Title: An approach to solving the inverse kinematics problem of virtual human's lower limbs kinematic chain

Authors: Gangfeng Deng; Xianxiang Huang; Qinhe Gao; Quanmin Zhu; Zhili Zhang; Ying Zhan

Addresses: Xi'an Research Institute of High Technology, Xi'an City, Shaan Xi Province, 710025, China ' Xi'an Research Institute of High Technology, Xi'an City, Shaan Xi Province, 710025, China ' Xi'an Research Institute of High Technology, Xi'an City, Shaan Xi Province, 710025, China ' Xi'an Research Institute of High Technology, Xi'an City, Shaan Xi Province, 710025, China ' Xi'an Research Institute of High Technology, Xi'an City, Shaan Xi Province, 710025, China ' Xi'an Research Institute of High Technology, Xi'an City, Shaan Xi Province, 710025, China

Abstract: The lower limbs kinematic chain (LLKC) is the important part of human body. It contains two joints with four degrees of freedom (DOF). As it is difficult to compute LLKC's inverse kinematic solution quickly and accurately by using neural network or genetic algorithm (GA) due to its high degree of freedom, we proposed a BP-GA approach by combining BP neural network and GA to resolve it. Firstly, the mathematical model of LLKC was built based on D-H method. Then BP neural network output a local optimal solution, which could be served as an individual of GA initial population. And the searching domain of GA could be determined by local optimal solution. Finally, the high-accuracy solution was searched by using the adaptive GA. The actions of walking, squatting and seated position were simulated and results showed that the precise solution could be calculated efficiently by using the proposed approach with the BP neural network high-speed and GA high-accuracy.

Keywords: lower limbs; kinematic chain; LLKC; inverse kinematics; D-H method; Denavit–Hartenberg; search domain; BP-GA; backpropagation neural networks; genetic algorithms; GAs; virtual human; human actions; walking; squatting; seated position; simulation.

DOI: 10.1504/IJMIC.2014.060009

International Journal of Modelling, Identification and Control, 2014 Vol.21 No.2, pp.160 - 171

Available online: 24 Mar 2014 *

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