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Research on Vision Navigation Technology of Porter Based on Improved Simulated Annealing Algorithms

机译:基于改进的模拟退火算法的波特视觉导航技术研究

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Aiming at the problem that the traditional path planning method of porter is easy to fall into local optimum solution and lacks general adaptability to the environment, a working environment model of porter is created by using the grid method. Based on an improved greedy algorithm for establishing a search tabu table, the simulated annealing coefficient and the grid coefficient are redefined by adding the idea of "survival of the fittest" in the genetic algorithm. An improved simulated annealing algorithm is proposed to solve the local convergence problem of greedy algorithm. Finally, the feasibility and adaptability of the algorithm to different environments are verified by simulation and practical experiments, which can effectively improve the quality of transportation vehicle path planning.
机译:针对Porter的传统路径规划方法易于陷入本地最佳解决方案,缺乏对环境的一般适应性,通过使用网格方法创建Porter的工作环境模型。基于用于建立搜索禁忌表的改进的贪婪算法,通过在遗传算法中添加“Fittest的生存”的思想来重新定义模拟退火系数和电网系数。提出了一种改进的模拟退火算法来解决贪婪算法的局部收敛问题。最后,通过模拟和实际实验验证了算法对不同环境的可行性和适应性,可以有效地提高运输车辆路径规划的质量。

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