The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
6D SLAM—3D mapping outdoor environments
Open accessAbstract
6D SLAM (simultaneous localization and mapping) or 6D concurrent localization and mapping of mobile robots considers six dimensions for the robot pose, namely, the x, y, and z coordinates and the roll, yaw, and pitch angles. Robot motion and localization on natural surfaces, e.g., driving outdoor with a mobile robot, must regard these degrees of freedom. This paper presents a robotic mapping method based on locally consistent 3D laser range scans. Iterative Closest Point scan matching, combined with a heuristic for closed loop detection and a global relaxation method, results in a highly precise mapping system. A new strategy for fast data association, cached k d‐tree search, leads to feasible computing times. With no ground‐truth data available for outdoor environments, point relations in maps are compared to numerical relations in uncalibrated aerial images in order to assess the metric validity of the resulting 3D maps. © 2007 Wiley Periodicals, Inc.
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Cites
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Durrant-Whyte, H., & Bailey, T. (2006) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2006.1638022 · Cited by 4,199
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A solution to the simultaneous localization and map building (SLAM) problem
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An optimal algorithm for approximate nearest neighbor searching fixed dimensions
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Cited by
LOAM: Lidar Odometry and Mapping in Real-time
Zhang, J., & Singh, S. (2014) · Robotics: Science and Systems X · doi:10.15607/rss.2014.x.007 · Cited by 3,303
Image Matching from Handcrafted to Deep Features: A Survey
Ma, J., Jiang, X., Fan, A., Jiang, J., & Yan, J. (2021) · International Journal of Computer Vision · doi:10.1007/s11263-020-01359-2 · Cited by 990
Visual simultaneous localization and mapping: a survey
Fuentes-Pacheco, J., Ruiz-Ascencio, J., & Rendón-Mancha, J. M. (2015) · Artificial Intelligence Review · doi:10.1007/s10462-012-9365-8 · Cited by 883
Low-drift and real-time lidar odometry and mapping
Zhang, J., & Singh, S. (2017) · Autonomous Robots · doi:10.1007/s10514-016-9548-2 · Cited by 820
A Review of Visual-LiDAR Fusion based Simultaneous Localization and Mapping
Debeunne, C., & Vivet, D. (2020) · Sensors · doi:10.3390/s20072068 · Cited by 386
Metadata
- Authors
- Nüchter, A., Lingemann, K., Hertzberg, J., & Surmann, H.
- Venue
- Journal of Field Robotics
- Publisher
- Wiley
- Published
- 2007-08
- Volume
- 24
- Issue
- 8-9
- Pages
- 699-722
- ISSN
- 1556-4959 (ISSN-L)
- 1556-4967
- OpenAlex
- W2071158641
- Cited by
- 450
- References
- 43
- FWCI
- 48.73
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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