Monocular Trail Detection and Tracking Aided by Visual SLAM for Small Unmanned Aerial Vehicles
This work addresses trail navigation challenges for small UAVs in search and rescue missions, but it is incremental as it builds on an existing technique.
The paper tackles the problem of trail detection and tracking for small UAVs in forest environments by extending a previous monocular method with Visual SLAM data to improve robustness, achieving a success rate of 97.8% in experiments.
This paper presents a monocular vision system susceptible of being installed in unmanned small and medium-sized aerial vehicles built to perform missions in forest environments (e.g., search and rescue). The proposed system extends a previous monocular-based technique for trail detection and tracking so as to take into account volumetric data acquired from a Visual SLAM algorithm and, as a result, to increase its sturdiness upon challenging trails. The experimental results, obtained via a set of 12 videos recorded with a camera installed in a tele-operated, unmanned small-sized aerial vehicle, show the ability of the proposed system to overcome some of the difficulties of the original detector, attaining a success rate of $97.8\,\%$.