Abstract
The monocular visual odometer is widely used in the navigation of robots and vehicles, but it has defects of the unknown scale of the estimated trajectory. In this paper, we presented a position and attitude estimation method, integrating the visual odometer and Global Position System (GPS), where the GPS positioning results were taken as a reference to minimize the trajectory estimation error of visual odometer and derive the attitude of the vehicle. Hardware-in-the-loop simulations were carried out; the experimental results showed that the positioning error of the proposed method was less than 1 m, and the accuracy and robustness of the attitude estimation results were better than those of the state-of-art vision-based attitude estimation methods.
Highlights
The position and attitude are essential measurements in guidance and control of an UnmannedAircraft Vehicle (UAV), and they are usually obtained by Inertial Navigation Sensors (INS) [1,2] and being corrected by the GPS (Global Position System) [3,4,5], magnetic sensors [6], and visual odometers [7,8], etc
For a UnmannedAircraft Vehicle (UAV) equipped with a monocular camera, the attitude estimation can be realized without INS, and the methods of estimating the attitude with pure computer vision are studied by many researchers, while a variety of methods have been proposed, such as horizon detection method [14,15] and vanishing points method [16,17,18]
The premise of the horizon detection method for attitude estimation is that the horizon must appear in the view of the camera
Summary
The position and attitude are essential measurements in guidance and control of an Unmanned. In GVO, the relative position and attitude were estimated by a monocular visual odometer, and the positioning results obtained by GPS were taken as references to eliminate the scale uncertainty of the pose of camera, where the position and attitude of the vehicle could be obtained simultaneously. The application of this method would not be limited by other factors except the general requirements of GPS and visual odometer.
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