Yuxuan Jin, Yixiang Ren, Tiantian Song, Zhiling Jiang, Guang-hua Song
{"title":"基于单目视觉的扑翼飞行器地面目标识别与定位系统","authors":"Yuxuan Jin, Yixiang Ren, Tiantian Song, Zhiling Jiang, Guang-hua Song","doi":"10.1145/3603781.3603829","DOIUrl":null,"url":null,"abstract":"Flapping-wing aerial vehicle (FAV) is a novel type of aircraft that mimics the flight mode of birds and insects. Visual perception plays a crucial role in enabling FAVs to acquire ground information and achieve intelligent capabilities. However, most current FAV vision systems rely on ground processing systems for assistance, which limits their operational range due to communication constraints between the aircraft and the ground. Moreover, the use of vision systems for ground target localization on FAVs is still under-researched. In this work, we present a monocular vision-based on-board ground target recognition and localization system for a self-designed FAV, which can run in quasi-real time, and truly endows the FAV with ground autonomous visual perception capabilities. The system utilizes both the images from camera and attitude-position data of the aircraft, and resolves the issue of temporal mismatch between them. To validate feasibility and accuracy of the system, a series of real-world flight experiments are conducted, followed by a discussion of the errors observed.","PeriodicalId":391180,"journal":{"name":"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On-board Monocular Vision-based Ground Target Recognition and Localization System for a Flapping-wing Aerial Vehicle\",\"authors\":\"Yuxuan Jin, Yixiang Ren, Tiantian Song, Zhiling Jiang, Guang-hua Song\",\"doi\":\"10.1145/3603781.3603829\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Flapping-wing aerial vehicle (FAV) is a novel type of aircraft that mimics the flight mode of birds and insects. Visual perception plays a crucial role in enabling FAVs to acquire ground information and achieve intelligent capabilities. However, most current FAV vision systems rely on ground processing systems for assistance, which limits their operational range due to communication constraints between the aircraft and the ground. Moreover, the use of vision systems for ground target localization on FAVs is still under-researched. In this work, we present a monocular vision-based on-board ground target recognition and localization system for a self-designed FAV, which can run in quasi-real time, and truly endows the FAV with ground autonomous visual perception capabilities. The system utilizes both the images from camera and attitude-position data of the aircraft, and resolves the issue of temporal mismatch between them. To validate feasibility and accuracy of the system, a series of real-world flight experiments are conducted, followed by a discussion of the errors observed.\",\"PeriodicalId\":391180,\"journal\":{\"name\":\"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3603781.3603829\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3603781.3603829","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On-board Monocular Vision-based Ground Target Recognition and Localization System for a Flapping-wing Aerial Vehicle
Flapping-wing aerial vehicle (FAV) is a novel type of aircraft that mimics the flight mode of birds and insects. Visual perception plays a crucial role in enabling FAVs to acquire ground information and achieve intelligent capabilities. However, most current FAV vision systems rely on ground processing systems for assistance, which limits their operational range due to communication constraints between the aircraft and the ground. Moreover, the use of vision systems for ground target localization on FAVs is still under-researched. In this work, we present a monocular vision-based on-board ground target recognition and localization system for a self-designed FAV, which can run in quasi-real time, and truly endows the FAV with ground autonomous visual perception capabilities. The system utilizes both the images from camera and attitude-position data of the aircraft, and resolves the issue of temporal mismatch between them. To validate feasibility and accuracy of the system, a series of real-world flight experiments are conducted, followed by a discussion of the errors observed.