Air-ground Matching: Appearance-based GPS-denied Urban Localization of Micro Aerial Vehicles
نویسندگان
چکیده
In this paper, we address the problem of globally localizing and tracking the pose of a camera-equipped micro aerial vehicle (MAV) flying in urban streets at low altitudes without GPS. An image-based global positioning system is introduced to localize the MAV with respect to the surrounding buildings. We propose a novel airground image-matching algorithm to search the airborne image of the MAV within a ground-level, geotagged image database. Based on the detected matching image features, we infer the global position of the MAV by back-projecting the corresponding image points onto a cadastral three-dimensional city model. Furthermore, we describe an algorithm to track the position of the flying vehicle over several frames and to correct the accumulated drift of the visual odometry whenever a good match is detected between the airborne and the ground-level images. The proposed approach is tested on a 2 km trajectory with a small quadrocopter flying in the streets of Zurich. Our vision-based global localization can robustly handle extreme changes in viewpoint, illumination, perceptual aliasing, and over-season variations, thus outperforming conventional visual placerecognition approaches. The dataset is made publicly available to the research community. To the best of our knowledge, this is the first work that studies and demonstrates global localization and position tracking of a drone in urban streets with a single onboard camera. C © 2015 Wiley Periodicals, Inc.
منابع مشابه
The Zurich Urban Micro Aerial Vehicle
This paper presents a dataset recorded on-board a camera-equipped Micro Aerial Vehicle (MAV) flying within the urban streets of Zurich, Switzerland, at low altitudes (i.e., 5-15 meters above the ground). The 2 km dataset consists of time synchronized aerial high-resolution images, GPS and IMU sensor data, ground-level street view images, and ground truth data. The dataset is ideal to evaluate a...
متن کاملSemantics for UGV Registration in GPS-denied Environments
Localization in a global map is critical to success in many autonomous robot missions. This is particularly challenging for multi-robot operations in unknown and adverse environments. Here, we are concerned with providing a small unmanned ground vehicle (UGV) the ability to localize itself within a 2.5D aerial map generated from imagery captured by a low-flying unmanned aerial vehicle (UAV). We...
متن کاملAppearance-Based Visual-Teach-And-Repeat Navigation Technique for Micro Aerial Vehicle
The objective of this paper is to develop a vision-based navigation technique for micro aerial vehicles, quadrotor type, to operate in GPS-denied environment. The navigation method has been developed while using appearance-based Visual-Teach-andRepeat (VT&R) technique. In a teaching phase, a quadrotor is manually navigated along a desired route to collect a set of reference images. In a repeati...
متن کاملNavigation and Control for Micro Aerial Vehicles in GPS-Denied Environments
Micro-air vehicles have been increasingly employed in diverse research projects in both military and civilian applications. That is because their high maneuverability and accurate mobility. Many of them have been successfully used in outdoor areas, while some have been operated indoors. However, very few have dedicated especial attention to the case of high pitch and roll movements while doing ...
متن کاملVision-guided Control Algorithms for Micro Aerial Vehicles
This study presents an image analysis method used in the vision guided control system for Micro Air Vehicles (MAVs). The paper describes a hypothetical model of a MAV located in the GPS-denied unknown environment, somewhere indoors. The model keeps moving autonomously following ‘the track’ marked with corners and other feature points recorded with a monocular camera pointed at the far end of a ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- J. Field Robotics
دوره 32 شماره
صفحات -
تاریخ انتشار 2015