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A 2.5D Vehicle Odometry Estimation for Vision Applications

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arxiv 2105.02679 v1 pith:J6MGKSRP submitted 2021-05-06 cs.RO cs.CV

A 2.5D Vehicle Odometry Estimation for Vision Applications

Paul Moran , Leroy-Francisco Periera , Anbuchezhiyan Selvaraju , Tejash Prakash , Pantelis Ermilios , John McDonald , Jonathan Horgan , Ciar\'an Eising This is my paper
classification cs.RO cs.CV
keywords sensorsvehicleapplicationsestimateodometryposesuspensionvision
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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.

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