DocumentCode :
3606188
Title :
COP-SLAM: Closed-Form Online Pose-Chain Optimization for Visual SLAM
Author :
Dubbelman, Gijs ; Browning, Brett
Author_Institution :
Dept. of Electr. Eng., Eindhoven Univ. of Technol., Eindhoven, Netherlands
Volume :
31
Issue :
5
fYear :
2015
Firstpage :
1194
Lastpage :
1213
Abstract :
In this paper, we analyze and extend the recently proposed closed-form online pose-chain simultaneous localization and mapping (SLAM) algorithm. Pose-chains are a specific type of extremely sparse pose-graphs and a product of contemporary SLAM front-ends, which perform accurate visual odometry and reliable appearance-based loop detection. They are relevant for challenging robotic applications in large-scale 3-D environments for which frequent loop detection is not desired or not possible. Closed-form online pose-chain SLAM efficiently and accurately optimizes pose-chains by exploiting their Lie group structure. The convergence and optimality properties of this solution are discussed in detail and are compared against state-of-the-art iterative methods. We also provide a novel solution space, that of similarity transforms, which has not been considered earlier for the proposed algorithm. This allows for closed-form optimization of pose-chains that exhibit scale drift, which is important to monocular SLAM systems. On the basis of extensive experiments, specifically targeting 3-D pose-chains and using a total of 60 km of challenging binocular and monocular data, it is shown that the accuracy obtained by closed-form online pose-chain SLAM is comparable with that of state-of-the-art iterative methods, while the time it needs to compute its solution is orders of magnitudes lower. This novel SLAM technique thereby is relevant to a broad range of robotic applications and computational platforms.
Keywords :
Lie groups; SLAM (robots); optimisation; COP-SLAM; Lie group structure; Visual SLAM; closed-form online pose-chain optimization; closed-form online pose-chain simultaneous localization and mapping algorithm; closed-form optimization; monocular SLAM systems; similarity transforms; Accuracy; Image edge detection; Optimization; Simultaneous localization and mapping; Trajectory; Visualization; Computer vision; pose-graph optimization; simultaneous localization and mapping (SLAM);
fLanguage :
English
Journal_Title :
Robotics, IEEE Transactions on
Publisher :
ieee
ISSN :
1552-3098
Type :
jour
DOI :
10.1109/TRO.2015.2473455
Filename :
7272096
Link To Document :
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