The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Localization Methods for a Mobile Robot in Urban Environments
Open accessAbstract
This paper addresses the problems of building a functional mobile robot for urban site navigation and modeling with focus on keeping track of the robot location. We have developed a localization system that employs two methods. The first method uses odometry, a compass and tilt sensor, and a global positioning sensor. An extended Kalman filter integrates the sensor data and keeps track of the uncertainty associated with it. The second method is based on camera pose estimation. It is used when the uncertainty from the first method becomes very large. The pose estimation is done by matching linear features in the image with a simple and compact environmental model. We have demonstrated the functionality of the robot and the localization methods with real-world experiments.
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Fischler, M. A., & Bolles, R. C. (1981) · Communications of the ACM · doi:10.1145/358669.358692 · Cited by 25,893
A solution to the simultaneous localization and map building (SLAM) problem
Dissanayake, M. W. M. G., Newman, P., Clark, S., Durrant-Whyte, H. F., & Csorba, M. (2001) · IEEE Transactions on Robotics and Automation · doi:10.1109/70.938381 · Cited by 2,661
Cited by
6D SLAM—3D mapping outdoor environments
Nüchter, A., Lingemann, K., Hertzberg, J., & Surmann, H. (2007) · Journal of Field Robotics · doi:10.1002/rob.20209 · Cited by 450
A Theoretical Foundation of Network Localization and Navigation
Win, M. Z., Shen, Y., & Dai, W. (2018) · Proceedings of the IEEE · doi:10.1109/jproc.2018.2844553 · Cited by 353
Adaptive fault-tolerant formation tracking control of networked mobile robots with input delays
Ai, X., Chen, Y.-Y., & Yu, H. (2024) · Journal of the Franklin Institute · doi:10.1016/j.jfranklin.2023.11.020 · Cited by 12
Metadata
- Authors
- Georgiev, A., & Allen, P. K.
- Venue
- IEEE Transactions on Robotics
- Published
- 2004-10
- Volume
- 20
- Issue
- 5
- Pages
- 851-864
- ISSN
- 1552-3098 (ISSN-L)
- OpenAlex
- W2124768549
- Cited by
- 168
- References
- 2
- FWCI
- 38.86
- 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).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
