Volume 48 Issue 3
Mar.  2022
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SHEN Shuce, SHI Yannan, SONG Jianfeng, et al. Research on trajectory planning of drill rig manipulator based on improved particle swarm optimization[J]. Journal of Mine Automation，2022，48(3)：71-77, 85. DOI: 10.13272/j.issn.1671-251x.2021090049
Citation: SHEN Shuce, SHI Yannan, SONG Jianfeng, et al. Research on trajectory planning of drill rig manipulator based on improved particle swarm optimization[J]. Journal of Mine Automation，2022，48(3)：71-77, 85. DOI: 10.13272/j.issn.1671-251x.2021090049
shu

Research on trajectory planning of drill rig manipulator based on improved particle swarm optimization

  • 1.

    School of Mechanical and Equipment Engineering, Hebei University of Engineering, Handan 056038, China

  • 2.

    Jikai (Hebei) Mechatronics Technology Co., Ltd., Shijiazhuang 050000, China

  • 3.

    Hebei Coal Ecological Protection Mining Industry Technology Research Institute, Handan 056038, China

  • 4.

    Handan Key Laboratory of Intelligent Vehicle, Handan 056038, China

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  • Received Date: September 13, 2021
  • Revised Date: January 25, 2022
  • Accepted Date: March 06, 2022
  • Available Online: March 09, 2022
    Graphical Abstract
    • Abstract
  • The manipulator is an important device of anti-outburst and anti-impact drill rig, which is related to whether the drill rig can drill normally and truly realize unmanned operation. In order to ensure the rapid, accurate and stable operation of the drill rig manipulator, the trajectory planning optimization is particularly important. There are some problems in the existing trajectory planning of drill rig manipulator, such as higher order, prematurity of optimization algorithm and so on. In order to solve the above problems, a time optimal trajectory planning method of drill rig manipulator based on improved particle swarm optimization ( PSO) algorithm is proposed. Firstly, the 3D model of the drill rig manipulator is constructed by using the standard Denavit-Hartenberg ( D-H), and the workspace of the manipulator is obtained by Monte Carlo method, and four path points are selected as interpolation points from the workspace. Secondly, in order to make the manipulator reach the specified position quickly and smoothly, the trajectory of the manipulator is constructed by using 3-5-3 piecewise polynomial interpolation in the joint space. Finally, by the improved PSO algorithm, the constructed trajectory is optimized in the shortest time, and the optimal trajectory planning of the drill rig manipulator is obtained. The Matlab simulation results show that the time optimal trajectory planning method of the drill rig manipulator based on improved PSO algorithm can not only ensure the smooth operation of each joint of the drill rig manipulator, but also reduce the running time from 3.168 5 s to 2.385 4 s, reduce the overall running time by about 25% compared with that before optimization, and improve the efficiency of the manipulator.
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    • References (16)
  • [1]
    卢新明,阚淑婷. 煤矿动力灾害本源预警方法关键技术与展望[J]. 煤炭学报,2020,45(增刊1):128-139.

    LU Xinming,KAN Shuting. Key technology and prospect of the original source early warning method for coal mine dynamic disaster[J]. Journal of China Coal Society,2020,45(S1):128-139.
    [2]
    国家煤矿安全监察局. 煤矿机器人重点研发目录[EB/OL]. [2021-08-13]. https://www.chinamine-safety.gov.cn/zfxxgk/fdzdgknr/tzgg/201901/t20190109_349156.shtml.

    National Coal Mine Safety Supervision Bureau. Catalogue of key research and development of coal mine robots [EB/OL]. [2021-08-13]. https://www.chinamine-safety.gov.cn/zfxxgk/fdzdgknr/tzgg/201901/t20190109_ 349156.shtml.
    [3]
    付荣,居鹤华. 基于粒子群优化的时间最优机械臂轨迹规划算法[J]. 信息与控制,2011,40(6):802-808.

    FU Rong,JU Hehua. Time-optimal trajectory planning algorithm for manipulator based on PSO[J]. Information and Control,2011,40(6):802-808.
    [4]
    HUANG Junsen,HU Pengfei,WU Kaiyuan,et al. Optimal time-jerk trajectory planning for industrial robots[J]. Mechanism and Machine Theory,2018,121:530-544. DOI: 10.1016/j.mechmachtheory.2017.11.006
    [5]
    韩顺杰,单新超,于爱君,等. 基于改进粒子群算法的工业机器人轨迹规划[J]. 制造技术与机床,2021(4):9-14.

    HAN Shunjie,SHAN Xinchao,YU Aijun,et al. Industrial robot trajectory planning based on improved PSO algorithm[J]. Manufacturing Technology & Machine Tools,2021(4):9-14.
    [6]
    陈晗,李林升. 基于复合形法的时间最优机械臂轨迹规划[J]. 机械传动,2019,43(3):72-75.

    CHEN Han,LI Linsheng. Trajectory planning of time optimal manipulator based on complex method[J]. Mechanical Transmission,2019,43(3):72-75.
    [7]
    乐英,岳艳波. 六自由度机器人运动学仿真及轨迹规划[J]. 组合机床与自动化加工技术,2016(4):89-92.

    YUE Ying,YUE Yanbo. The kinematics simulation and trajectory planning of six-DOF robot[J]. Modular Machine Tool & Automatic Manufacturing Technique,2016(4):89-92.
    [8]
    王学琨,李刚,周东凯,等. 基于DE的时间最优6−DOF机械臂轨迹规划算法[J]. 计算机仿真,2015,32(8):332-337. DOI: 10.3969/j.issn.1006-9348.2015.08.072

    WANG Xuekun,LI Gang,ZHOU Dongkai,et al. Time-optimal trajectory planning algorithm based on DE for 6-DOF manipulator[J]. Computer Simulation,2015,32(8):332-337. DOI: 10.3969/j.issn.1006-9348.2015.08.072
    [9]
    赵明辉. 双臂并联煤矸石分拣机器人及其轨迹规划研究[J]. 工矿自动化,2020,46(9):57-63.

    ZHAO Minghui. Research on dual-arm parallel coal gangue sorting robot and its trajectory planning[J]. Industry and Mine Automation,2020,46(9):57-63.
    [10]
    郭锐,石月,李永涛,等. 液压凿岩机器人机械臂轨迹规划研究[J]. 中国工程机械学报,2021,19(4):289-294.

    GUO Rui,SHI Yue,LI Yongtao,et al. Research on trajectory planning of hydraulic rock drilling robot manipulator[J]. Chinese Journal of Construction Machinery,2021,19(4):289-294.
    [11]
    徐尤南,刘志强,陈洁. 基于粒子群算法的码垛机器人时间轨迹优化研究[J]. 华东交通大学学报,2021,38(3):75-81.

    XU Younan,LIU Zhiqiang,CHEN Jie. Time trajectory optimization of palletizing robot based on particle swarm optimization[J]. Journal of East China Jiaotong University,2021,38(3):75-81.
    [12]
    赵丽娟,张海宁,岳海涛,等. 滚筒螺旋叶片的激光熔覆中机械臂路径轨迹研究[J]. 煤炭学报,2020,45(增刊2):1041-1051.

    ZHAO Lijuan,ZHANG Haining,YUE Haitao,et al. Path and trajectory of manipulator in laser cladding of shearer blade[J]. Journal of China Coal Society,2020,45(S2):1041-1051.
    [13]
    王晓丽,侯媛彬,王涛. 基于VC++的工业机器人轨迹规划研究[J]. 工矿自动化,2009,35( 5):34-37.

    WANG Xiaoli,HOU Yuanbin,WANG Tao. Research on trajectory planning of industrial robot based on VC++[J]. Industry and Mine Automation,2009,35( 5):34-37.
    [14]
    李小为,胡立坤,王琥. 速度约束下PSO的六自由度机械臂时间最优轨迹规划[J]. 智能系统学报,2015,10(3):393-398.

    LI Xiaowei,HU Likun,WANG Hu. PSO-based time optimal trajectory planning for six degrees of freedom robot manipulators with speed constraints[J]. CAAI Transactions on Intelligent Systems,2015,10(3):393-398.
    [15]
    黄超,茅健,马丽,等. 基于改进粒子群算法的时间最优机械臂轨迹规划[J]. 上海工程技术大学学报,2020,34(3):238-246.

    HUANG Chao,MAO Jian,MA Li,et al. Time-optimal trajectory planning for manipulator based on improved particle swarm optimization algorithm[J]. Journal of Shanghai University of Engineering Science,2020,34(3):238-246.
    [16]
    SHI Yannan,QI Penglei,LIU Yang,et al. Channel modeling and optimization of leaky coaxial cable network in coal mine based on state transition method and particle swarm optimization algorithm[J]. IEEE Access,2021,9:86889-86898. DOI: 10.1109/ACCESS.2021.3088842
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    [8]ZHA Bing. Design of intelligent control system for vehicle cooling fa[J]. Journal of Mine Automation, 2013, 39(3): 98-100.
    [9]ZHANG Guo-Wei. Research of Fault Detection and Intelligent Diagnosis Technology of Heavy-loading Machinery in Copper-scandium Metal Mine[J]. Journal of Mine Automation, 2011, 37(8): 34-37.
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