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A 2.5D Vehicle Odometry Estimation for Vision Applications

2021-05-06 14:01:46
Paul Moran, Leroy-Francisco Periera, Anbuchezhiyan Selvaraju, Tejash Prakash, Pantelis Ermilios, John McDonald, Jonathan Horgan, Ciarán Eising

Abstract

This paper proposes a method to estimate the pose of a sensor mounted on a vehicle as the vehicle moves through the world, an important topic for autonomous driving systems. Based on a set of commonly deployed vehicular odometric sensors, with outputs available on automotive communication buses (e.g. CAN or FlexRay), we describe a set of steps to combine a planar odometry based on wheel sensors with a suspension model based on linear suspension sensors. The aim is to determine a more accurate estimate of the camera pose. We outline its usage for applications in both visualisation and computer vision.

Abstract (translated)

URL

https://arxiv.org/abs/2105.02679

PDF

https://arxiv.org/pdf/2105.02679.pdf


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