基于改进海洋捕食者算法的机械臂逆解求解
Inverse Solution of Manipulator Based on Improved Marine Predators Algorithm
巫启源 1熊瑞平 1何智东 2胡英达 1李静 1周程胜1
作者信息
- 1. 四川大学机械工程学院,成都 610065
- 2. 新达泵阀股份有限公司,达州 635000
- 折叠
摘要
针对冗余机械臂逆运动学求解较难、精度较低的问题,在已有海洋捕食者算法(marine preda-tors algorithm,MPA)基础上,引入Tent映射初始化策略、精英反向学习策略、自适应t分布变异机制,提出了改进海洋捕食者算法(IMPA),并将其应用于冗余机械臂逆解求解中.4 个典型测试函数的测试结果表明,IMPA的求解精度和计算稳定性比MPA和另一种改进MPA更优;冗余机械臂逆解求解实例结果表明,IMPA的求解速度更快,求解精度和稳定性更佳,机械臂位姿精度提高,位姿误差降低,具有一定优势.
Abstract
In order to solve the inverse kinematics of redundant manipulators with difficulty and low accu-racy,based on the existing marine predators algorithm(MPA),the Tent mapping initialization strategy,elite Reverse learning strategy,and adaptive t distribution mutation mechanism are introduced,and an im-proved marine predator algorithm(IMPA)is proposed and applied to solve the inverse kinematics of re-dundant manipulators.The test results of four typical test functions indicate that IMPA has better solving ac-curacy and computational stability than MPA and another improved MPA;The example results of redundant robotic arm inverse solution show that IMPA has faster solving speed,better solving accuracy and stability,improved robotic arm pose accuracy,and reduced pose error,which has certain advantages.
关键词
冗余机械臂/逆运动学求解/海洋捕食者算法/精英反向学习Key words
redundant manipulator/inverse kinematics/marine predators algorithm/elite opposition-based learning引用本文复制引用
基金项目
宜宾-四川大学战略合作科技创新研发项目(2020CDYB-11)
宜宾-四川大学战略合作科技创新研发项目(2019CDYB-5)
四川大学-达州市政府战略合作项目(2020CDDZ-11)
出版年
2024
NETL
NSTL
维普
万方数据