Review of UAV optical navigation methods and algorithms

Abstract

The article is devoted to a review of navigation methods for unmanned aerial vehicles (UAVs) via the optical channel. The relevance of the topic is due to the fact that optical navigation ensures UAV autonomy in the absence of a GNSS signal, which is a typical problem in modern conditions. The paper examines and compares the main methods and approaches used to implement optical navigation. Modern visual navigation systems are based on a combination of computer vision, deep learning, and multi-sensor integration. The core of such systems consists of visual odometry (VO) and visual simultaneous localization and mapping (Visual SLAM) methods.

Comparative experiments of VO methods on the standard KITTI dataset confirmed the effectiveness of modern optimization and dynamic models. Research into Visual SLAM algorithms in dynamic scenes showed a significant advantage for methods implementing loop closure mechanisms and filtering of moving objects. At the same time, it should be emphasized that the provided numerical evaluations were mostly obtained in local test ranges and small environments with good visual landmarks (urban scenes, laboratory, or corridor routes). The conducted review demonstrates existing and promising solutions and outlines directions for the further development of this technology.