Pose identification and updating in autonomous vehicles
Document typeConference lecture
PublisherInternational Academy, Research, and Industry Association (IARIA)
Rights accessOpen Access
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.
CitationGrau, A., Bolea, Y., Munguía, R.F. Pose identification and updating in autonomous vehicles. A: International Conference on Sensor Device Technologies and Applications. "SENSORDEVICES 2017: The Eighth International Conference on Sensor Device Technologies and Applications: September 10-14, 2017, Rome, Italy". Rome: International Academy, Research, and Industry Association (IARIA), 2017, p. 87-92.