Multi-machine Cooperation Task Planning Based on Ant Colony Algorithm
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    Abstract:

    In order to realize the dispatching management of multimachine cooperative navigation operation in dynamic farmland environment, the task planning of multimachine cooperative navigation operation based on ant colony algorithm was studied. The task planning of multimachine cooperative operation was divided into two parts: task allocation and task sequence planning. Firstly, a task allocation model of multimachine cooperative operation was established by combining global and local methods, considering both path cost and task execution ability. Then, by comparing and analyzing the task sequence planning problem and traveling salesman problem, the task sequence planning model of agricultural machinery operation was established by using ant colony algorithm. Finally, the simulation experiment of task sequence planning based on ant colony algorithm was carried out by using Matlab platform. According to the actual land information of Zhuozhou experimental farm, different groups of task sets were set to analyze the optimization path, the shortest and average distance of each generation and the fitness evolution curve of ant colony algorithm. The simulation results showed that the task sequence optimization based on ant colony algorithm can effectively reduce the cost of path and improve the efficiency of operation. The running time of the algorithm was less than 1 s, which preliminarily met the realtime requirements of multimachine cooperative operation, and provided a basis for further solving the multimachine cooperative navigation operation in the field environment.

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History
  • Received:April 20,2019
  • Revised:
  • Adopted:
  • Online: July 10,2019
  • Published: July 10,2019
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