现代制造工程 ›› 2025, Vol. 540 ›› Issue (9): 60-65.doi: 10.16731/j.cnki.1671-3133.2025.09.008

• 机器人技术 • 上一篇    下一篇

基于渐进式BP神经网络的蛇形机械臂逆运动学求解方法

徐湘融1, 马国梁1, 许立松2, 王天涯1   

  1. 1 南京理工大学能源与动力工程学院,南京 210094;
    2 南京理工大学自动化学院,南京 210094
  • 收稿日期:2024-10-15 出版日期:2025-09-18 发布日期:2025-09-23
  • 作者简介:徐湘融,硕士研究生,主要研究方向为绳驱连续型机械臂设计及控制研究。马国梁,副教授,硕士研究生导师,主要研究方向为导航、制导与控制。E-mail:xuxiangrong2023@163.com;mgl@njust.edu.cn。

Inverse kinematics solution of snake-arm robot based on progressive BP neural network

XU Xiangrong1, MA Guoliang1, XU Lisong2, WANG Tianya1   

  1. 1 School of Energy and Power Engineering,Nanjing University of Science and Technology,Nanjing 210094,China;
    2 School of Automation,Nanjing University of Science and Technology,Nanjing 210094,China
  • Received:2024-10-15 Online:2025-09-18 Published:2025-09-23

摘要: 针对传统BP神经网络在求解蛇形机械臂逆运动学问题时的收敛速度慢、误差大等问题,提出一种渐进式BP神经网络逆运动学求解方法。首先,建立正运动学模型;然后,引入最佳柔顺性原则,提出以关节角度变化的加权和作为惩罚项的损失函数,该损失函数充分考虑到机械臂运动过程中关节角度变化的连续性和平稳性;最后,根据蛇形机械臂各关节之间的连接约束,构建一种具有层级渐进结构的BP神经网络模型,提高了求解速度。仿真结果表明,该渐进式BP神经网络精度高、收敛速度快,能有效地求解蛇形机械臂逆运动学问题。

关键词: 蛇形机械臂, 逆运动学, BP神经网络

Abstract: Aiming at the slow convergence and large error issues in solving the inverse kinematics of a snake-arm robot using traditional BP neural networks,a progressive BP neural network inverse kinematics solution was proposed. Firstly,a forward kinematics model was established. Then,the principle of optimal compliance was introduced. A weighted sum of joint angle changes was used as the penalty term in the loss function,ensuring continuity and smoothness of the joint angle changes in the robot′s joint movements. Finally,based on the constraints between the joints of the snake-arm robot,a BP neural network model with a hierarchical progressive structure was constructed to improve the solving speed.Simulation results show that the progressive BP neural network achieves high accuracy and fast convergence,effectively solving the inverse kinematics problem of the snake-arm robot.

Key words: snake-arm robot, inverse kinematics, BP neural network

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