Robust positioning of drones for land use monitoring in strong terrain relief using vision-based navigation

TL;DR

This paper presents a vision-based navigation system for drones that improves land use monitoring in urban canyons and rugged terrains where GPS signals are unreliable, demonstrating accuracy within 20 meters.

Contribution

The study introduces a novel vision-based navigation approach that leverages terrain relief maps to enhance drone positioning in challenging environments, surpassing traditional GPS methods.

Findings

Maximum position error is 20 meters in ideal conditions.

Maximum Euler angle error is 0.83 degrees.

In camera movement scenarios, position error increases to 30 meters.

Abstract

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.