基于改进RRT算法的无人车路径规划研究与测试  

Research and testing of unmanned vehicle path planning based on improved RRT algorithm

作　　者：许瑶 刘晓峰[2] Xu Yao;Liu Xiaofeng(Jilin Technology College of Electronic Information,Jilin 132000,China;Aviation University Air Force,Changchun 130000,China)

机构地区：[1]吉林电子信息职业技术学院,吉林132000 [2]空军航空大学,长春130000

出　　处：《国外电子测量技术》2023年第8期132-138,共7页Foreign Electronic Measurement Technology

摘　　要：针对基本快速搜索随机树(RRT)算法在路径规划过程中存在的节点采样随机、收敛速度慢以及寻址精度低等问题,结合目标引力函数和障碍物排斥力场函数,设计了一种基于动态步长的改进RRT算法。算法采用分区域节点扩展方式,实现精细化路线规划,提升路径指向性及避障能力;同时,利用转角限制、平滑处理等方式减少无效拐点,提高路线实用性。结果表明,所用算法具有较好的抗干扰能力,可有效提高无人车的路径规划精度和作业效率,缩短货物运送路程,减少成本消耗。相比基本RRT算法,采用改进RRT算法的无人车行驶路程缩短17.7%,作业效率提高25%,成本消耗减少25%。研究结果具有一定实用性,可为仓储无人运输车应用提供理论支撑。Aiming at the problems of random node sampling,slow convergence speed,and low addressing accuracy in the path planning process of the basic RRT algorithm,an improved RRT algorithm based on dynamic step size was designed by combining the target gravity function and obstacle repulsion field function.The algorithm adopts a partitioned node expansion method to achieve refined route planning,improve path directionality and obstacle avoidance ability;At the same time,using methods such as corner restrictions and smoothing to reduce invalid inflection points and improve the practicality of the route.The results show that the algorithm used has good anti-interference ability,which can effectively improve the path planning accuracy and operational efficiency of unmanned vehicles,shorten the transportation distance of goods,and reduce cost consumption.Compared to the basic RRT algorithm,the improved RRT algorithm reduces the driving distance of unmanned vehicles by 17.7%,improves work efficiency by 25%,and reduces cost consumption by 25%.The research results have certain practicality and can provide theoretical support for the application of unmanned storage transport vehicles.

关 键 词：无人车 改进RRT算法 动态步长 路径规划 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]