A 2.5D Vehicle Odometry Estimation for Vision Applications
A 2.5D Vehicle Odometry Estimation for Vision Applications
著者: Paul Moran, Leroy-Francisco Periera, Anbuchezhiyan Selvaraju, Tejash Prakash, Pantelis Ermilios, John McDonald, Jonathan Horgan, Ciarán Eising
分類: cs.RO, cs.CV
原文アブストラクト
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.