摘要(Abstract)：
为了有效提高机械手控制中逆向运动学求解的速度和准确度,提出一种基于极限学习机-入侵性杂草优化的机械手逆向运动学求解方法;建立工业六自由度机械手的正向运动学模型,并利用训练较快的极限学习机计算机械手关节角度向量,即输出机械手关节逆运动学初解;利用入侵性杂草优化算法对得到的初始逆解进行优化,取最小适应度时的杂草位置作为输出,以便得到最佳的逆向运动学求解。结果表明,相比于基于粒子群优化-反向传播神经网络的求解方法,所提出方法的机械手末端执行器的精度更高,平均计算时间仅为5.68 ms,实时性更好。
关键词(KeyWords)： 六自由度机械手;入侵性杂草优化;极限学习机;运动学模型;逆解
基金项目(Foundation): 国家自然科学基金项目(61741303);; 广东省教育厅高校青年创新人才项目(自然科学)(2016KQNCX2354);; 广西自然科学基金项目(2018GXNSFAA294061);; 广西重点研发计划项目(2017AC05027)
作者(Author): 杨雨佳,神显豪,刘珊珊,程日光
DOI: 10.13349/j.cnki.jdxbn.20201215.001
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