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作 者:刘小臣 何卫东[1] 姚世选[1] 张迎辉[1] 崔泽 LIU Xiaochen;HE Weidong;YAO Shixuan;ZHANG Yinghui;CUI Ze(School of Mechanical Engineering,Dalian Jiaotong University,Dalian Liaoning 116028,China)
机构地区:[1]大连交通大学机械工程学院,辽宁大连116028
出 处:《机床与液压》2021年第21期1-7,共7页Machine Tool & Hydraulics
基 金:2017年度国家重点研发计划项目(2017YFB1300700)。
摘 要:微小型工业机器人以其强耦合性、可扩展性、高精度被广泛应用到各行业,然而大多数机器人以串联型为主,其结构弱刚度问题会导致机器人动作时产生振动从而影响整体稳定性。以服务型机器人为研究对象,为保证机器人结构刚度以及抓取物体过程的稳定性,对机器人整体结构刚度进行优化。对机器人进行运动学静态建模,利用刚度等效原理计算机器人关节刚度;在抓取位姿范围约束下,将机器人末端刚度椭球半轴长作为优化指标,采用改进粒子群算法(IPSO)对机器人在不同抓取位姿的刚度进行优化,并将结果与遗传算法、粒子群算法的优化结果进行对比;通过ANSYS有限元分析和实验对比机器人优化前后的末端变形量,结果表明:基于IPSO算法的机器人抓取系统刚度优化对提高机器人整体稳定性具有一定意义。Micro industrial robots are widely used in various industries due to their strong coupling,scalability and high precision.However,most robots are mainly connected in series,and the problem of low structural stiffness will cause vibration in the robot’s mo⁃tion and affect the overall stability.Taking the service robot as the research object,in order to ensure the stiffness of the robot structure and the stability of the grasping process,the overall stiffness of the robot was optimized.The kinematic static model of the robot was es⁃tablished,and the stiffness equivalence principle was used to calculate the joint stiffness of the robot;under the constraints of the grasping posture range,the robot end stiffness ellipsoid half-axis length was used as the optimization index,the improved particle swarm optimization(IPSO)algorithm was used to optimize the stiffness of the robot at different grasping poses,and the results were compared with those of genetic algorithm and particle swarm optimization algorithm;the end deformations before and after optimization were compared through ANSYS finite element analysis and experiments.The results show that the research on the stiffness optimization of the robot gripping system based on IPSO algorithm has certain significance to improve the overall stability of the robot.
关 键 词:机器人抓取系统 静态建模 关节刚度 改进粒子群(IPSO)算法 位姿优化
分 类 号:TP242.2[自动化与计算机技术—检测技术与自动化装置]
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