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作 者:许永桥 倪艳光[1] 潘若鸣 刘玉 王恒迪[1] XU Yongqiao;NI Yanguang;PAN Ruoming;LIU Yu;WANG Hengdi(School of Mechatronics Engineering,Henan University of Science and Technology,Luoyang,Henan 471003,China;Luoyang Qiange Robot Tehnology Co.,Ltd.,Luoyang,Henan 471000,China)
机构地区:[1]河南科技大学机电工程学院,河南洛阳471003 [2]洛阳千歌机器人科技有限公司,河南洛阳471000
出 处:《轻工机械》2023年第2期66-71,77,共7页Light Industry Machinery
基 金:山东省重点研发计划(2020CXGC011003)。
摘 要:针对传统机械臂轨迹规划效率较低的问题,课题组提出了对传统遗传算法初始种群的选取及种群的变异策略改进的方法。该方法以三次B样条插值曲线作为轨迹规划的基础,以各关节运动角速度、角加速度、角加加速度作为运动约束,使用改进型遗传算法(improved genetic algorithm,IGA)进行时间优化,可以得到满足运动约束条件的时间最优运动轨迹。课题组以自主研发的QFB140机械臂作为研究对象,采用改进型D-H参数进行标识,并导入MATLAB进行仿真。结果表明:IGA在时间优化上有了较大提升,进一步实现了时间最优轨迹规划,提高了工作的效率。Aiming at the low fficiency of traditional manipulator trajectory planning,an improvement on the method of traditional genetic algorithm to select the initial population and the population mutation strategy was proposed.With cubic B-spline interpolation curve as the basis of trajectory planning,the motion speed,acceleration and jerk of each joint were used as motion constraints,and an improved genetic algorithm(IGA)was adopted for time optimization to obtain the time optimal motion trajectory that satisfied the kinematic constraints.Taking the self-developed QFB140 manipulator as the research object,the improved D-H parameters were used for identification and imported it into MATLAB for simulation.The results show that the IGA has a great improvement in time optimization,and further realizes the time optimal trajectory planning,and improves work eficiency.
分 类 号:TH113[机械工程—机械设计及理论]
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