改进的多项式曲线拟合轨迹预测算法
Trajectory prediction algorithm based on improved polynomial curve fitting
黄万炎 1杜万和 2杨淑珍 2俞涛1
作者信息
- 1. 上海大学机电工程与 自动化学院,上海 200444
- 2. 上海大学机电工程与 自动化学院,上海 200444;上海第二工业大学智能制造与控制工程学院,上海 201209
- 折叠
摘要
针对传统多项式曲线拟合轨迹预测算法对复杂多变的轨迹预测准确率不高问题,提出改进的多项式曲线拟合轨迹预测算法.首先,获得轨迹的曲率、挠率阈值;然后,通过该阈值识别预测误差可能较大的轨迹部位,并采用插值滚动预测算法进行预测;最后,采用双误差预测值更新算法,对预测值进行更新.仿真结果表明,相较于传统多项式曲线拟合轨迹预测算法,所提算法的平均位移误差(average displacement error,ADE)下降了42.77％,最终位移误差(final displacement error,FDE)下降了36.62％,从而验证了所提算法的可行性和有效性.
Abstract
Aiming at the problem that the traditional polynomial curve fitting trajectory prediction algorithm is not accurate enough for complex and changeable trajectory prediction,an improved polynomial curve fitting trajectory prediction algorithm is proposed.Firstly,the curvature and torsion thresholds of the trajectory are obtained.Secondly,the trajectory parts with larger prediction errors are identified by the thresholds above,and the interpolation rolling prediction algorithm is used for prediction.Finally,the double errors predictive value update algorithm is used to update the predicted value.Simulation results show that compared with the traditional polynomial curve fitting trajectory prediction algorithm,the average displacement error(ADE)of the proposed algorithm decreases by 42.77％.The final displacement error(FDE)reduces by 36.62％,which verifies the feasibility and the effectiveness of the proposed algorithm.
关键词
多项式曲线拟合/轨迹预测/曲率/挠率/误差Key words
polynomial curve fitting/trajectory prediction/curvature/torsion/error引用本文复制引用
出版年
2024
NETL
NSTL
万方数据