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浙江大学学报(工学版)
浙江大学学报(工学版)  2023, Vol. 57 Issue (1): 1-9    DOI: 10.3785/j.issn.1008-973X.2023.01.001
机械与能源工程     
基于时间冲击最优的TBM换刀机器人轨迹规划
陶治同(),陶建峰*(),覃程锦,刘成良
上海交通大学 机械系统与振动国家重点实验室，上海 200240
Trajectory planning of TBM disc cutter changing robot based on time-jerk optimization
Zhi-tong TAO(),Jian-feng TAO*(),Cheng-jin QIN,Cheng-liang LIU
State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240, China
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摘要：

为了提高隧道掘进机（TBM）换刀机器人的工作效率，减小换刀过程中的运动冲击，提出基于改进型粒子群优化（PSO）算法的轨迹优化方法. 采用位姿分离法与关节变量最小策略，对冗余关节机器人进行运动学分析. 利用所求的逆解，将目标轨迹由笛卡尔空间映射到关节空间. 针对每个关节使用5次NURBS曲线构造冲击连续的关节轨迹，以时间冲击最优构造目标函数，采用改进型PSO算法求解出最优时间序列，完成对轨迹的优化. 通过对特定的换刀任务进行轨迹规划，得到各关节的优化轨迹. 优化结果表明，提出的轨迹规划方法可以为换刀机器人各关节提供理想的轨迹，具有较强的轨迹跟踪能力. 利用5次NURBS插值法与改进型PSO优化算法，可以保证轨迹的时间最短与冲击最小，提高了运行的效率与平稳性.
关键词： TBM换刀机器人;  轨迹规划;  改进型粒子群优化;  时间冲击最优;  5次NURBS曲线    
Abstract:

A trajectory planning method based on improved particle swarm optimization (PSO) algorithm was proposed in order to improve the working efficiency of tunnel boring machine (TBM) disc cutter changing robot and reduce the motion jerk in the process of tool changing. The kinematics of the redundant joint robot was analyzed by using the position and pose separation method and the joint variable minimization strategy. The target trajectory was mapped from Cartesian space to joint space by using the inverse solution. The jerk continuous joint trajectory was constructed by using 5-degree NURBS curve for each joint. The objective function was constructed by the time jerk optimization, and the optimal time series was solved by using the improved PSO algorithm so as to complete the trajectory optimization. The trajectory planning of specific disc cutter change task was conducted, and the optimal trajectory of each joint was obtained. The optimization results show that the proposed trajectory planning method can provide an ideal trajectory for each joint of the tool changing robot and has strong trajectory tracking ability. The 5th NURBS interpolation method and the improved PSO optimization algorithm were used to ensure the shortest time and minimum impact of the trajectory, and improve the efficiency and stability of the operation.
Key words: tunnel boring machine disc cutter changing robot    trajectory planning    improved particle swarm optimization    time jerk optimization    5th NURBS curve
收稿日期: 2022-03-30 出版日期: 2023-01-17
CLC:  U 45  
基金资助: 国家重点研发计划资助项目(2018YFB1306703)
通讯作者: 陶建峰     E-mail: taozhitong@sjtu.edu.cn;jftao@sjtu.edu.cn
作者简介: 陶治同（1997—），男，硕士生，从事机器人轨迹规划的研究. orcid.org/0000-0003-0362-4567. E-mail： taozhitong@sjtu.edu.cn
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陶治同
陶建峰
覃程锦
刘成良

引用本文:

陶治同,陶建峰,覃程锦,刘成良. 基于时间冲击最优的TBM换刀机器人轨迹规划[J]. 浙江大学学报(工学版), 2023, 57(1): 1-9.

Zhi-tong TAO,Jian-feng TAO,Cheng-jin QIN,Cheng-liang LIU. Trajectory planning of TBM disc cutter changing robot based on time-jerk optimization. Journal of ZheJiang University (Engineering Science), 2023, 57(1): 1-9.

链接本文:

https://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2023.01.001    或    https://www.zjujournals.com/eng/CN/Y2023/V57/I1/1

图 1  换刀机器人的关节示意图
图 2  换刀机器人机构简图
图 3  换刀机器人运动学模型
i $a{\text{/mm}}$ $\alpha {\text{/} }(^{\circ})$ $d{\text{/mm}}$ ${\rm{offset}}/{\rm{mm}}$ $\theta {\text{/} }(^{\circ })$
1 0 0 0~3480 0 0
2 0 0 0~390 1147 0
3 0 0 364 0 ?90~90
4 0 ?90 0 0 ?30~90
5 0 90 0~460 1204 0
6 0 0 0 0 ?45~45
7 0 ?90 0 0 ?90~75
8 0 90 764 0 ?90~90
表 1  换刀机器人的DH表
图 4  轨迹优化的流程图
图 5  空间路径的采样图
位置点 d/mm θ/（°）
关节1 关节2 关节5 关节3 关节4 关节6 关节7 关节8
1 0 0 0 0 0 0 0 0
2 14.38 2.57 103.18 ?29.01 ?5.42 17.01 5.42 3.01
3 81.67 14.58 217.03 ?25.23 ?6.28 33.03 6.28 10.23
4 225.76 40.31 365.02 ?18.77 ?8.12 49.05 8.11 15.77
5 378.41 67.57 428.21 ?18.78 ?8.57 65.06 8.56 18.78
6 538.07 96.08 460.00 ?16.90 ?11.21 81.08 11.20 19.07
7 686.70 122.62 460.00 ?25.12 ?12.87 76.79 12.86 13.12
8 830.28 148.26 460.00 ?30.61 ?13.65 62.07 13.65 10.61
9 967.20 172.71 460.00 ?30.61 ?13.65 47.35 13.65 11.61
10 1125.65 201.00 460.00 ?25.60 ?16.14 32.63 16.14 10.60
11 1291.57 230.63 460.00 ?20.02 ?20.54 17.91 20.54 6.02
12 1472.53 263.34 460.00 ?16.89 ?24.43 4.85 24.42 6.21
表 2  各关节位置列表
$ i $ $v_{\rm{p}}/(\mathrm{m}\mathrm{m}\cdot\mathrm{s^{-1} })$ $a_{\rm{p}}/(\mathrm{m}\mathrm{m}\cdot{\mathrm{s} }^{-2})$ $j_{\rm{p}}/(\mathrm{m}\mathrm{m}\cdot{\mathrm{s} }^{-3})$
1 400 500 500
2 120 350 400
5 120 300 400
i vr/((°)·s?1) ar/((°)·s?2) jr/((°)·s?3)
3 75 45 45
4 60 30 40
6 80 50 45
7 70 45 30
8 90 50 45
表 3  各关节运动学约束
图 6  换刀机器人的移动关节运动曲线
图 7  换刀机器人的转动关节运动曲线
图 8  最优值收敛对比
图 9  空间优化轨迹
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