Obstacle detection using stereo vision for unmanned ground vehicles
Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
In recent years, the market for automatized surveillance and use of unmanned ground vehicles (UGVs) has increased considerably. In order for unmanned vehicles to operate autonomously, high level algorithms of artificial intelligence need to be developed and accompanied by some way to make the robots perceive and interpret the environment. The purpose of this work is to investigate methods for real-time obstacle detection using stereo vision and implement these on an existing UGV platform. To reach real-time processing speeds, the algorithms presented in this work are designed for parallel processing architectures and implemented using programmable graphics hardware. The reader will be introduced to the basics of stereo vision and given an overview of the most common real-time stereo algorithms in literature along with possible applications. A novel wide-baseline real-time depth estimation algorithm is presented. The depth estimation is used together with a simple obstacle detection algorithm, producing an occupancy map of the environment allowing for evasion of obstacles and path planning. In addition, a complete system design for autonomous navigation in multi-UGV systems is proposed.
Place, publisher, year, edition, pages
2009. , 45 p.
Depth estimation, Stereo vision, Obstacle detection, UGV
Computer Vision and Robotics (Autonomous Systems)
IdentifiersURN: urn:nbn:se:liu:diva-18255ISRN: LiU-ITN-TEK-A--09/025--SEOAI: oai:DiVA.org:liu-18255DiVA: diva2:217591
Dell'Acqua, Pierangelo, universitetslektor