Large scale vision-based navigation without an accurate global reconstruction

Autonomous cars will likely play an important role in the future. A vision system designed to support outdoor navigation for such vehicles has to deal with large dynamic environments, changing imaging conditions, and temporary occlusions by other moving objects. This paper presents a novel appearance-based navigation framework relying on a single perspective vision sensor, which is aimed towards resolving of the above issues. The solution is based on a hierarchical environment representation created during a teaching stage, when the robot is controlled by a human operator. At the top level, the representation contains a graph of key-images with extracted 2D features enabling a robust navigation by visual servoing. The information stored at the bottom level enables to efficiently predict the locations of the features which are currently not visible, and eventually (re-)start their tracking. The outstanding property of the proposed framework is that it enables robust and scalable naviga...

• Type: Conference
• Year: 2007
• Where: CVPR
• Authors: Albert Diosi, Anthony Remazeilles, François Chaumette, Sinisa Segvic
• Keywords: Appearance-based Navigation Framework, Computer Vision, CVPR 2007, Outdoor Navigation, Robust Navigation, Scalable Navigation, Successful Real-time Navigation