基于蚁群四次贝塞尔曲线的无人车路径规划  

Unmanned vehicle path planning based on ant colony quartic Bezier curve

作　　者：张金炜 王文扬[2] 郭蓬[2] 高嵩[2] ZHANG Jinwei;WANG Wenyang;GUO Peng;GAO Song(Hebei University of Technology,Tianjin 300132,China;China Automotive Technology&Research Center Co.,Ltd.,Tianjin 300300,China)

机构地区：[1]河北工业大学,天津300132 [2]中国汽车技术研究中心有限公司,天津300300

出　　处：《现代电子技术》2019年第13期113-116,共4页Modern Electronics Technique

基　　金：国家重点研发计划(2017YFB0102500)~~

摘　　要：为了实现在障碍物环境下规划出符合无人车行驶曲率并安全避障的路径,提出一种蚁群算法与四次贝塞尔曲线融合的路径规划方法。首先在栅格地图下利用蚁群算法规划出从起始点到目标点的全局最短路径;然后将路径分割成有限个位置点,在每两个点之间生成具有行驶曲率、避障安全距离的贝塞尔曲线;最后形成一条连续的无人车行驶路径。经过仿真验证,证明了此方法的有效性和可行性。In order to plan the path conforming to driving curvature and safe obstacle avoidance of unmanned vehicle in the obstacle environment,a path planning method fusing ant colony optimization algorithm and quartic Bezier curve is proposed. The ant colony optimization algorithm is used to plan the global shortest path from the starting point to the target point under the grid map. The path is divided into a finite number of points,and the Bezier curve with driving curvature and safe obstacle avoidance distance is generated between every two points. After that,a continuous unmanned driving path is formed. The effectiveness and feasibility of this method are verified with simulation.

关 键 词：路径规划 蚁群算法 贝塞尔曲线 行驶曲率 避障 安全距离 

分 类 号：TN911.1-34[电子电信—通信与信息系统]