摘要
三维凹形障碍物存在时,移动智能体常用的路径规划算法易陷入局部最优,使规划的路径变长或者是算法运行的时间过长,这些对于实时性要求较高的路径规划任务都是不利的。针对这一问题,提出一种非最优路径凹陷点处理的方法,避免了规划算法对非最优路径凹陷点的遍历,并用A^(*)算法规划路径。使用了MATLAB进行仿真,结果表明该方法可以防止局部最优,保证算法的实时性。
In the presence of three-dimensional concave obstacles, the path planning algorithms commonly used by mobile agents tend to fall into local optimum, making the planned path become longer, or the running time of the algorithm become too long, which are unfavorable to the path planning tasks with high real-time requirements. Therefore, this paper proposes a method for processing non-optimal path depressions to avoid the traversal of non-optimal path depressions by the planning algorithm. A^(*)algorithm was used to plan the path. MATLAB was used for simulation. The results show that this method can prevent local optimization and ensure real-time performance of the algorithm.
作者
任文杰
徐啟蕾
Ren Wenjie;Xu Qilei(School of Automation and Electrical Engineering,Qingdao University of Science and Technology,Qingdao 266061,Shandong,China)
出处
《计算机应用与软件》
北大核心
2023年第1期311-316,349,共7页
Computer Applications and Software
