Authors

Abstract

In recent years, the problem of “rural labor shortage” in China has become increasingly serious, with a large number of young laborers going out to work, leading to an increasing amount of idle rural land. The intensification of population aging and the reduction of agricultural labor force in China resulted in an urgent demand for agricultural robots. With the rapid development of agricultural machinery and automation technology, agricultural robots have been continuously developing. They can better adapt to the development of biotechnology in agriculture, and traditional harvesting methods may undergo significant changes, with an increased focus on the cultivation of crops. Therefore, this paper introduces a new encoding scheme on the basis of traditional genetic algorithm (GA) and proposes an improved double encoding GA. This new encoding scheme is used on the crossover link, whereas the path node sequence encoding scheme is still used on the mutation link. The selection operation is placed after the mutation, and the merging sorting and elitist selection are performed on the parent population, crossover population, and mutation population before selection, thereby accelerating the convergence speed. On the basis of the improved GA, the three-dimensional path of the apple harvesting robot is designed and planned, with the addition of adaptive adjustment function during the progress. The experimental simulation results show that the three-dimensional path planning of the apple harvesting mobile robot based on the improved GA can minimize the number of paths and loops and well meet the operational requirements of the harvesting robot.

Abstract in Chinese

近年来，我国“农村劳动力短缺”问题日益严重，大量年轻劳动力外出务工，导致农村闲置土地数量不断增加。随着中国人口老龄化的加剧和农业劳动力的减少，劳动力缺口较大，对农业机器人的需求迫切。随着农业机械及其自动化技术的快速发展，农业机器人也在不断发展。它们可以更好地适应农业生物技术的发展，传统的收获方法可能会发生重大变化，越来越注重作物的种植。因此，本文在传统遗传算法（GA）的基础上引入了一种新的编码方案，并提出了一种改进的双编码GA。这种新的编码方案用于交叉链路，而路径节点序列编码方案仍用于变异链路。变异后进行选择操作，选择前对亲本种群、交叉种群和变异种群进行合并排序和精英选择，从而加快收敛速度。在改进遗传算法的基础上，设计并规划了苹果收获机器人的三维路径，并在过程中加入了自适应调整功能。实验仿真结果表明，基于改进遗传算法的苹果收获移动机器人三维路径规划可以使路径和回路的数量最小化，很好地满足收获机器人的操作要求。