摘要
根据无人地面车辆自主导航的需求,提出一种给定任务点的约束条件下的最优路径实现方法.首先基于地理信息系统(GIS)平台构建为车辆行驶提供先验信息的GIS数据库,并设计研究基于计算几何的路段匹配算法,同时结合A*算法进行全局路径规划.然后根据无人地面车辆的运动特性和对路口识别的需求提出了新的路口模型,同时为保证无人地面车辆行驶轨迹的平滑性和对路口识别的精确性,对路口轨迹和U-turn轨迹进行了算法设计.最后提出了动态重规划的行驶策略.实际跑车实验证明了该设计算法的有效性.
According to the requirements of unmanned ground vehicle （UGV） autonomous navigation, an implementation method was proposed for path optimization with given task points as constraints. Firstly, a geographic information system （GIS） database was built based on the GIS platform to provide priori information for UGV. And then a road-matching algorithm was designed based on the computational geometry. Simultaneously the static and dynamic path planning was conducted combining with A＊ algorithm. Secondly, a new crossroads model was proposed according to the movement characteristics of UGV and the demand in recognizing the intersection. An algorithmic design for the intersection tracks and U-turn tracks was conducted to smooth the UGV＇s driving routes and to ensure the accuracy of intersection recognition. At last, a dynamic re-planning driving strategy was put forward. The validity of designed algorithm was verified by actual car experiments.
出处
《北京理工大学学报》
EI
CAS
CSCD
北大核心
2016年第8期851-856,861,共7页
Transactions of Beijing Institute of Technology
基金
国家自然科学基金资助项目(61173076)
国家自然科学基金重大研究计划培育资助项目(91120003)
