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.

中文翻译：

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用于视觉应用的2.5D车辆里程计估计

本文提出了一种方法来估计车辆在世界范围内行驶时安装在车辆上的传感器的姿态，这是自动驾驶系统的重要主题。基于一组常用的车辆里程传感器，并在汽车通信总线（例如CAN或FlexRay）上提供输出，我们描述了一组步骤，将基于车轮传感器的平面里程与基于线性悬架传感器的悬架模型相结合。目的是确定照相机姿势的更准确的估计。我们概述了其在可视化和计算机视觉中的应用程序的用法。