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Pose Identification and Updating in Autonomous Vehicles

Authors:
Antoni Grau
Yolanda Bolea
Rodrigo Munguia

Keywords: Attitude Estimation; Sensor Fusion; Vehicle Navigation

Abstract:
In this paper, a novel algorithm to know the pose of any autonomous vehicle is described. Such a system (Attitude and Heading Reference System, AHRS) is essential for real time vehicle navigation, guidance and control applications. For low funded projects, with simple sensors, efficient and robust algorithms become necessary for an acceptable performance, and the well-known extended Kalman filter (EKF) fulfills those requirements. In this kind of applications, the use of the EKF in direct configuration has been much less explored than its counterpart, the EKF in indirect configuration. Specifically, in this paper a novel method based on an Extended Kalman Filter in direct configuration is proposed, where the filter is explicitly derived from both kinematic and errors models. Experiments with real data show that the proposed method is able to maintain an accurate and drift-free attitude and heading estimation.

Pages: 87 to 92

Copyright: Copyright (c) IARIA, 2017

Publication date: September 10, 2017

Published in: conference

ISSN: 2308-3514

ISBN: 978-1-61208-581-4

Location: Rome, Italy

Dates: from September 10, 2017 to September 14, 2017