Mobile robot localization by tracking geometric beacons
Abstract
The application of the extended Kaman filter to the problem of mobile robot navigation in a known environment is presented. An algorithm for, model-based localization that relies on the concept of a geometric beacon, a naturally occurring environment feature that can be reliably observed in successive sensor measurements and can be accurately described in terms of a concise geometric parameterization, is developed. The algorithm is based on an extended Kalman filter that utilizes matches between observed geometric beacons and an a priori map of beacon locations. Two implementations of this navigation algorithm, both of which use sonar, are described. The first implementation uses a simple vehicle with point kinematics equipped with a single rotating sonar. The second implementation uses a 'Robuter' mobile robot and six static sonar transducers to provide localization information while the vehicle moves at typical speeds of 30 cm/s.>
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The EKF method laid the foundation for the first SLAM algorithm known as EKF-SLAM.
“This gave birth to the implementation of the Extended Kalman Filter (EKF) method, which laid the foundation for the first SLAM algorithm known as the EKF-SLAM [193].”
From Applications and Challenges of Artificial Intelligence in Space Missions (2024) · cites this paper as [193]
FastSLAM uses a hybrid technique integrating Particle Filter and EKF, making it popular for higher data accuracy.
“FastSLAM uses a hybrid technique that integrates Particle Filter and EKF approach, making it popular for its higher data accuracy [193, 195].”
From Applications and Challenges of Artificial Intelligence in Space Missions (2024) · cites this paper as [193]
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“This was followed in 1991 by Leonard et al . in [192] developing a SLAM technique based on [191], which used a probabilistic approach in solving the SLAM problem.”
Method
- Authors
- Leonard, J. J., & Durrant-Whyte, H. F.
- Affiliations
- University of Oxford (GB)
- ORCID
- Leonard, J.J.
- Venue
- IEEE Transactions on Robotics and Automation
- Published
- 1991-06
- Volume
- 7
- Issue
- 3
- Pages
- 376-382
- ISSN
- 1042-296X (ISSN-L)
- OpenAlex
- W2109749443
- Cited by
- 1,245
- References
- 0
- Citations by year
- 2026: 11 · 2025: 13 · 2024: 22 · 2023: 30 · 2022: 18 · 2021: 30 · 2020: 41 · 2019: 38 · 2018: 42 · 2017: 38 · 2016: 40 · 2015: 37 · 2014: 42 · 2013: 39 · 2012: 54
- FWCI
- 29.69
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Robotics and Automation (publishedVersion)
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Robotics and Sensor-Based Localization
- Physical Sciences › Computer Science › Artificial Intelligence › Target Tracking and Data Fusion in Sensor Networks
- Physical Sciences › Engineering › Aerospace Engineering › Inertial Sensor and Navigation
- Keywords
- mobile robot localization, extended Kalman filter, sonar, model-based localization
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