摘要
为了减弱机械臂的抖动并提高其工作效率,以四自由度机械臂为研究对象,提出了一种改进型粒子群优化(Improved Particle Swarm Optimization, IPSO)算法。该算法的惯性权重和学习因子能够随着迭代次数的增加进行线性变化,不再是传统粒子群算法中的固定值。以优化机械臂运动时间为目标,选取机械臂工作空间中可到达的路径点,并根据逆运动学求出了各路径点对应的关节角度。利用IPSO算法对机械臂运动时间进行优化,并采用3-5-3插值法对机械臂运动过程进行了拟合。结果表明:相对传统粒子群优化算法来说,IPSO算法的收敛速度较高,采用该算法进行的机械臂轨迹规划使机械臂整个轨迹的运动时间缩短了约45.7%。
In order to reduce the jitter of the manipulator and improve work efficiency,an improved particle swarm optimization(IPSO)algorithm was proposed to take the four-DOF manipulator as the research object,in which the inertia weight and learning factor presented linear changes according to different iterations,instead of the fixed value under the traditional particle swarm optimization algorithm,with the goal of optimizing the running time of the manipulator.The reachable path points in the working space of the manipulator were selected,the joint angles at each path point were solved by inverse kinematics,the time was optimized by IPSO algorithm,and the motion process of the manipulator was fitted by 3-5-3 interpolation method.The results show that the convergence speed of the IPSO algorithm is increased,the running time of the whole trajectory of the robot arm is shortened by 45.7%,and the working efficiency of the robot arm is effectively improved.
作者
梁昌兴
姚佳俊
金哲增
李金泉
LIANG Changxing;YAO Jiajun;JIN Zhezeng;LI Jinquan(School of Mechanical Engineering,Shenyang Ligong University,Shenyang 110159,China)
出处
《成组技术与生产现代化》
2024年第3期13-21,共9页
Group Technology & Production Modernization
基金
国家级大学生创新创业训练计划资助项目(202310144023)。
关键词
机械臂
优化算法
粒子群优化
轨迹规划
robot arm
optimization algorithm
particle swarm optimization
trajectory planning
