关键词: 路径寻优, 无人农机, 排序优化, 蚁群算法

Abstract: Promoting vegetable mechanization and unmanned planting can guarantee the benefits of highquality vegetable largescale planting technology, and effectively guarantee the quality and quality of vegetables, which is conducive to the development of the industrial system of vegetable largescale production planting technology. This paper uses the GPS positioning point set for unmanned tractor operation to transform the actual agricultural operation area into a regular rectangle. On this basis, an optimization model with the shortest total turning distance of the unmanned tractor is established, and the ant colony algorithm is used to search the path sequence of unmanned tractor cultivated land. At the same time, considering that the traditional ant colony algorithm is easy to fall into the local optimum and the global search ability is insufficient, an improved ant colony algorithm based on the harmony search strategy is proposed. The sigmoid function and the harmony search mechanism are introduced to improve the path search ability and obtain high sequence of quality farmland working paths. In this paper, the traditional ant colony algorithm (AC), the elite ant colony algorithm (ELAC) and the shuttle and back operation methods are used as comparison algorithms, and the operation path search experiment of unmanned tractors is carried out for different farmland operation scales. The test results show that the total turning distance obtained by the algorithm in this paper is reduced by 35.53%-43.08% compared with the shuttle tillage method, and reduced by 24.98%-86.88% compared with the return tillage method. The elite ant colony algorithm has better performance in smallscale operation areas, but as the scale of vegetable fields expands, the optimization effect of the improved harmony ant colony algorithm is more obvious.

Key words: path optimization, unmanned agricultural machinery, ranking optimization, ant colony algorithm