EKF SLAM updates in O(n) with Divide and Conquer SLAM

In this paper we describe divide and conquer SLAM (D&C SLAM), an algorithm for performing simultaneous localization and mapping using the extended Kalman filter. D&C SLAM overcomes the two fundamental limitations of standard EKF SLAM: 1.) the computational cost per step is reduced from O(n 2...

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Bibliographische Detailangaben

Hauptverfasser:	Paz, L.M., Jensfelt, P., Tardos, J.D., Neira, J.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	ALGORITHM Computational efficiency Costs Covariance matrix Estimation error Information filters SIMULTANEOUS LOCALIZATION Simultaneous localization and mapping Sparse matrices State estimation Stochastic processes Vehicles
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