苹果园内无人割草机多机协同作业路径优化算法  

A path optimization algorithm for cooperative operation of multiple unmanned mowers in apple orchard

作　　者：谢金燕 刘丽星 杨欣[1,2] 王潇洒 王旭 刘树腾 XIE Jinyan;LIU Lixing;YANG Xin;WANG Xiaosa;WANG Xu;LIU Shuteng(College of Mechanical and Electrical Engineering,Hebei Agricultural University,Baoding 071000,China;Hebei Province Smart Agriculture Equipment Technology Innovation Center,Baoding 071000,China)

机构地区：[1]河北农业大学机电工程学院,河北保定071000 [2]河北省智慧农业装备技术创新中心,河北保定071000

出　　处：《华南农业大学学报》2024年第4期578-587,共10页Journal of South China Agricultural University

基　　金：国家现代农业产业技术体系建设专项(CARS-27);河北省现代农业产业技术体系(HBCT2023120202)。

摘　　要：[目的]提高新型苹果园内多台无人割草机协同作业时的工作效率。[方法]提出一种改进的遗传算法(Improved genetic algorithm, IGA),为每台割草机分配并优化作业路径。根据实际无人割草机作业情况,以总转弯时间和作业时长为综合优化目标,构建无人割草机多机作业路径优化模型。通过设定任务阈值,引入改良圈策略和Metropolis准则改进遗传算法(Genetic algorithm, GA)以求解模型。[结果]仿真试验结果表明,IGA为每台割草机分配的任务量均衡,与GA相比,IGA优化后的矩形果园路径平均总转弯时间和作业时长分别减少22.89%和19.36%;与分区作业相比,IGA优化后的矩形果园路径平均总转弯时间和作业时长分别减少45.53%和10.68%。在梯形果园中,IGA不受果树分布影响,与GA和分区作业相比,平均总转弯时间分别减少14.38%和34.08%,平均作业时长分别减少23.71%和10.07%。[结论]所提出的IGA性能更好,能有效优化机群的作业路径,缩短作业时长,提高作业能力。[Objective]To improve the work efficiency of cooperative operation of multiple unmanned lawn mowers in modern apple orchard.[Method]An improved genetic algorithm(IGA)was proposed to assign and optimize the operating path for each mower.According to the actual operation of unmanned mowers,taking the total turning time and operation time as the comprehensive optimization goal,the optimization model for the operating path of multi-unmanned mower was constructed.In order to solve the model,the genetic algorithm(GA)was improved by setting task thresholds,introducing the improved circle algorithm and Metropolis criterion.[Result]Simulation experiments results showed that the IGA balanced the workload assigned to each unmanned mower.Compared with GA,the path optimized by IGA resulted in an average reduction of 22.89%and 19.36%in the total turning time and operation time,respectively,in the rectangular orchard.Compared with the partition operation,the total turning time and operation time of the path optimized by IGA were reduced by an average of 45.53%and 10.68%,respectively,in the rectangular orchard.In the trapezoidal orchard,IGA was not affected by the distribution of fruit trees.Compared with GA and partition operation,the average value of total turning time reduced by 14.38%and 34.08%,respectively,while the average value of operation time reduced by 23.71%and 10.07%,respectively.[Conclusion]The proposed IGA performs better and can effectively optimize the operating paths of the fleet,reducing the operation duration and improving work capacity.

关 键 词：路径优化 无人割草机 协同作业 遗传算法 苹果园 

分 类 号：S24[农业科学—农业电气化与自动化] S224.1[农业科学—农业工程] S661.1