基于粒子群算法的机器人关节空间最优运动轨迹规划
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摘要
为了提高机器人的工作效率,对机器人轨迹规划进行研究。文章依据机器人运动学特征,提出了一种关节空间运动轨迹规划的算法。其基于粒子群算法,采用高次多项式插值的方式,对机器人关节空间的运动轨迹进行拟合。在确保运动轨迹平滑的同时,保证了关节运动的平稳性。最后,在MATLAB中进行仿真实验,实现了关节空间最优运动规划。该算法结构简单,易于实现,为提高机器人的工作效率提供了科学依据。
To improve the working efficiency of the robot,the paper studied the trajectory planning of robot.According to the kinematics characteristics of the robot,proposed an algorithm of joint space trajectory planning.Based on the particle swarm optimization algorithm,the trajectory of the joint space of the robot is fitted by using the high order polynomial interpolation method.Ensuring the smooth of motion trajectory,meanwhile,guarantee the stability of joint motion.Finally,the simulation experiment is carried out in MATLAB,and the optimal motion planning of joint space is realized.The algorithm is simple and easy to implement,which provides a scientific basis for improving the working efficiency of the robot.
To improve the working efficiency of the robot,the paper studied the trajectory planning of robot.According to the kinematics characteristics of the robot,proposed an algorithm of joint space trajectory planning.Based on the particle swarm optimization algorithm,the trajectory of the joint space of the robot is fitted by using the high order polynomial interpolation method.Ensuring the smooth of motion trajectory,meanwhile,guarantee the stability of joint motion.Finally,the simulation experiment is carried out in MATLAB,and the optimal motion planning of joint space is realized.The algorithm is simple and easy to implement,which provides a scientific basis for improving the working efficiency of the robot.
引文
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[11]董慧颖,梁爽.基于MATLAB的PUMA560机器人运动学仿真[J].无线互联科技,2014(5):179-180.
[12]姚禹.粒子群优化算法的发展及应用[J].信息记录材料,2009(4):50-54.
[2]马丹妮,李传江,张自强.基于遗传算法的七自由度机器人轨迹规划[J].实验室研究与探索,2016(9):33-37.
[3]赫建立,朱龙英,成磊,等.基于遗传算法的6-DOF机器人最优时间轨迹规划[J].机械传动,2015(9):41-45.
[4]郭清达,万传恒,史步海.基于遗传算法的工业机器人时间最优轨迹规划及仿真研究[J].计算机测量与控制,2014,22(4):1240-1242.
[5]恽为民,席裕庚.基于遗传算法的机器人关节空间最优运动规划[J].机器人,1995(4):206-217.
[6]勾月凯,葛为民,王肖锋,等.基于粒子群算法的可重构模块化机器人速度约束下轨迹规划[J].天津理工大学学报,2016,32(5):6-11,47.
[7]李小为,胡立坤,王琥.速度约束下PSO的六自由度机械臂时间最优轨迹规划[J].智能系统学报,2015,10(3):393-398.
[8]Fang Gao,Qiang Zhao,Gui-Xian Li.Path Planning of Continuum Robot Base dona New Improved Particle Swarm Optimization Algorithm[J].Journal of Harbin Institute of Technology,2013(4):78-84.
[9]Ellips MASEHIAN,Davoud SEDIGHIZADEH.Multi-objective robot motion planning using aparticle swarm optimization model[J].Journal of Zhejiang University–Science C(Computers&Electronics),2010(8):607-619.
[10]于楚泓.基于MATLAB的机器人运动学建模及仿真分析[J].机电信息,2017(9):78-79.
[11]董慧颖,梁爽.基于MATLAB的PUMA560机器人运动学仿真[J].无线互联科技,2014(5):179-180.
[12]姚禹.粒子群优化算法的发展及应用[J].信息记录材料,2009(4):50-54.