基于GA-PSO的六轴机械臂轨迹规划方法  

Trajectory Planning Method of Six-axis Manipulator Based on GA-PSO

作　　者：石征锦[1] 董恩奇 白士宇 Shi Zheng-jin;Dong En-qi;Bai Shi-yu(Shenyang Ligong University,Shenyang 110159,China)

机构地区：[1]沈阳理工大学,辽宁沈阳110159

出　　处：《内燃机与配件》2022年第14期37-39,共3页Internal Combustion Engine & Parts

摘　　要：就目前遗传算法收敛性差且速度较慢,以及粒子群算法较容易跳进局部最优而非全局最优的情况下,提出了一种人工智能算法——GA-PSO的混合优化算法,来达到机械臂运行时间的最优。采用人工智能算法对关节空间中的位置以及事件进行优化,以此实现六轴机械臂运动轨迹的优化,即从起点位置到达目标点所花时间最短。运用5次多项式来构造关节空间插值曲线,以时间优化作为主要研究的运动轨迹规划转变为非线性且有约束的轨迹规划,进一步结合GA-PSO的混合优化算法来获取全局的最优解;利用MATLAB软件进行仿真,得出仿真结果显示该方法优于单一的GA与PSO算法。As far as the current genetic algorithm has poor convergence and slow speed, and the particle swarm algorithm is easier to jump into the local optimum rather than the global optimum.The paper comes up with a mixed optimization algorithm-GA-PSO in artificial intelligence algorithm running time of the mechanical arm to achieve the optimum. An artificial intelligent algorithm is used to optimize the positions of the joint space and events, the realization of six axis trajectory optimization of mechanical arm from the starting location to reach target takes the shortest time. The joint space interpolation bight is made up by quintic polynomials, and the trajectory planning problem with time majorization transforms into a nonlinear programming matter keeping within bounds. Then GA-PSO hybrid optimization algorithm is used to gain the whole optimal solution. The emulation results in MATLAB show that the method is superior to GA and PSO algorithms.

关 键 词：轨迹优化 六轴机械臂 混合优化算法 五次多项式 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]