Robust positioning of drones for land use monitoring in strong terrain relief using vision-based navigation
This addresses positioning issues for drone operators in complex terrains, but it is incremental as it adapts existing vision-based methods to a specific application.
The paper tackled robust drone positioning for land use monitoring in challenging terrain like urban canyons and strong relief, where GPS fails, by using vision-based navigation with a terrain map; results showed maximum position errors of 20-30 meters and angle errors of 0.83-2.2 degrees.
For land use monitoring, the main problems are robust positioning in urban canyons and strong terrain reliefs with the use of GPS system only. Indeed, satellite signal reflection and shielding in urban canyons and strong terrain relief results in problems with correct positioning. Using GNSS-RTK does not solve the problem completely because in some complex situations the whole satellite's system works incorrectly. We transform the weakness (urban canyons and strong terrain relief) to an advantage. It is a vision-based navigation using a map of the terrain relief. We investigate and demonstrate the effectiveness of this technology in Chinese region Xiaoshan. The accuracy of the vision-based navigation system corresponds to the expected for these conditions. . It was concluded that the maximum position error based on vision-based navigation is 20 m and the maximum angle Euler error based on vision-based navigation is 0.83 degree. In case of camera movement, the maximum position error based on vision-based navigation is 30m and the maximum Euler angle error based on vision-based navigation is 2.2 degrees.