Multi-Region Scene Matching Based Localisation for Autonomous Vision Navigation of UAVs

Abstract

A multi-region scene matching-based localisation system for automated navigation of Unmanned Aerial Vehicles (UAV) is proposed. This system may serve as a backup navigation error correction system to support autonomous navigation in the absence of a global positioning system such as a Global Navigation Satellite System. Conceptually, the system computes the location of the UAV by comparing the sensed images taken by an on board optical camera with a library of pre-recorded geo-referenced images. Several challenging issues in building such a system are addressed, including the colour variability problem and elimination of time-varying details from the pairs of images. The overall algorithm is an iterative process involving four sub-processes: firstly, exact histogram matching is applied to sensed images to overcome the colour variability issues; secondly, regions are automatically extracted from the sensed image where landmarks are detected via their colour histograms; thirdly, these regions are matched against the library, while eliminating inconsistent regions between underlying image pairs in the registration process; and finally the location of the UAV is computed using an optimisation procedure which minimises the localisation error using affine transformations. Experimental results demonstrate the proposed system in terms of accuracy, robustness and computational efficiency.