Rectangular Spraying Task Assignment Via a Genetic Algorithm

Abstract

This paper deals with the assignment problem of multiple robot with the rectangular spaying tasks. Without pointing to the starting points of each task, the upper left vertex, the upper right vertex, the lower left vertex and the lower right vertex are selected by the genetic algorithm. The ergodic-based genetic algorithm is designed to achieve the shortest time and the lowest path cost. The improved mutation operator is set to accelerate the convergence process and improve the practicability of the proposed algorithm. Compared with the strategy of market-based algorithm, the genetic algorithm reduces the average time cost by 16.98% and distance costs by 9.05%, respectively.