基于改进麻雀算法机械臂时间最优轨迹规划

Optimal Trajectory Planning for Robotic Arms Based on Improved Sparrow Algorithm

为了提高机械臂的工作效率和稳定性,采用改进麻雀搜索算法的机械臂时间最优多项式插值轨迹规划方法。通过改进Sin混沌初始化种群、发现者和跟随者比例动态调整,并加入了柯西高斯变异,优化了算法局部搜索和全局寻优的能力。以实验室的AUBO-i10机器人为研究对象,首先利用逆运动学求出给定机械臂末端路径点各个关节的位置信息,采用分段多项式拟合关节空间下运动轨迹。在限制机械臂的关节角度、运动速度和加速度的条件下,通过改进麻雀搜索算法对机械臂末端运行轨迹进行时间最短优化。使用MATLAB进行仿真,仿真结果表明,改进麻雀搜索算法在收敛速度和寻优精度有了明显的提升,有效减少了机械臂在工作中运行的时间。

A time-optimal polynomial interpolation trajectory planning algorithm using an improved sparrow search algorithm is employed to enhance the efficiency and stability of the robotic arm.The algorithm′s capabilities in local search and global optimization were optimized by enhancing Sin chaos initialization of populations,dynamically adjusting the ratios of explorers and followers,and introducing cauchy-gaussian mutation.Taking the AUBO-i10 robot as the research subject,the positions of various joints at given end-effector path points were first determined using inverse kinematics.Segment-wise polynomial fitting was applied to approximate motion trajectories in the joint space.Under constraints related to the robot arm′s running speed and joint angles,the improved sparrow search algorithm was utilized to optimize the time required for the end-effector to traverse the trajectory.Simulations were conducted using MATLAB,followed by experimental analysis.The results indicate that the improved sparrow search algorithm has shown a significant improvement in convergence speed and optimization precision,effectively reducing the operational time of the robotic arm during its tasks.