基于改进A*算法的分拣搬运机器人路径规划
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苏州科技大学,苏州科技大学,苏州科技大学,常州工学院,苏州科技大学,苏州科技大学

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国家自然科学基金(61401297); 江苏省自然科学基金(BK20140283);江苏省高等学校自然科学研究项目:( 17KJB120011); 苏州市科技项目(SYG201708)


Path Planning of Sorting and Handling Robot Based on Improved A* Algorithm
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University of Electronic and Information Engineering,Suzhou University of Science and Technology,Suzhou,;China;Changzhou Institute of Technology,School of Computer and Information Engineering,Changzhou,;China,University of Electronic and Information Engineering,Suzhou University of Science and Technology,Suzhou,,Changzhou Institute of Technology,School of Computer and Information Engineering,Changzhou,University of Electronic and Information Engineering,Suzhou University of Science and Technology,Suzhou,University of Electronic and Information Engineering,Suzhou University of Science and Technology,Suzhou

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    摘要:

    为了解决分拣搬运机器人在路径规划过程中,遇到目标点众多的情况时存在路径寻优效率低、容易出错等问题。针对A*算法存在多个最小值时,无法实现路径最优化的问题进行研究,提出一种将蚁群算法与A*算法相结合的改进A*算法。首先使用A*算法筛选出一条最优化的路线来分布信息素,从而简化A*算法在路径规划上的运算。其次以筛选出的路线为基础,针对不同情况结合蚁群算法设计了三种通用方案,以此为基础进行具体的路径规划,从而解决A*算法本身存在的容易带入大量重复数据的问题。通过仿真与实际实验验证了本文提出的改进的A*算法能够满足自动分拣搬运的需求,值得推广与使用。

    Abstract:

    In order to solve the sorting handling optimal robot path planning in the process, often encounter target many situations exist path planning problems such as low efficiency, error prone. Multiple minimum value of A* algorithm cannot be achieved under the condition of path optimization problems are studied, and an improved A* algorithm which combine ant colony algorithm and A* algorithm is proposed. Firstly, the A* algorithm is used to select the optimal route, distribution information, so as to simplify the operation of A* algorithm. Secondly, based on the selected route, according to different situation combined with ant colony algorithm to design three kinds of general scheme which based on a specific path planning, and then solve the A* algorithm itself easily into a large number of duplicate data problems. The proposed improved A* algorithm of this paper is verified by simulation and practical experiment can meet the demand of automatic sorting handling, which is worth popularizing and using.

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蔡旻,刘士凡,陶重犇,李春光,孙云飞,班建民.基于改进A*算法的分拣搬运机器人路径规划计算机测量与控制[J].,2018,26(4):164-166.

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  • 收稿日期:2017-09-01
  • 最后修改日期:2017-09-01
  • 录用日期:2017-09-27
  • 在线发布日期: 2018-04-23
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