基于新型A^(*)算法的田间路径规划研究  

Study on field path planning based on novel A^(*)algorithm

作　　者：孙肖杰 吴春笃 杨官学[1] 陆向龙 SUN Xiaojie;WU Chundu;YANG Guanxue;LU Xianglong(School of Electrical and Information Engineering,Jiangsu University,Zhenjiang 212000,Jiangsu,China)

机构地区：[1]江苏大学电气信息工程学院,江苏镇江212000

出　　处：《农业装备与车辆工程》2024年第2期8-11,24,共5页Agricultural Equipment & Vehicle Engineering

基　　金：江苏大学农业装备学部项目(NZXB20200102)。

摘　　要：针对传统A^(*)算法不能满足喷雾机器人依据作物分布生成作业路径的特定场景需求,提出了基于传统A^(*)算法对其启发函数进行改进和再优化的新型A^(*)算法。首先,在传统A^(*)算法中加入新的启发函数项,改变路径点代价值的计算规则,引导算法更倾向于选取两侧有障碍物的路径点,满足农业机器人需沿着两侧障碍物行进的需求;接着,针对初步改进的新型A^(*)算法在障碍物距离较大时路径规划出现迂回和重复问题,通过引入路径判断函数项,根据相邻障碍物的间距设置不同路径代价函数,计算规则的触发条件,智能选择合适的代价函数公式,引导算法在两侧障碍物间距较大时更倾向于选择中间位置的路径点,进一步提高农业机器人的作业效率。经过仿真实验验证,该算法可以准确地选择最佳路径,达到预期效果。In view of the fact that the traditional A^(*)algorithm could not meet the specific scene requirements that the spray robot needed to generate the operation path according to the crop distribution in the farmland,a new A^(*)algorithm based on the traditional A^(*)algorithm was proposed to improve and re-optimize its heuristic function.Firstly,a new heuristic function term was added to the traditional A^(*)algorithm to change the calculation rules of the path point generation value.The guidance algorithm was more inclined to select the path points with obstacles on both sides to meet the needs of agricultural robots to travel along the obstacles on both sides.Then,aiming at the problem of path detour and repetition in the path planning of the newly improved A^(*)algorithm when the obstacle distance was large,the path judgment function term was introduced,and the trigger conditions of different path cost function calculation rules were set according to the distance between adjacent obstacles to intelligently select the appropriate cost function formula.The guidance algorithm was more inclined to select the path point in the middle position when the distance between the obstacles on both sides was large,so as to further improve the operation efficiency of the agricultural robot.Finally,the simulation results showed that the algorithm could accurately select the best path and achieve the expected effect.

关 键 词：农业机器人 路径规划 A^(*)算法 改进优化 

分 类 号：TP242.3[自动化与计算机技术—检测技术与自动化装置]