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Uncertainty Estimation For Stereo Visual Odometry, Derek W. Ross
Uncertainty Estimation For Stereo Visual Odometry, Derek W. Ross
Graduate Theses, Dissertations, and Problem Reports
Over the past few decades, unmanned aerial vehicles (UAVs) have been increasingly popular for use in locations that are lacking, or have unreliable global navigation satellite system (GNSS) availability. One of the more popular localization techniques for quadrotors is the use of visual odometry (VO) through monocular, RGB-D, or stereo cameras. With primary applications in the context of Simultaneous Localization And Mapping (SLAM) and indoor navigation, VO is largely used in combination with other sensors through Bayesian filters, namely Extended Kalman Filter (EKF) or Particle Filter. This work investigates the accuracy of two standard covariance estimation techniques for a feature-based …
Design And Evaluation Of Novel Attitude Estimation System Using Mems Sensors For Indoor Uas, Joshua Bruce Milam
Design And Evaluation Of Novel Attitude Estimation System Using Mems Sensors For Indoor Uas, Joshua Bruce Milam
Graduate Theses, Dissertations, and Problem Reports
Most small unmanned aerial systems in use today, employ extended Kalman filter sensor fusion algorithms in order to provide accurate estimations of attitude or orientation. These complex algorithms use measurements from GPS receivers and magnetometer sensors that can be rendered useless in GPS denied environments or areas of significant magnetic interference, such as inside buildings or other structures. The complexity of these algorithms makes them inaccessible for some researchers and hobbyists who wish to code their own attitude estimation algorithms. This complexity is also computationally expensive and requires processors that are powerful enough to operate the algorithms along with any …