerial Vehicle (UAV), is able to land, take off, hover, and move on 3D trajectory. The ability requires accurate control of the rotors velocity based on input from its sensors. One of the control mechanisms is the altitude control. This paper presents a new algorithm to identify altitude change of a quadcopter based on image processing techniques. The algorithm is designed to be simple and efficient in terms of computation and memory usage. The algorithm identifies altitude change by calculating correlation function of 10 sampled rows of pixels. This paper also presents some experiments conducted to investigate the performance of the algorithm. The results indicated that the algorithm is able to properly identify altitude change with accuracy of more than 96%.","PeriodicalId":207985,"journal":{"name":"2015 7th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"The development of image-based algorithm to identify altitude change of a quadcopter\",\"authors\":\"N. Pah, Henry Hermawan\",\"doi\":\"10.1109/ICITEED.2015.7408916\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Quadcopter, a popular Unmanned Aerial Vehicle (UAV), is able to land, take off, hover, and move on 3D trajectory. The ability requires accurate control of the rotors velocity based on input from its sensors. One of the control mechanisms is the altitude control. This paper presents a new algorithm to identify altitude change of a quadcopter based on image processing techniques. The algorithm is designed to be simple and efficient in terms of computation and memory usage. The algorithm identifies altitude change by calculating correlation function of 10 sampled rows of pixels. This paper also presents some experiments conducted to investigate the performance of the algorithm. The results indicated that the algorithm is able to properly identify altitude change with accuracy of more than 96%.\",\"PeriodicalId\":207985,\"journal\":{\"name\":\"2015 7th International Conference on Information Technology and Electrical Engineering (ICITEE)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 7th International Conference on Information Technology and Electrical Engineering (ICITEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICITEED.2015.7408916\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 7th International Conference on Information Technology and Electrical Engineering (ICITEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICITEED.2015.7408916","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The development of image-based algorithm to identify altitude change of a quadcopter
Quadcopter, a popular Unmanned Aerial Vehicle (UAV), is able to land, take off, hover, and move on 3D trajectory. The ability requires accurate control of the rotors velocity based on input from its sensors. One of the control mechanisms is the altitude control. This paper presents a new algorithm to identify altitude change of a quadcopter based on image processing techniques. The algorithm is designed to be simple and efficient in terms of computation and memory usage. The algorithm identifies altitude change by calculating correlation function of 10 sampled rows of pixels. This paper also presents some experiments conducted to investigate the performance of the algorithm. The results indicated that the algorithm is able to properly identify altitude change with accuracy of more than 96%.