基于自适应升温模拟退火算法的农业机器人全区域覆盖策略

目的 提出一种复杂农田环境下农业机器人全区域覆盖策略，以便合理规划农业机器人的工作遍历路径。方法 根据农田实际生产环境定义农业机器人复杂工作环境模型，并在此基础上建立一级分区与二级分区的概念。引入遗传算法变异操作的思想，建立基于贪婪机制的模拟退火算法优质可行解生成方法；建立解集多样性的概念，设计基于自适应升温的模拟退火算法改进方法，以此求解分区间的最佳遍历顺序问题。通过A*算法与八邻域搜索法相结合进行农业机器人跨区域衔接路径规划，依此，实现机器人覆盖全区域。结果 仿真结果表明，改进的模拟退火算法所规划的路径长度分别比传统遗传算法和模拟退火算法减少了14.7%和10.1%，收敛时的迭代次数分别减少9.8%和59.1%；农业机器人全区域覆盖仿真试验中遍历路径重复率为14.86%。高地隙喷药机器人现场遍历试验中，路径重复率为15.83%。结论 研究结果可为农业机器人在复杂农田环境中全遍历覆盖提供研究思路。

Whole area coverage strategy of agricultural robot based on adaptive heating simulated annealing algorithm

Objective To propose a whole area coverage strategy of agricultural robot in complex farmland environment, and reasonably plan the working traversal path of agricultural robot.Method The complex farmland working environment model was defined according to the actual production environment of agricultural robot, and the concepts of first-level partition and second-level partition were established. The idea of genetic algorithm mutation operation was introduced to establish a high-quality feasible solution generation method of simulated annealing algorithm based on greedy mechanism. Based on the establishment of the concept of solution set diversity, an improved method of simulated annealing algorithm based on adaptive heating was designed to solve the problem of the optimal traversal sequence between partitions. The A* algorithm was combined with the eight-neighbor search method to plan the cross-regional connection path of agricultural robot. By this way, the scheme designed in this paper could achieve that the robot covered the whole working area.Result The simulation results showed that, compared with the traditional genetic algorithm and simulated annealing algorithm, the path length planned by the improved simulated annealing algorithm was reduced by 14.7% and 10.1% respectively, and the number of iterations during convergence was reduced by 9.8% and 59.1% respectively. The repeating rate of the traversal path of the agricultural robot in the simulation test of whole area coverage was 14.86%. The path repetition rate in the field traversal test of the high ground-clearance spraying robot was 15.83%.Conclusion The research results can provide a research idea for the full traversal coverage of agricultural robot in complex farmland environment.