Fast 3D pose estimation with out-of-sequence measurements

We present an algorithm for pose estimation using fixed-lag smoothing. We show that fixed-lag smoothing enables inclusion of measurements from multiple asynchronous measurement sources in an optimal manner. Since robots usually have a plurality of uncoordinated sensors, our algorithm has an advantag...

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Vydané v:2007 IEEE/RSJ International Conference on Intelligent Robots and Systems s. 2486 - 2493
Hlavní autori: Ranganathan, A., Kaess, M., Dellaert, F.
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 01.10.2007
Predmet:
Delay estimation
Filtering algorithms
Global Positioning System
Mobile robots
Robot sensing systems
Simultaneous localization and mapping
Smoothing methods
Testing
Time measurement
Wheels
ISBN:9781424409112, 142440911X
ISSN:2153-0858
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Shrnutí:We present an algorithm for pose estimation using fixed-lag smoothing. We show that fixed-lag smoothing enables inclusion of measurements from multiple asynchronous measurement sources in an optimal manner. Since robots usually have a plurality of uncoordinated sensors, our algorithm has an advantage over filtering-based estimation algorithms, which cannot incorporate delayed measurements optimally. We provide an implementation of the general fixed-lag smoothing algorithm using square root smoothing, a technique that has become prominent. Square root smoothing uses fast sparse matrix factorization and enables our fixed-lag pose estimation algorithm to run at upwards of 20 Hz. Our algorithm has been extensively tested over hundreds of hours of operation on a robot operating in outdoor environments. We present results based on these tests that verify our claims using wheel encoders, visual odometry, and GPS as sensors.
ISBN:9781424409112
142440911X
ISSN:2153-0858
DOI:10.1109/IROS.2007.4399318