A new state vector for range-only SLAM

This paper considers the simultaneous localization and mapping (SLAM) problem where the range-only sensor is used. Landmark initialization is a critical issue in range-only SLAM due to the lack of bearing information from the robot to the landmarks. A new state vector is proposed to be used in solvi...

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Bibliographic Details
Main Authors: Ahmad, A., Shoudong Huang, Wang, J. J., Dissanayake, G.
Format: Conference Proceeding
Language:English
Subjects:
Covariance matrix
Landmark initialization
Least squares optimization
Noise
Optimization
Range-only SLAM
Simultaneous localization and mapping
Sparse matrices
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Summary:This paper considers the simultaneous localization and mapping (SLAM) problem where the range-only sensor is used. Landmark initialization is a critical issue in range-only SLAM due to the lack of bearing information from the robot to the landmarks. A new state vector is proposed to be used in solving the range-only SLAM. In the new state vector, the landmark position is represented in different ways under different situations. This new representation avoids the need of multiple hypotheses on the landmark positions implemented in most of the existing range-only SLAM algorithms. Simulation and experimental results demonstrate the effectiveness of the new range-only SLAM algorithm using the new state vector within the least squares framework.
ISSN:1948-9439
1948-9447
DOI:10.1109/CCDC.2011.5968704