Optimal trajectory planning of robot energy consumption based on improved sparrow search algorithm

Yaosheng Zhou, Guirong Han, Ziang Wei, Zixin Huang, Xubing Chen, Jianjun Wu
{"title":"Optimal trajectory planning of robot energy consumption based on improved sparrow search algorithm","authors":"Yaosheng Zhou, Guirong Han, Ziang Wei, Zixin Huang, Xubing Chen, Jianjun Wu","doi":"10.1177/00202940231220080","DOIUrl":null,"url":null,"abstract":"In order to reduce the energy consumption of the welding robot and ensure the cooperative movement of the robot joints, a trajectory planning method with optimal energy consumption based on improved sparrow search algorithm is proposed. Firstly, the trajectory planning model with optimal energy consumption is established based on the joint torque and angular velocity of the robot. To make the velocity, acceleration and jerk of each joint of the robot be bounded and continuous, the joint space trajectory is constructed with seventh degree B-spline curve. The total energy consumption of the robot is calculated by combining kinematic and dynamic parameters. On the basis of improved sparrow search algorithm, the time series corresponding to the optimal energy consumption is solved by using elite reverse learning, non-dominated sorting and Gaussian-Cauchy variation strategy, and then the optimal continuous motion trajectory of energy consumption is planned. The simulation results show that the proposed method can not only achieve continuous smooth control objective, but also effectively reduce energy consumption.","PeriodicalId":510299,"journal":{"name":"Measurement and Control","volume":"59 46","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Measurement and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/00202940231220080","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In order to reduce the energy consumption of the welding robot and ensure the cooperative movement of the robot joints, a trajectory planning method with optimal energy consumption based on improved sparrow search algorithm is proposed. Firstly, the trajectory planning model with optimal energy consumption is established based on the joint torque and angular velocity of the robot. To make the velocity, acceleration and jerk of each joint of the robot be bounded and continuous, the joint space trajectory is constructed with seventh degree B-spline curve. The total energy consumption of the robot is calculated by combining kinematic and dynamic parameters. On the basis of improved sparrow search algorithm, the time series corresponding to the optimal energy consumption is solved by using elite reverse learning, non-dominated sorting and Gaussian-Cauchy variation strategy, and then the optimal continuous motion trajectory of energy consumption is planned. The simulation results show that the proposed method can not only achieve continuous smooth control objective, but also effectively reduce energy consumption.
基于改进的麻雀搜索算法的机器人能耗优化轨迹规划
为了降低焊接机器人的能耗,确保机器人关节的协同运动,提出了一种基于改进的麻雀搜索算法的最优能耗轨迹规划方法。首先,根据机器人的关节力矩和角速度建立能耗最优的轨迹规划模型。为使机器人各关节的速度、加速度和颠簸有界且连续,用七度 B 样条曲线构建关节空间轨迹。结合运动学和动力学参数,计算出机器人的总能耗。在改进的麻雀搜索算法基础上,利用精英反向学习、非支配排序和高斯-考奇变异策略求解最优能耗对应的时间序列,进而规划出最优能耗的连续运动轨迹。仿真结果表明,所提方法不仅能实现连续平滑控制目标,还能有效降低能耗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信