Introduction to navigation and intelligence for UAVs relying on computer vision

Vision-based sensors (VBSs) provide several advantages to unmanned aircraft systems (UASs) primarily due to a large amount of data they are able to capture, and their reduced size, weight, power, and cost compared to other state-of-the-art sensors. A number of vision-based navigation (VBN) methods have emerged recently, which aim to maximise state-estimation performance and reduce reliance on the global navigation satellite system. This chapter identifies and describes some of the most popular visual navigation strategies for the UAS to acquaint the reader with this important field of study. VBN methods presented here include visual servoing, optical flow-based state estimation, visual odometry and terrain referenced visual navigation. Reference system architectures and relevant mathematical models for these methods are presented to facilitate a more in-depth understanding. A review of these methods and their applications to various UAS use-cases is conducted, focussing primarily on seminal work in this domain. The limitations of this sensing modality are also presented, along with a discussion of future trends including multi-spectral imaging and biomimetic systems to inform the reader of key gaps and research avenues in this field.