Cited by 1,245Robotics and Sensor-Based LocalizationTarget Tracking and Data Fusion in Sensor NetworksInertial Sensor and Navigation

Mobile robot localization by tracking geometric beacons

Leonard, J.J., Durrant-Whyte, H.F.·1991·IEEE Transactions on Robotics and Automation

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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Crossref · 10.1109/70.88147

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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].”
  • 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].”

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Authors
Leonard, J. J., & Durrant-Whyte, H. F.
Affiliations
University of Oxford (GB)
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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