{"title":"三维视觉伺服路径规划:轮式移动机器人","authors":"Hassen Mekki, Manel Letaief","doi":"10.1109/ICBR.2013.6729262","DOIUrl":null,"url":null,"abstract":"In this paper, we are interested in 3D visual servoïng path planning and path tracking. In fact, in the 3D visual servoïng task, there is no control in the image space and the object may get out of the camera field of view during servoing. To solve this problem, we have used a new approach based on a flatness concept. The 3D visual servoïng suffer from another major problem, is to determine the relative pose of the camera and the object. Generally, the pose estimation is made by correspondences between points of one image and points of the space that is the 2D-3D correspondence. In our work we have used a 3D visual sensor called Kinect. To show the efficiency of the proposed algorithm, we have implemented it on a wheeled Koala robot.","PeriodicalId":269516,"journal":{"name":"2013 International Conference on Individual and Collective Behaviors in Robotics (ICBR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Path planning for 3D visual servoing: For a wheeled mobile robot\",\"authors\":\"Hassen Mekki, Manel Letaief\",\"doi\":\"10.1109/ICBR.2013.6729262\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we are interested in 3D visual servoïng path planning and path tracking. In fact, in the 3D visual servoïng task, there is no control in the image space and the object may get out of the camera field of view during servoing. To solve this problem, we have used a new approach based on a flatness concept. The 3D visual servoïng suffer from another major problem, is to determine the relative pose of the camera and the object. Generally, the pose estimation is made by correspondences between points of one image and points of the space that is the 2D-3D correspondence. In our work we have used a 3D visual sensor called Kinect. To show the efficiency of the proposed algorithm, we have implemented it on a wheeled Koala robot.\",\"PeriodicalId\":269516,\"journal\":{\"name\":\"2013 International Conference on Individual and Collective Behaviors in Robotics (ICBR)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Individual and Collective Behaviors in Robotics (ICBR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICBR.2013.6729262\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Individual and Collective Behaviors in Robotics (ICBR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBR.2013.6729262","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Path planning for 3D visual servoing: For a wheeled mobile robot
In this paper, we are interested in 3D visual servoïng path planning and path tracking. In fact, in the 3D visual servoïng task, there is no control in the image space and the object may get out of the camera field of view during servoing. To solve this problem, we have used a new approach based on a flatness concept. The 3D visual servoïng suffer from another major problem, is to determine the relative pose of the camera and the object. Generally, the pose estimation is made by correspondences between points of one image and points of the space that is the 2D-3D correspondence. In our work we have used a 3D visual sensor called Kinect. To show the efficiency of the proposed algorithm, we have implemented it on a wheeled Koala robot.