多策略改进麻雀算法在机械臂时间最优轨迹规划中的应用  

Application of Multi-strategy Improved Sparrow Algorithm in Time Optimal Trajectory Planning of Manipulator

作　　者：邱冰 李小兵[1] 石志新[1] 罗玉峰[1] QIU Bing;LI Xiaobing;SHI Zhixin;LUO Yufeng(School of Advanced Manufacturing,Nanchang University,Nanchang 330031)

机构地区：[1]南昌大学先进制造学院,南昌330031

出　　处：《机械科学与技术》2024年第10期1714-1722,共9页Mechanical Science and Technology for Aerospace Engineering

基　　金：国家自然科学基金项目(52165003,51365036)。

摘　　要：针对六自由度柑橘采摘机械臂时间最优轨迹规划问题,提出一种多策略改进麻雀算法(Multi-strategy improved sparrow search algorithm, MISSA)的轨迹规划方法。首先,利用改进D-H参数法建立机械臂的运动学模型,并对其正、逆运动学进行求解,然后利用3-5-3多项式插值建立机械臂关节空间的运动轨迹。最后针对普通麻雀算法,利用Logistic混沌映射均匀化种群,并融合改进正余弦策略平衡算法的局部与全局搜索能力后,得到了改进麻雀算法,并利用该算法对机械臂进行时间最优轨迹规划,再与GA、PSO、SSA算法进行对比。结果表明,多策略改进麻雀算法相比于其他3种算法在收敛速度和精度上均有明显提高,关节运行时间缩短46.7%,且优化后得到关节运动学曲线均光滑无突变,验证了算法的有效性。In order to solve the problem of time optimal trajectory planning of six-degree-of-freedom citrus picking manipulator,a multi-strategy improved sparrow search algorithm(MISSA)for trajectory planning is proposed in this paper.Firstly,the kinematics model of the manipulator is established with the improved D-H parameter method,and its forward and inverse kinematics are solved,and then the joint space trajectory of the manipulator is established by 3-5-3 polynomial interpolation.Next,aiming at the ordinary sparrow algorithm,using Logistic chaotic map to homogenize the population,and combining the local and global search ability of the improved sine and cosine strategy balance algorithm,the improved sparrow search algorithm is obtained.Finally,the algorithm is used to plan the time optimal trajectory of the manipulator,and then compared with GA,PSO and SSA algorithms.The results show that the MISSA has a significant improvement in convergence speed and accuracy compared with the other three algorithms,the joint running time is reduced by 46.7%,and the joint kinematics curves are smooth and without sudden change after optimization,which verifies the effectiveness of the new algorithm.

关 键 词：采摘机械臂 多项式插值 轨迹规划 时间最优 多策略改进麻雀算法 

分 类 号：TP241[自动化与计算机技术—检测技术与自动化装置]