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首页> 外文会议>10th France-Japan Congress, 8th Europe-Asia Congress on Mechatronics >Error reduction for large rotational motion estimation of autonomous vehicle
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Error reduction for large rotational motion estimation of autonomous vehicle

机译：自动驾驶车辆大旋转运动估计的误差减小

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摘要

This paper presents a methodology for reducing error in large rotation using an omnidirectional camera based on bundle adjustment technique. One of the most traditional problems of motion estimation method is accumulative error. The advantage of omnidirectional camera is that allows tracking landmarks in large rotation and long travel. The minimal error is applied on set of sequent images so that landmarks are tracked in all images. The global motion is estimated in high accuracy based on utility to optimize the partial rotation error based on the bundle adjustment technique. The criterion for evaluation is the angular deviation between projection and back-projection of corresponding points. This criterion makes advantage to use quasiconvex optimization method for solving problem. The experimental equipment consists of an electric vehicle with an omnidirectional camera, laser sensor and GPS receiver. The data was collected under large rotation and different terrain in outdoor environments. In order to evaluate proposed method, the vehicle positions were compared with GPS information and plotted on satellite images from Google Maps.
机译：本文提出了一种基于束调整技术的全向摄像机减少大旋转误差的方法。运动估计方法最传统的问题之一是累积误差。全向摄像机的优点是可以大旋转和长行程地跟踪地标。将最小误差应用于后续图像集，以便在所有图像中跟踪界标。基于实用程序，可以高精度估计全局运动，并基于束调整技术优化局部旋转误差。评估的标准是相应点的投影与反投影之间的角度偏差。该准则有利于使用拟凸优化方法求解问题。实验设备包括带有全向摄像机的电动汽车，激光传感器和GPS接收器。该数据是在室外环境中大旋转和不同地形下收集的。为了评估提出的方法，将车辆位置与GPS信息进行比较，并绘制在Google Maps的卫星图像上。

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