Journal of Guangxi Normal University(Natural Science Edition) ›› 2011, Vol. 29 ›› Issue (2): 125-129.

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Self-organizing Inverse Kinematics Planning for Manipulators Based on Ant Colony Neural Network

ZHU Jing-wei1, RUI Ting1, LI Jue-long2, FANG Hu-sheng1, ZHANG Jin-lin1   

  1. 1.Engineering Institute of Engineering Corps,PLA University of Science and Technology,Nanjing Jiangsu 210007,China;
    2.Managing Office of Coast Defense Engineering Technology,Beijing 100841,China
  • Received:2011-05-05 Published:2018-11-19

Abstract: Ant colony neural network is used to solve self-organizing inverse kinematics planning for manipulators.The neural network training problem is translated into the problem of searching the minimum value of the functionina continuous space by setting the objective function.In the early stage of the algorithm,the sample point set of the motion route is only needed to be obtained for training the neural network,and the inverse kinematics solution is not needed.The algorithm achieves self-organizing manipulator inverse kinematics planning for the neural network.The continuous ant colony algorithm is used to solve the problem of searching the minimum value for the continuous function.Experimental results show that the control algorithm has higher accuracy and convergence speed.

Key words: manipulator, neural network, continuous ant colony algorithm, self-organizing inverse kinematics planning

CLC Number: 

  • TP183
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