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Mapping Large Loops with a Single Hand-Held Camera

L. Clemente, Andrew Davison, Ian Reid, J. Neira, J. Tardos

Conference or Workshop Paper
Robotics: Science and Systems
June, 2007
Abstract

This paper presents a method for Simultaneous

Localization and Mapping (SLAM) relying on a monocular

camera as the only sensor which is able to build outdoor, closed-

loop maps much larger than previously achieved with such

input. Our system, based on the Hierarchical Map approach [1],

builds independent local maps in real-time using the EKF-SLAM

technique and the inverse depth representation proposed in [2].

The main novelty in the local mapping process is the use of a

data association technique that greatly improves its robustness in

dynamic and complex environments. A new visual map matching

algorithm stitches these maps together and is able to detect

large loops automatically, taking into account the inobservability

of scale intrinsic to pure monocular SLAM. The loop closing

constraint is applied at the upper level of the Hierarchical Map

in near real-time.

We present experimental results demonstrating monocular

SLAM as a human carries a camera over long walked trajectories

in outdoor areas with people and other clutter, even in the more

difficult case of forward-looking camera, and show the closing of

loops of several hundred meters.

BibTEX file for the publication
 

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