摘要
针对传统机械手在码垛抓取过程中轨迹优化问题,提出了改进型蝴蝶优化算法对机械手轨迹进行优化,用以提高机械手抓取的效率、准确性。提出利用切比雪夫混沌映射种群初始化,对惯性权重因子进行改进,以防止算法陷入局部最优。随后将改进型蝴蝶优化算法与原蝴蝶优化算法在3个基准函数测试中进行对比,改进型蝴蝶优化算法比原算法有显著提升,随后在Matlab中对机械手第三关节进行最优轨迹运动仿真,结果表明利用改进型蝴蝶优化算法在轨迹时间最优中有良好的表现。
To resolve the trajectory optimization problem of traditional manipulators in the palletizing gripping process,an improved butterfly optimization algorithm is proposed to optimize the manipulator trajectory for improving the efficiency and accuracy of manipulator gripping.It is proposed to use Chebyshev chaotic mapping population initialization to improve the inertia weight factor to prevent the algorithm from falling into local optimum.The improved butterfly optimization algorithm is then compared with the original butterfly optimization algorithm in three benchmark function tests,and the improved butterfly optimization algorithm has a significant improvement over the original algorithm,and then the optimal trajectory motion of the third joint of the manipulator is simulated using Matlab software,and the results show that the improved butterfly optimization algorithm has good performance in trajectory time optimization.
作者
郭北涛
涂修贤
GUO Beitao;TU Xiuxian(School of Mechanical and Power Engineering,Shenyang University of Chemical Technology,Shenyang 110142,China)
出处
《机械工程师》
2024年第5期5-8,共4页
Mechanical Engineer
关键词
轨迹规划
蝴蝶算法
切比雪夫混沌映射
惯性权重因子
trajectory planning
butterfly algorithm
Chebyshev chaotic mapping
inertial weighting factor
