基于改进蝴蝶搜索算法的六自由度机械臂路径规划

Path Planning of 6-DOF Manipulator Based on Improved Butterfly Search Algorithm

针对目前机械臂路径规划的主流算法,如RRT算法、蝴蝶算法和人工势场法等在全局搜索时易遇到寻优精度低、收敛速度慢,在局部搜索时易陷入局部最优解等问题,提出一种改进蝴蝶搜索算法。针对基本蝴蝶算法在种群初始化时添加了Cubic映射,在进行全局和局部搜索时加入非线性惯性权重系数和融入樽海鞘群算法,在确定最优解后加入了柯西变异,以此来提高算法收敛速度和寻优精度等问题。通过MATLAB构建六自由度机械臂和三维空间障碍物的三维模型,并进行仿真实验。结果表明:改进后的蝴蝶算法增强了收敛速度和寻优精度。最后进行了真机实验,验证了改进后的蝴蝶算法能够快速实现机械臂的路径规划。

Aiming at the problems of current mainstream path planning algorithms such as RRT algorithm,butterfly algorithm,artificial potential field method,such as low optimization accuracy,slow convergence speed in global search,and local optimal solution in local search,an improved butterfly search algorithm was proposed.Cubic mapping was added to the basic butterfly algorithm during population initialization,nonlinear inertia weight coefficients were added to the global and local search,salp group algorithm was integrated,Cauchy mutation was added after the optimal solution was determined,so as to improve the convergence speed and optimization accuracy.The 3D model of a 6-DOF manipulator and the 3D space obstacle was constructed by MATLAB,and simulation experiments were conducted.The simulation results show that the improved butterfly algorithm enhances the convergence speed and optimization accuracy.Finally,the real machine experiments were made.It shows that the improved butterfly algorithm can be used to quickly achieve path planning for the manipulator.