GNSS非依存のUAV地理的自己位置推定：機上カメラ画像と正射写真の視覚マッチング
GNSS-denied geolocalization of UAVs by visual matching of onboard camera images with orthophotos
下向きカメラを不要にし、任意方向のカメラ画像を正射変換して正射地図と照合するモンテカルロ位置推定法を提案し、GNSSなしでUAVの大域的な自己位置推定を実現した。
著者: Jouko Kinnari, Francesco Verdoja, Ville Kyrki
分類: cs.RO
原文アブストラクト
Localization of low-cost Unmanned Aerial Vehicles (UAVs) often relies on Global Navigation Satellite Systems (GNSS). GNSS are susceptible to both natural disruptions to radio signal and intentional jamming and spoofing by an adversary. A typical way to provide georeferenced localization without GNSS for small UAVs is to have a downward-facing camera and match camera images to a map. The downward-facing camera adds cost, size, and weight to the UAV platform and the orientation limits its usability for other purposes. In this work, we propose a Monte-Carlo localization method for georeferenced localization of an UAV requiring no infrastructure using only inertial measurements, a camera facing an arbitrary direction, and an orthoimage map. We perform orthorectification of the UAV image, relying on a local planarity assumption of the environment, relaxing the requirement of downward-pointing camera. We propose a measure of goodness for the matching score of an orthorectified UAV image and a map. We demonstrate that the system is able to localize globally an UAV with modest requirements for initialization and map resolution.
