Authors

Abstract

In this study, the discrete artificial bee colony (DABC) algorithm was proposed to plan the path of agricultural robots traversing multiple fields in hilly areas. Based on the basic ABC algorithm as the framework, the path coding method was adopted, and the discrete crossover operator, reverse operator, immune operator, and single/multi-step 2-opt operator were comprehensively used to help hired bees, observing bees, and scout bees to generate new food sources. Finally, the optimized field traversal order and the entrance and exit distribution of each field were obtained. The simulation results showed that compared with the traditional ABC algorithm, the average shortest path of the DABC algorithm proposed in this study was shortened by 1.59%, accompanied by the less iterations contributing to algorithm convergence and good ability to jump out of the local optimal solution. The simulation experiment was carried out using real field data and field operation parameters. The field traversal order and the entrance and exit distribution obtained by the proposed method can effectively reduce the length of the transfer path and its repeatability. This study exhibits superiority and feasibility in the field traversal path planning of agricultural robots in hilly areas, and the trajectory coordinates output by the algorithm can provide a path reference for large-area operations of agricultural machinery drivers or unmanned agricultural machineries.

Abstract in Chinese

本研究针对丘陵地区的农田环境下农业机器人遍历多个田块的遍历路径问题，提出了离散人工蜂群算法对农业机器人丘陵地区农田遍历路径进行规划。以基本人工蜂群算法为框架，采用路径编码的方式，综合运用离散交叉算子，逆转算子，免疫算子和单/多步 2-opt 算子以帮助雇佣蜂，观察蜂和侦察蜂产生新食物源，最终得到优化后的田块遍历顺序以及每个田块的进出口分布。仿真结果表明，与传统人工蜂群算法相比，本研究提出的离散人工蜂群算法平均最短路径缩短1.59%，算法收敛迭代次数更少，并表现出较好的跳出局部最优解的能力。利用真实的农田数据和田间作业参数进行仿真试验，通过本研究方法得到的田块遍历顺序和进出口的排布能够有效地减少转移路径的长度和路径的重复率。本研究在农业机器人丘陵地区农田遍历路径规划上的优越性和可行性，算法输出的轨迹坐标能为农机驾驶员或无人农机在大面积作业时提供路径参考。