改进ABC算法的串联机械臂多目标优化
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摘要
针对串联机械臂工作时间最优、能耗最优、脉动最优的轨迹优化问题,提出一种基于改进人工蜂群算法的多目标轨迹优化方法。文中采用5次NURBS曲线插值法建立工作轨迹数学模型,构造高阶连续关节运行轨迹并对其进行合理规划。以串联机械臂运行时间、能量消耗和脉动冲击为目标建立目标函数,通过改进人工蜂群算法进行优化设计并获得Pareto最优解集,运用归一化权重目标函数获取期望解。选择PUMA560串联机械臂进行仿真分析,结果表明:5次NURBS曲线轨迹规划方法有效构造平滑轨迹,改进人工蜂群算法能够实现满足约束条件的多目标优化,验证了算法的有效性,为后续研究奠定基础。
Aim at the trajectory optimization problem of optimal working time, optimal energy consumption and optimal pulsation of the series manipulator, a multi-target trajectory optimization method based on improved artificial bee colony algorithm was proposed. In this paper, a five-time curve interpolation method was used to establish a mathematical model of the working trajectory, and the high-order continuous joint run trajectory wa constructed and rationally planned. The objective function was established with the aim of series manipulator run time, energy consumption and pulsation shock. The artificial bee colony algorithm was used to optimize the design and obtain the optimal solution set. The normalized weight objective function iwas used to obtain the desired solution. The simulation of the tandem manipulator was carried out. The results show that the five-curve trajectory plan method effectively constructs a smooth trajectory. The improved artificial bee colony algorithm can achieve multi-objective optimization that satisfies the constraints. The effectiveness of the algorithm was verified and the basis for subsequent research was laid.
Aim at the trajectory optimization problem of optimal working time, optimal energy consumption and optimal pulsation of the series manipulator, a multi-target trajectory optimization method based on improved artificial bee colony algorithm was proposed. In this paper, a five-time curve interpolation method was used to establish a mathematical model of the working trajectory, and the high-order continuous joint run trajectory wa constructed and rationally planned. The objective function was established with the aim of series manipulator run time, energy consumption and pulsation shock. The artificial bee colony algorithm was used to optimize the design and obtain the optimal solution set. The normalized weight objective function iwas used to obtain the desired solution. The simulation of the tandem manipulator was carried out. The results show that the five-curve trajectory plan method effectively constructs a smooth trajectory. The improved artificial bee colony algorithm can achieve multi-objective optimization that satisfies the constraints. The effectiveness of the algorithm was verified and the basis for subsequent research was laid.
引文
[1] 管成,王飞,张登雨.基于NURBS的挖掘机器人时间最优轨迹规划[J].吉林大学学报(工),2015,45(2):540-546.
[2] 孙亮,马江,阮晓钢.六自由度串联机械臂轨迹规划与仿真研究[J].控制工程,2010,17(3):388-392.
[3] 喻骁,刘东,兰维瑶.基于PSO算法的串联机械臂PID控制器参数优化[J].组合机床与自动化加工技术,2011(2):89-92.
[4] Liu X L,Xiong L P.Mechanical Arm Active Disturbance Rejection Control Based on Artificial Bee Colony Algorithm[J].Applied Mechanics & Materials,2014,513-517(513-517):1511-1514.
[5] 任子武,王振华,孙立宁.基于改进人工蜂群算法的并联机器人正运动学解[J].机械工程学报,2013,49(13):48-55.
[6] Elkhateeb N A,Badr R I.Novel PID Tracking Controller for 2DOF Robotic Manipulator System Based on Artificial Bee Colony Algorithm[J].DOI:10.1515/ecce-2017-0008.
[7] 李小霞,汪木兰,刘坤,等.基于五次B样条的机械手关节空间平滑轨迹规划[J].组合机床与自动化加工技术,2012(8):39-42.
[8] 魏焕新,胡招娣,唐明珠.基于Logistic模型的改进人工蜂群算法[J].兰州理工大学学报,2017,43(2):104-109.
[9] 葛宇,梁静,王学平,等.改进人工蜂群算法求解多目标连续优化问题[J].计算机科学,2014,41(6):254-259.
[10] Wen S,Xia J,Gao R,et al.Improved artificial bee colony algorithm based optimal navigation path for mobile robot[C]// Intelligent Control and Automation,IEEE,2016:2928-2933.
[2] 孙亮,马江,阮晓钢.六自由度串联机械臂轨迹规划与仿真研究[J].控制工程,2010,17(3):388-392.
[3] 喻骁,刘东,兰维瑶.基于PSO算法的串联机械臂PID控制器参数优化[J].组合机床与自动化加工技术,2011(2):89-92.
[4] Liu X L,Xiong L P.Mechanical Arm Active Disturbance Rejection Control Based on Artificial Bee Colony Algorithm[J].Applied Mechanics & Materials,2014,513-517(513-517):1511-1514.
[5] 任子武,王振华,孙立宁.基于改进人工蜂群算法的并联机器人正运动学解[J].机械工程学报,2013,49(13):48-55.
[6] Elkhateeb N A,Badr R I.Novel PID Tracking Controller for 2DOF Robotic Manipulator System Based on Artificial Bee Colony Algorithm[J].DOI:10.1515/ecce-2017-0008.
[7] 李小霞,汪木兰,刘坤,等.基于五次B样条的机械手关节空间平滑轨迹规划[J].组合机床与自动化加工技术,2012(8):39-42.
[8] 魏焕新,胡招娣,唐明珠.基于Logistic模型的改进人工蜂群算法[J].兰州理工大学学报,2017,43(2):104-109.
[9] 葛宇,梁静,王学平,等.改进人工蜂群算法求解多目标连续优化问题[J].计算机科学,2014,41(6):254-259.
[10] Wen S,Xia J,Gao R,et al.Improved artificial bee colony algorithm based optimal navigation path for mobile robot[C]// Intelligent Control and Automation,IEEE,2016:2928-2933.