Vision-Based Localization and Guidance for Unmanned Aerial Vehicles

• Main Author: Conte, Gianpaolo
• Format: Doctoral Thesis
• Language: English
• Published: Linköpings universitet, Institutionen för datavetenskap 2009
• Subjects: Unmanned Aerial Vehicles; Guidance; Kalman filter; Vision-based Navigation; Geo-referenced Imagery; Autonomous Landing; Target Geo-location; Computer science; Datavetenskap
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-17767; http://nbn-resolving.de/urn:isbn:978-91-7393-603-3

The thesis has been developed as part of the requirements for a PhD degree at the Artificial Intelligence and Integrated Computer System division (AIICS) in the Department of Computer and Information Sciences at Linköping University.The work focuses on issues related to Unmanned Aerial Vehicle (UAV) navigation, in particular in the areas of guidance and vision-based autonomous flight in situations of short and long term GPS outage.The thesis is divided into two parts. The first part presents a helicopter simulator and a path following control mode developed and implemented on an experimental helicopter platform. The second part presents an approach to the problem of vision-based state estimation for autonomous aerial platforms which makes use of geo-referenced images for localization purposes. The problem of vision-based landing is also addressed with emphasis on fusion between inertial sensors and video camera using an artificial landing pad as reference pattern. In the last chapter, a solution to a vision-based ground object geo-location problem using a fixed-wing micro aerial vehicle platform is presented.The helicopter guidance and vision-based navigation methods developed in the thesis have been implemented and tested in real flight-tests using a Yamaha Rmax helicopter. Extensive experimental flight-test results are presented. === WITAS