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Quaternion-based EKF-SLAM from relative pose measurements: observability analysis and applications

Published online by Cambridge University Press:  01 April 2014

Luca Carlone ,
Vito Macchia ,
Federico Tibaldi  and
Basilio Bona
Luca Carlone*
Affiliation:
College of Computing, Georgia Institute of Technology, Atlanta, USA
Vito Macchia
Affiliation:
Dipartimento di Automatica e Informatica, Politecnico di Torino, Torino, Italy
Federico Tibaldi
Affiliation:
Dipartimento di Automatica e Informatica, Politecnico di Torino, Torino, Italy
Basilio Bona
Affiliation:
Istituto Superiore Mario Boella, Torino, Italy
*
*Corresponding author. E-mail: [email protected]
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Summary

In this work, we investigate a quaternion-based formulation of 3D Simultaneous Localization and Mapping with Extended Kalman Filter (EKF-SLAM) using relative pose measurements. We introduce a discrete-time derivation that avoids the normalization problem that often arises when using unit quaternions in Kalman filter and we study its observability properties. The consistency of the estimation errors with the corresponding covariance matrices is also evaluated. The approach is further tested on real data from the Rawseeds dataset and it is applied within a delayed-state EKF architecture for estimating a dense 3D map of an unknown environment. The contribution is motivated by the possibility of abstracting multi-sensorial information in terms of relative pose measurements and for its straightforward extensions to the multi robot case.

Keywords

3D EKF-SLAMUnit quaternionsObservabilityRelative pose measurementsDelayed-state filters
Type
Articles
Information
Robotica , Volume 33 , Issue 6 , July 2015 , pp. 1250 - 1280
Copyright
Copyright © Cambridge University Press 2014 

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