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点焊机器人复杂轨迹逆运动学组合优化求解
引用本文:周友行,张建勋,董银松. 点焊机器人复杂轨迹逆运动学组合优化求解[J]. 焊接学报, 2010, 31(9): 21-24
作者姓名:周友行  张建勋  董银松
作者单位:湘潭大学,机械工程学院,湖南,湘潭,411105
基金项目:国家自然科学基金资助项目,教育部留学回国人员科研启动基金,湖南省高校创新平台开放基金
摘    要:针对6自由度点焊机器人复杂轨迹上多点焊接作业时的逆运动学组合求解问题,通过构建机器人运动学模型的非线性方程组,提出了一种离线编程的变进制变步长求解可逆优化迭代算法.该算法在给定位置优化目标下,每次迭代过程中,逐步缩小机器人每个关节变量变化值,同时依次做"前进、后退、保持一步"的试探判断策略,逐步迭代计算得到满足精度要求的数值解.通过对六自由度点焊机器人在复杂轨迹上作业的数值模拟,证明该算法设计简单,求解效率高,而且能在多组非线性方程组中优化组合所求数值解,同时保证机器人关节运动的平稳性.

关 键 词:点焊机器人  逆运动学  变步长  复杂轨迹规划
收稿时间:2009-04-01

An optimization algorithm for combination inverse kinematics problems of welding robot in complex trajectory
ZHOU Youhang,ZHANG Jianxun and DONG Yinsong. An optimization algorithm for combination inverse kinematics problems of welding robot in complex trajectory[J]. Transactions of The China Welding Institution, 2010, 31(9): 21-24
Authors:ZHOU Youhang  ZHANG Jianxun  DONG Yinsong
Affiliation:School of Mechanical Engineering, Xiangtan University, Xiangtan 411105, Hunan, China,School of Mechanical Engineering, Xiangtan University, Xiangtan 411105, Hunan, China and School of Mechanical Engineering, Xiangtan University, Xiangtan 411105, Hunan, China
Abstract:To solve the combination problems of six DOF welding robot''s inverse kinematics in complex trajectory planning,a variable step-size and revisable optimization algorithm was presented by building the nonlinear equations of robot kinematics models.Based on the conception of variable step and variable scale,the test strategy of ''forward,backward or maintain a step'' was adopted to approach the optimization objective for each joint under the given error,and the precision numerical solutions could be met after iterative searches.The computed conclusion showed that this method was effective and the program was easy to design.Moreover,the numerical solutions of the inverse kinematics could be optimized in nonlinear equations.At the same time,the stationary of six DOF welding robot joint movements in complex trajectory could be guaranted.
Keywords:welding robot  inverse kinematics  variable step-size  complex trajectory planning
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