| 496 | 3 | 181 |
| 下载次数 | 被引频次 | 阅读次数 |
针对机器人导航在面向复杂环境时A*算法占用内存大、搜索时间长等问题,提出了一种基于改进A*算法的机器人导航方法。改进A*算法抛弃遍历周围点,直接将起点和终点的欧氏距离作为最短路径,若线段上有障碍物,则选取障碍物附近2个点为子起点和子终点,用A*算法寻找路径;采用n阶贝塞尔曲线平滑小范围A*算法所造成的路径曲折,根据A*算法获得的不同曲线判断贝塞尔曲线的阶数。仿真结果表明,本算法只需使用小范围的A*规划且仅需考虑A*算法部分的曲率连续问题,路径实时性得到较大提高。
Abstract:To solve the problems of high memory consumption and long search time of A* algorithm in line segment in complex environments,this paper proposes a robot navigation method based on an improved A* algorithm. The improved A* algorithm abandons the traversal of surrounding nodes and directly takes the Euclidean distance between the start and the end points as the shortest path. If there are obstacles on the line segment,the two points near the obstacle are taken as the sub-starting point and sub-ending point,and the A* algorithm is used to find the path. In addition,the n-order Bezier curve is used to smooth out the path tortuosity caused by the A* algorithm in a small range,and the order of the Bezier curve is determined according to the different curves obtained by the A* algorithm. The simulation results show that the real-time performance of the path can be greatly improved by using only a small range of A*planning and only considering the curvature continuity problem of the A* algorithm part.
[1]林依凡,陈彦杰,何炳蔚,等.无碰撞检测RRT*的移动机器人运动规划方法[J].仪器仪表学报,2020,41(10):257-267.
[2] JIANG H J,SUN Y. Research on global path planning of electric disinfection vehicle based on improved A*algorithm[J].Energy Reports,2021,7:1270-1279.
[3] LAI X,LI J H,CHAMBERS J. Enhanced center constraint weighted A*algorithm for path planning of petrochemical inspection robot[J]. Journal of Intelligent&Robotic Systems,2021,102(4):1-15.
[4]李贤.基于RRT算法的采茶机器人路径规划研究[J].农机化研究,2023,45(9):180-183.
[5]刘梦奇,王维强,田良宇.基于B样条曲线的无人驾驶车辆Informed RRT*算法研究[J].智能计算机与应用,2022,12(4):25-29.
[6]武斌,金春洁.基于小波神经网络与遗传算法的机器人全局路径和局部路径优化[J].自动化与仪表,2023,38(7):33-37.
[7]孙鹏娜,张忠民.基于蚁群算法的无人船平滑路径规划[J].电子科技,2023,36(3):14-20.
[8]王维,裴东,冯璋.改进A*算法的移动机器人最短路径规划[J].计算机应用,2018,38(5):1523-1526.
[9]迟旭,李花,费继友.基于改进A*算法与动态窗口法融合的机器人随机避障方法研究[J].仪器仪表学报,2021,42(3):132-140.
[10]耿宏飞,神健杰. A*算法在AGV路径规划上的改进与验证[J].计算机应用与软件,2022,39(1):282-286.
[11]劳彩莲,李鹏,冯宇.基于改进A*与DWA算法融合的温室机器人路径规划[J].农业机械学报,2021,52(1):14-22.
[12]SEYYEDHASANI H,DVORAK J S. Reducing field work time using fleet routing optimization[J]. Biosystems Engineering,2018,169:1-10.
[13] LI H,ZHANG Z,YANG K,et al. Improving heuristic functions in A*algorithm path planning[J]. Journal of Research in Science and Engineering,2022,4(10):12-16.
[14]齐凤莲,王晓庆,张帼英.改进A*算法的AGV避障路径规划研究[J].机床与液压,2023,51(9):34-39.
[15]周俊,何永强.农业机械导航路径规划研究进展[J].农业机械学报,2021,52(9):1-14.
[16]龚鹏,李文博,马庆升,等.基于改进A*算法的无人车路径规划研究[J].组合机床与自动化加工技术,2023(3):17-20,24.
基本信息:
DOI:10.19573/j.issn2095-0926.202401008
中图分类号:TP242;TP18
引用信息:
[1]石迅,杨耿煌,陈庆斌.基于改进A*算法的机器人导航研究[J].天津职业技术师范大学学报,2024,34(01):44-48.DOI:10.19573/j.issn2095-0926.202401008.
2023-06-26
2023
2023-08-01
2024-03-25
2024
1
2024-03-28
2024-03-28