Andrew Davison, Ian Reid, N. Molton, O. Stasse
We present a real-time algorithm which can recover the 3D trajectory of a monocular camera, moving rapidly through a
previously unknown scene. Our system, which we dub MonoSLAM, is the first successful application of the SLAM methodology from
mobile robotics to the "pure vision" domain of a single uncontrolled camera, achieving real time but drift-free performance inaccessible
to Structure from Motion approaches. The core of the approach is the online creation of a sparse but persistent map of natural
landmarks within a probabilistic framework. Our key novel contributions include an active approach to mapping and measurement, the
use of a general motion model for smooth camera movement, and solutions for monocular feature initialization and feature orientation
estimation. Together, these add up to an extremely efficient and robust algorithm which runs at 30 Hz with standard PC and camera
hardware. This work extends the range of robotic systems in which SLAM can be usefully applied, but also opens up new areas. We
present applications of MonoSLAM to real-time 3D localization and mapping for a high-performance full-size humanoid robot and live
augmented reality with a hand-held camera.
pubs.doc.ic.ac.uk: built & maintained by Ashok Argent-Katwala.