| Authors |
Hoppe Christof, Pirker Katrin, Rüther Matthias, Bischof Horst |
| Appeared in |
AAPR/OAGM: Machine Vision Research for High Quality Processes and Products, JOANNEUM RESEARCH |
| Date |
2011 |
| Abstract |
Keyframe-based visual SLAM systems perform reliably and fast in medium-sized environments. Currently,
their main weaknesses are robustness and scalability in large scenarios. In this work, we
propose a hybrid, keyframe based visual SLAM system, which overcomes these problems. We combine
visual features of different strength, add appearance-based loop detection and present a novel
method to incorporate non-visual sensor information into standard bundle adjustment frameworks to
tackle the problem of weakly textured scenes. On a standardized test dataset, we outperform EKFbased
solutions in terms of localization accuracy by at least a factor of two. On a self-recorded
dataset, we achieve a performance comparable to a laser scanner approach. |
| Link |
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