{"title":"Observer-control scheme for autonomous navigation: Flight tests validation in a quadrotor vehicle","authors":"L. E. Munoz, P. Castillo, P. Garcia","doi":"10.1109/ICUAS.2013.6564762","DOIUrl":null,"url":null,"abstract":"We present in this paper an improvement of a nonlinear control algorithm based on the Lyapunov analysis and the saturation functions, to realize autonomous navigation of a quadrotor vehicle. The algorithm is analyzed and the convergence of the states is ameliorated, in addition, the stability analysis in closed-loop system is proved with these new conditions. In order to locate the aerial vehicle a new position estimation algorithm is developed using the dead-reckoning technique with the Extended Kalman Filter (EKF). This algorithm is based in the data fusion of the classical sensors; an Inertial Measurement Unit (IMU), an ultrasonic sensor and a vision system. The algorithms are validated onboard in flight tests to realize autonomous navigation of the quadrotor vehicle. The most important results are depicted in some graphs.","PeriodicalId":322089,"journal":{"name":"2013 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Unmanned Aircraft Systems (ICUAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICUAS.2013.6564762","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
We present in this paper an improvement of a nonlinear control algorithm based on the Lyapunov analysis and the saturation functions, to realize autonomous navigation of a quadrotor vehicle. The algorithm is analyzed and the convergence of the states is ameliorated, in addition, the stability analysis in closed-loop system is proved with these new conditions. In order to locate the aerial vehicle a new position estimation algorithm is developed using the dead-reckoning technique with the Extended Kalman Filter (EKF). This algorithm is based in the data fusion of the classical sensors; an Inertial Measurement Unit (IMU), an ultrasonic sensor and a vision system. The algorithms are validated onboard in flight tests to realize autonomous navigation of the quadrotor vehicle. The most important results are depicted in some graphs.