基于改进模拟退火算法的搬运机器人路径规划

针对传统搬运机器人路径规划方法易陷入局部最优解,以及缺乏对环境普遍适应性的问题。应用栅格法创建搬运机器人工作环境模型,以一种建立搜索禁忌表的改进贪心算法为基础,通过加入遗传算法中“优胜劣汰”的思想,重新定义了模拟退火系数和栅格系数,提出了一种可以解决贪心算法局部收敛问题的改进模拟退火算法。最后通过仿真和具体实物实验,验证了该算法具有的可行性以及对于不同环境的适应性,能够有效地提高搬运机器人路径规划的质量。

Path Planning of Handing Robot Based on Improved Simulated Annealing Algorithm

For handling the problems that traditional path planning method of transport robot is easy to get into local optimal solution and lacking in general adaptability to environment, this paper proposed an improved grid method to create a handling robot working environment model, and based on the improved greedy algorithm, and referenced to the idea of genetic algorithm. This article defines the annealing coefficient and the lattice coefficient and puts forward an improved simulated annealing algorithm which can solve the problem of local convergence of the improved greedy algorithm. Finally, through simulation and concrete physical experiment, it is proved that this algorithm is feasible and can adapt to different environment, which can effectively improve the quality of robot path planning.