{"title":"Robust localization system for an autonomous mower","authors":"Huiwen Guo, Xinyu Wu, Ruiqing Fu, Wei Feng","doi":"10.1109/ROBIO.2015.7419728","DOIUrl":null,"url":null,"abstract":"This paper presents a robust vision-based localization system for an autonomous mower, which is significant for both the meadow map building and the successful area covering. Instead of setting the monocular camera toward the scene, which suffers from the disturbance of moving objects, less mark points or variation of illumination, we equip the camera toward the ground with constant illumination compensation. To achieve the localization of the mower, point features are extracted and matched between pairs of frames. Motion is incremental obtained by calculate the rotation and translation transformation of matched feature point pairs. As the angle accumulated error has greater contribution to the location error, angular acceleration sensor is adopted to compensate the angle error especially in the steep turning case. Experiments on meadow with our mowers demonstrate the robustness of our localization system.","PeriodicalId":325536,"journal":{"name":"2015 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Robotics and Biomimetics (ROBIO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROBIO.2015.7419728","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper presents a robust vision-based localization system for an autonomous mower, which is significant for both the meadow map building and the successful area covering. Instead of setting the monocular camera toward the scene, which suffers from the disturbance of moving objects, less mark points or variation of illumination, we equip the camera toward the ground with constant illumination compensation. To achieve the localization of the mower, point features are extracted and matched between pairs of frames. Motion is incremental obtained by calculate the rotation and translation transformation of matched feature point pairs. As the angle accumulated error has greater contribution to the location error, angular acceleration sensor is adopted to compensate the angle error especially in the steep turning case. Experiments on meadow with our mowers demonstrate the robustness of our localization system.