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Visual SLAM for Autonomous Navigation of MAVs Visual SLAM for Autonomous Navigation of MAVs
| Content Provider | CiteSeerX |
|---|---|
| Researcher | Yang, Shaowu |
| Abstract | This thesis focuses on developing onboard visual simultaneous localization and map-ping (SLAM) systems to enable autonomous navigation of micro aerial vehicles (MAVs), which is still a challenging topic considering the limited payload and computational ca-pability that an MAV normally has. In MAV applications, the visual SLAM systems are required to be very efficient, especially when other visual tasks have to be done in par-allel. Furthermore, robustness in pose tracking is highly desired in order to enable safe autonomous navigation of an MAV in three-dimensional (3D) space. These challenges motivate the work in this thesis in the following aspects. Firstly, the problem of visual pose estimation for MAVs using an artificial landmark is addressed. An artificial neural network (ANN) is used to robustly recognize this visual marker in cluttered environments. Then a computational projective-geometry method is implemented for relative pose computation based on the retrieved geometry informa-tion of the visual marker. The presented vision system can be used not only for pose control of MAVs, but also for providing accurate pose estimates to a monocular visual |
| File Format | |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Thesis |
