{"title":"由骚动运动产生的线速度","authors":"Wenbo Dong, Volkan Isler","doi":"10.1109/IROS.2017.8206187","DOIUrl":null,"url":null,"abstract":"Most Unmanned Aerial Vehicle (UAV) controllers require linear velocities as input. An effective method to obtain linear velocity is to place a downward facing camera and to estimate the velocity from the optical flow. However, this technique fails in outdoor environments when the ground is covered with grass or other objects which move due to winds such as those caused by the propellers. We present a novel method to estimate the linear velocities from stereo images even in the presence of disorderly motion of image features. We validate the approach using imagery obtained from a UAV flying through orchard rows.","PeriodicalId":6658,"journal":{"name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"11 1","pages":"3467-3472"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Linear velocity from commotion motion\",\"authors\":\"Wenbo Dong, Volkan Isler\",\"doi\":\"10.1109/IROS.2017.8206187\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Most Unmanned Aerial Vehicle (UAV) controllers require linear velocities as input. An effective method to obtain linear velocity is to place a downward facing camera and to estimate the velocity from the optical flow. However, this technique fails in outdoor environments when the ground is covered with grass or other objects which move due to winds such as those caused by the propellers. We present a novel method to estimate the linear velocities from stereo images even in the presence of disorderly motion of image features. We validate the approach using imagery obtained from a UAV flying through orchard rows.\",\"PeriodicalId\":6658,\"journal\":{\"name\":\"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)\",\"volume\":\"11 1\",\"pages\":\"3467-3472\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IROS.2017.8206187\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IROS.2017.8206187","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Most Unmanned Aerial Vehicle (UAV) controllers require linear velocities as input. An effective method to obtain linear velocity is to place a downward facing camera and to estimate the velocity from the optical flow. However, this technique fails in outdoor environments when the ground is covered with grass or other objects which move due to winds such as those caused by the propellers. We present a novel method to estimate the linear velocities from stereo images even in the presence of disorderly motion of image features. We validate the approach using imagery obtained from a UAV flying through orchard rows.