Square Root SAM: Simultaneous Localization and Mapping via Square Root Information Smoothing
Georgia Institute of Technology
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Abstract
Solving the SLAM (simultaneous localization and mapping) problem is one way to enable a robot to explore, map, and navigate in a previously unknown environment. Smoothing approaches have been investigated as a viable alternative to extended Kalman filter (EKF)-based solutions to the problem. In particular, approaches have been looked at that factorize either the associated information matrix or the measurement Jacobian into square root form. Such techniques have several significant advantages over the EKF: they are faster yet exact; they can be used in either batch or incremental mode; are better equipped to deal with non-linear process and measurement models; and yield the entire robot trajectory, at lower…
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Authors
2Topics & keywords
Topics
Keywords
- Simultaneous localization and mapping
- Extended Kalman filter
- Smoothing
- Square root
- Jacobian matrix and determinant
- Computer science
- Heuristics
- Kalman filter
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