Improved genetic algorithm for orchard lawn mower operation path planning
To improve the efficiency of orchard mowing machines and address the mowing machines' path planning problem,this paper proposes a method called IGA (Improved Genetic Algorithm).First,through an analysis of different operational scenarios,the path planning problem of the mowing machine is transformed into a scheduling and ordering problem for operations,and a mathematical model is built based on the mowing machine's operational environment.Second,based on the GA (Genetic Algorithm),a dynamic linear calibration method is used to amplify the differences between fitness values,and a fitness function is designed.Through optimization of the operators,the algorithm's performance and convergence speed are improved while ensuring the search capability of the genetic algorithm.Finally,15 different orchards with different parameters are simulated,and two standardized orchards are selected for field experiments to validate the performance of the improved genetic algorithm.Our results show the improved genetic algorithm performs better in optimization and convergence speed,and efficiently solves the path planning problem of mowing machines in orchards.
orchard lawn mowerpath planningimproved genetic algorithmdynamic linear calibration
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