Technical Paper
Estimating Unmanned Aerial System Pose Using Cast Shadows and Computer Vision Techniques
2024-03-05
2024-01-1931
Although there have been significant advancements in vision-based localization techniques over recent years, there are still problems that need to be addressed. One of these problems is localization in dynamically illuminated environments, like one might find when a small unmanned aerial system (sUAS) equipped with a lighting payload attempts to autonomously navigate inside a dark, damaged structure. When visual odometry (VO) methods are implemented in a dynamically illuminated environment, the accuracy of the state estimation degrades because the shadows are improperly identified as features and these shadow-features move in a different manner than static objects in the environment. As a result, sUAS pose estimates often accumulate errors without bound. This work will examine the merits and demerits inherent in conventional or prevailing sUAS self-localization techniques in dark environments.