2D pose nodes sampling heuristic for fast loop closing빠른 루프 클로징을 위한 2D포즈 노드 샘플링 휴리스틱

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The graph-based SLAM (Simultaneous Localization and Mapping) approach has been gaining much attention in SLAM research recently thanks to its ability to provide better maps and full trajectory estimations when compared to the filtering-based SLAM approach. Even though graph-based SLAM requires batch processing causing it to be computationally heavy, recent advancements in optimization and computing power enable it to run fast enough to be used in real-time. However, data association problems still require large amount of computation when building a pose graph. For example, to find loop closures it is necessary to consider the whole history of the robot trajectory and sensor data within the confident range. As a pose graph grows, the number of candidates to be searched also grows. It makes searching the loop closures a bottleneck when solving the SLAM problem. Our approach to alleviate this bottleneck is to sample a limited number of pose nodes in which loop closures are searched. We propose a heuristic for sampling pose nodes that are most advantageous to closing loops by providing a way of ranking pose nodes in order of usefulness for closing loops.
Publisher
Institute of Control, Robotics and Systems
Issue Date
2016
Language
Korean
Article Type
Article
Citation

Journal of Institute of Control, Robotics and Systems, v.22, no.12, pp.1021 - 1026

ISSN
1976-5622
DOI
10.5302/J.ICROS.2016.16.0135
URI
http://hdl.handle.net/10203/264226
Appears in Collection
CE-Journal Papers(저널논문)
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