基于蚁群算法的运动时间优化算法研究
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TP301.6

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四川省科技计划重点研发项目(2017GZ0352);国家“十三五”重大专项(2016ZX05045)


Optimization of multijoint robot motion of hydraulic drilling vehicle based on ant colony algorithm
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    摘要:

    液压凿岩台车在现代隧道掘进施工中发挥了重要作用,现有液压凿岩台车在进行寻找孔位时,由操作人员完成,找孔顺序、找孔时间无优化,导致寻找孔位时间浪费,效率低。针对上述问题,本文对长臂多关节智能凿岩机面向超大隧道断面与复杂孔系的多节变运动与寻孔路径的时间进行优化,创新研究如下:通多对凿岩隧道形式、开挖方式分析和炮眼参数的设定,对左右两机械臂钻孔任务提出无碰规划方案,同时以多关节机械臂各个关节变量的总变化时间作为优化目标函数,采用蚁群算法优化目标函数,得到寻找孔位时间最短的优化寻找孔位路径,提高了液压凿岩台车机械臂的定位找孔效率。

    Abstract:

    Hydraulic rock drilling rig plays an important role in modern tunneling construction. The existing hydraulic drilling rig is completed by the operator when locating the hole position. The order of locating holes and the time to search holes is not optimized, which results in time waste and low efficiency. In view of the above problems, in this paper, the multinode motion and the time of locating hole path of long arm multijoint intelligent rock drill are optimized for large tunnel section and complex hole system. The innovative research is as follows: by the rock drilling tunnel form and excavation mode analysis, as well as the explosion hole parameters setting, a collisionfree planning is proposed for the left and right manipulator drilling tasks. At the same time, the total change time of each joint variable of the multijoint manipulator is used as the optimization objective function. The ant colony algorithm is used to optimize the objective function, and the optimized hole finding path with the shortest hole positioning time is obtained, which improves the positioning and finding efficiency of the hydraulic rock drilling rig mechanical arm.

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引用本文格式: 魏鹏,罗红波,赵康,龙伟. 基于蚁群算法的运动时间优化算法研究[J]. 四川大学学报: 自然科学版, 2018, 55: 1171.

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  • 收稿日期:2018-05-08
  • 最后修改日期:2018-07-06
  • 录用日期:2018-07-13
  • 在线发布日期: 2018-11-29
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