Geo-referencing for UAV Navigation using Environmental Classification, Report no. LiTH-ISY-R-2957
نویسندگان
چکیده
A UAV navigation system relying on GPS is vulnerable to signal failure, making a drift free backup system necessary. We introduce a vision based geo-referencing system that uses pre-existing maps to reduce the long term drift. The system classi es an image according to its environmental content and thereafter matches it to an environmentally classi ed map over the operational area. This map matching provides a measurement of the absolute location of the UAV that can easily be incorporated into a sensor fusion framework. Experiments show that the geo-referencing system reduces the long term drift in UAV navigation, enhancing the ability of the UAV to navigate accurately over large areas without the use of GPS.
منابع مشابه
The ARCUS Planning Framework for UAV Surveillance with EO/IR Sensors, Report no. LiTH-ISY-R-2885
This report gives an overview of the planner framework developed in the Arcus project. The framework consists of a number of planning modules and planning modes that are introduced.
متن کاملA Planning Algorithm of a Gimballed EO/IR Sensor for Multi Target Tracking, Report no. LiTH-ISY-R-2887
This report proposes an algorithm for planning the aiming direction of a vision sensor with limited field-of-view for tracking of multiple targets. The sensor is mounted in an actuated gimbal on an unmanned aerial vehicle (UAV). Dynamic constraints of the gimbal are included implicitly and a genetic algorithm is used to solve the optimization problem.
متن کاملSimultaneous navigation and SAR Auto-focusing, Report no. LiTH-ISY-R-2959
Synthetic Aperture Radar (SAR) equipment is an all-weather radar imaging system that can create high resolution images by means of utilising the movement of the flying platform. Accurate knowledge of the flown trajectory is essential in order to get focused images. Recently SAR systems are becoming more used on smaller and cheaper flying platforms like Unmanned Aerial Vehicles (UAV). Since UAVs...
متن کاملUtilizing Model Structure for Efficient Simultaneous Localization and Mapping for a UAV Application, Report no. LiTH-ISY-R-2836
This contribution aims at unifying two recent trends in applied particle ltering (pf). The rst trend is the major impact in simultaneous localization and mapping (slam) applications, utilizing the Fastslam algorithm. The second one is the implications of the marginalized particle lter (mpf) or the Rao-Blackwellized particle lter (rbpf) in positioning and tracking applications. Using the standar...
متن کاملSolving the SLAM Problem for Unmanned Aerial Vehicles Using Smoothed Estimates, Report no. LiTH-ISY-R-2971
In this paper we present a solution to the simultaneous localization and mapping (SLAM) problem for unmanned aerial vehicles (UAV) using a camera and inertial sensors. A good SLAM solution is an important enabler for autonomous robots. Our approach is based on an optimization based formulation of the problem, which results in a smoother, rather than a filter. The proposed algorithm is evaluated...
متن کامل