摘要
在机器人避障路径规划中,传统的RRT算法随机性过大,使得避障效率低下,同时存在部分狭窄空间难以规划的问题,依靠结合其他算法思想的方式,改进优化路径规划过程。设计了一种结合人工势场法思想的改进RRT算法,通过改进选点算法的方式,提出了一种改进后的增益复合选点函数,根据其受势力场和狭窄空间的综合影响,建立新的节点选择算法,有概率地生成节点,减少更多的无效选点,大大提高了整体的选点效率,节约了大量的时间,完成整个路径规划工作。实验采用Matlab数学仿真软件进行验证,采用多种针对性地图进行测试实验,在普通工作环境下成功率提高了13%,工作时间减少了67.6%;在复杂工作环境下成功率提高了16.5%,工作时间减少了22.1%。不论在哪种情况下,改进后的算法都大大增加了求解成功率和求解效率。
In the robot obstacle avoidance path planning,the randomness of the traditional RRT algorithm is too large,which makes the obstacle avoidance efficiency low.At the same time,it is difficult to plan in some narrow space.By combining the ideas of other algorithms,the optimization path planning process can be improved.An improved RRT algorithm combined with the idea of artificial potential field method was designed.By improving the point selection algorithm,an improved gain composite point selection function was proposed.According to the comprehensive influence of force field and narrow space,a new node selection algorithm was established to generate nodes with probability,reduce more invalid points,and greatly improve the overall point selection efficiency.It saved a lot of time and completed the whole path planning.The experiment was verified by Matlab mathematical simulation software and tested by a variety of targeted maps.In the ordinary working environment,the success rate was increased by 13%and the working time was reduced by 67.6%.In the complex working environment,the success rate was increased by 16.5%and the working time was reduced by 22.1%.In any case,the improved algorithm greatly increases the success rate and efficiency.
作者
王稷尧
袁锋伟
Wang Jiyao;Yuan Fengwei(School of Mechanical Engineering,University of South China,Hengyang,Hunan 421001,China)
出处
《机电工程技术》
2022年第3期161-164,298,共5页
Mechanical & Electrical Engineering Technology
基金
湖南省协同创新中心开放基金项目(编号:2019KFZ04)。
关键词
路径规划
RRT算法
人工势场法
节点选择
path planning
RRT algorithm
artificial potential field method
node update
