摘要
针对传统TEB(time elastic band)算法在智能小车通过狭窄通道时容易陷入局部最优,同时通过弯道时容易出现加速度突变等局限性,在传统TEB算法的基础上,结合同源TEB轨迹优化算法,在动态时变障碍物的环境中对传统TEB算法进行改进.首先,通过构建拓扑地图搜索所有可行路径;然后,通过代价函数对每条路径进行评估,确定最优路径;最后,额外添加加速度约束,保证智能小车平顺通过弯道.实验结果表明,本文算法能够针对狭窄通道快速找到最优合理路径,同时也能大大抑制智能小车在通过弯道时加速度的冲击突变.
In response to the limitations of traditional TEB algorithms,such as being prone to local optimum while intelligent cars pass through narrow channels and the sudden changes of acceleration while they pass through the curves,in this paper,the traditional TEB algorithm is improved in the environment of dynamic time-varying obstacles by combining the homologous TEB trajectory optimization algorithm with the traditional TEB algorithm.Firstly,all feasible paths are searched by constructing a topological map;Secondly,each path is evaluated through a cost function to determine the optimal path;Finally,additional acceleration constraints are added to ensure that the intelligent cars pass through the curve smoothly.The experimental results show that the proposed algorithm can quickly find the optimal and reasonable path for narrow channels.Furthermore,the sudden acceleration impact of intelligent cars is greatly suppresses while they pass through the curves.
作者
陈法法
苏晨
蒋浩
万刚
陈保家
CHEN Fafa;SU Chen;JIANG Hao;WAN Gang;CHEN Baojia(Hubei Key Laboratory of Hydroelectric Machinery Design&Maintenance,China Three Gorges University,Yichang 443002,China;Overhaul and Maintenance Factory of China Yangtze Power Co.,Ltd.,Yichang 443002,China)
出处
《三峡大学学报（自然科学版）》
CAS
北大核心
2024年第2期90-97,共8页
Journal of China Three Gorges University：Natural Sciences
基金
国家自然科学基金项目(51975324)
国家大坝安全工程技术研究中心开放基金(CX2022B06)
湖北省教育厅科研项目(B2021036)。
作者简介
通信作者:陈法法(1983-),男,教授,博士,主要研究方向为机电装备动态测试与故障诊断.E-mail:chenfafa2005@126.com。
