基于改进鲸鱼算法的搬运机器人运动规划
 李静,熊瑞平*,胡英达,周程胜,巫启源
(四川大学 机械工程学院,四川 成都 610041)
摘要:针对搬运机器人搬运效率不足、稳定性效果不好等问题,使用改进鲸鱼优化算法的时间最优运动规划方法进行解决。首先将机器人模型导入MATLAB中,根据相关算法计算出机器人的空间范围,从空间范围中选取实际目标点并转换到关节空间,在关节空间中使用“四次-三次-四次”插值多项式构造机器人的轨迹,然后将各关节的角速度、角加速度作为约束条件,采用改进的鲸鱼优化算法对轨迹进行优化,缩短机器人运行时间。通过仿真实验,改进的鲸鱼算法较PSO算法规划时间缩短约30%,较标准的鲸鱼算法规划时间缩短约17%,有效提升了搬运机器人在搬运方面的效率和稳定性。
关键词:搬运机器人;运动规划;多项式插值;时间最优;鲸鱼算法
中图分类号:TP242.3            文献标志码:A            doi:10.3969/j.issn.1006-0316.2024.02.001
文章编号:1006-0316 (2024) 02-0001-07
Trajectory Planning of Handling Robot Based on Improved Whale Algorithm
LI Jing,XIONG Ruiping,HU Yingda,ZHOU Chengsheng,WU Qiyuan
( School of Mechanical Engineering, Sichuan University, Chengdu 610041, China )
Abstract:A time-optimal trajectory planning method based on improved whale optimization algorithm is proposed to solve the problems of low efficiency and insufficient stability of the robot. Firstly, the robot model is imported into MATLAB, and the space range of the robot is calculated according to the relevant algorithm. The actual target points are selected from the space range and converted to the joint space. In the joint space, the  “quartic-cubic-quartic” interpolation polynomial is used to construct the robot trajectory, and then the angular velocity and angular acceleration of each joint are taken as the constraint conditions. The improved whale optimization algorithm is used to optimize the trajectory and shorten the running time of the robot. Through simulation experiments, the planning time of the improved whale algorithm is about 30% shorter than that of the PSO algorithm, and about 17% shorter than that of the standard whale algorithm, which can effectively improve the handling efficiency and stability of the robot.
Key words:handling robot;trajectory planning;polynomial interpolation;optimal time;whale algorithm
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收稿日期:2023-06-08
基金项目:四川省重点研发项目——智能涂装产线关键技术的开发与集成(2020YFG0119);四川省智能制造与机器人重大专项课题——工业机器人成套装备研制与应用(2019ZDZX0019)
作者简介:李静(1997-),男,陕西渭南人,硕士研究生,主要研究方向为智能机器人,E-mail:664308242@qq.com。*通讯作者:熊瑞平(1970-),男,四川成都人,博士,副教授、硕士生导师,主要研究方向为工业机器人应用及智能控制技术,E-mail:xiongruiping@163.com。


 

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