论文标题
通过线性优化的自动驾驶汽车校准
Autonomous Vehicle Calibration via Linear Optimization
论文作者
论文摘要
在导航活动中,移动车辆的运动学参数起着重要作用。进程最常用于死去的估算。但是,使用此方法,错误的积累是一个缺点。结果,有必要校准探射参数以最大程度地减少误差积累。本文提出了基于连续最小平方编程的管道,以通过校准应用模型的参数来最大程度地减少运动型车辆模型连续时间步长的任意地标的相对位置。结果表明,开发的管道通过小型数据集产生了准确的结果。
In navigation activities, kinematic parameters of a mobile vehicle play a significant role. Odometry is most commonly used for dead reckoning. However, the unrestricted accumulation of errors is a disadvantage using this method. As a result, it is necessary to calibrate odometry parameters to minimize the error accumulation. This paper presents a pipeline based on sequential least square programming to minimize the relative position displacement of an arbitrary landmark in consecutive time steps of a kinematic vehicle model by calibrating the parameters of applied model. Results showed that the developed pipeline produced accurate results with small datasets.