Neural network for dynamic human motion prediction

Successful use of artificial neural network (ANN) to simulate human model motion.Experimentation results of using ANN to simulate the tasks of walking and jumping.The use of ANN reduces the simulation time from 1-40?min to a fraction of a second. Digital human models (DHMs) are critical for improved designs, injury prevention, and a better understanding of human behavior. Although many capabilities in the field are maturing, there are still opportunities for improvement, especially in motion prediction. Thus, this work investigates the use of an artificial neural network (ANN), specifically a general regression neural network (GRNN), to provide real-time computation of DHM motion prediction, where the underlying optimization problems are large and computationally complex. In initial experimentation, a GRNN is used successfully to simulate walking and jumping on a box while using physics-based human simulations as training data. Compared to direct computational simulations of dynamic motion, use of GRNN reduces the calculation time for each predicted motion from 1-40?min to a fraction of a second with no noticeable reduction in accuracy. This work lays the foundation for studying the effects of changes to training regiments on human performance.

[1]  Ghassan AlRegib,et al.  Neural Networks for Human Arm Movement Prediction in CVEs , 2008 .

[2]  Imre Horváth,et al.  Using artificial neural networks for human body posture prediction , 2010 .

[3]  Yujiang Xiang,et al.  Physics-based modeling and simulation of human walking: a review of optimization-based and other approaches , 2010 .

[4]  Don B. Chaffin,et al.  On simulating human reach motions for ergonomics analyses , 2002 .

[5]  Joo H. Kim,et al.  Predictive dynamics: an optimization-based novel approach for human motion simulation , 2010 .

[6]  Toshio Tsuji,et al.  A Hybrid Motion Classification Approach for EMG-Based Human–Robot Interfaces Using Bayesian and Neural Networks , 2009, IEEE Transactions on Robotics.

[7]  Karim Abdel-Malek,et al.  Development of the Virtual-Human SantosTM , 2007, HCI.

[8]  Yujiang Xiang,et al.  Dynamic motion planning of overarm throw for a biped human multibody system , 2010 .

[9]  J. Jaldén,et al.  On using an adaptive neural network to predict lung tumor motion during respiration for radiotherapy applications. , 2005, Medical physics.

[10]  Alice E. Smith,et al.  Bias and variance of validation methods for function approximation neural networks under conditions of sparse data , 1998, IEEE Trans. Syst. Man Cybern. Part C.

[11]  Yujiang Xiang,et al.  Optimization‐based dynamic human walking prediction: One step formulation , 2009 .

[12]  Sarangapani Jagannathan,et al.  Neural Network Output Feedback Control of Robot Formations , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[13]  Adrian Hilton,et al.  A survey of advances in vision-based human motion capture and analysis , 2006, Comput. Vis. Image Underst..

[14]  Neil Davey,et al.  Time Series Prediction and Neural Networks , 2001, J. Intell. Robotic Syst..

[15]  Joo Hyun Kim,et al.  Efficient ZMP Formulation and Effective Whole-Body Motion Generation for a Human-Like Mechanism , 2008 .

[16]  Philip D. Wasserman,et al.  Advanced methods in neural computing , 1993, VNR computer library.

[17]  Yujiang Xiang,et al.  A validation framework for predictive human models , 2011 .

[18]  Eui S. Jung,et al.  Prediction of human reach posture using a neural network for ergonomic man models , 1994 .

[19]  Yujiang Xiang,et al.  Backward walking simulation of humans using optimization , 2014 .

[20]  Mohammad Hindi Bataineh,et al.  New Neural Network for Real-Time Human Dynamic Motion Prediction , 2016 .

[21]  David W. Coit,et al.  STATIC NEURAL NETWORK PROCESS MODELS : CONSIDERATIONS AND CASE STUDIES , 1998 .

[22]  Karim Abdel-Malek,et al.  Artificial Neural Network-Based Prediction of Human Posture , 2013, HCI.

[23]  Frank L. Lewis,et al.  Neural network output feedback control of robot manipulators , 1999, IEEE Trans. Robotics Autom..

[24]  Donald F. Specht,et al.  A general regression neural network , 1991, IEEE Trans. Neural Networks.

[25]  Mohammad Hindi Bataineh.  Artificial neural network for studying human performance , 2013 .

[26]  Guolei Zheng,et al.  Human-machine posture prediction and working efficiency evaluation of virtual human using radial basis function neural network , 2010, 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems.

[27]  Chris Murphy,et al.  Santos: A Physics-Based Digital Human Simulation Environment , 2006 .

[28]  M. Nixon,et al.  Automated Human Recognition by Gait using Neural Network , 2008, 2008 First Workshops on Image Processing Theory, Tools and Applications.

[29]  Yujiang Xiang,et al.  Hybrid predictive dynamics: a new approach to simulate human motion , 2012 .

[30]  J. Arora,et al.  Human lifting simulation using a multi-objective optimization approach , 2010 .

[31]  Shinsuk Park,et al.  Modeling of Artificial Neural Network for the Prediction of the Multi-Joint Stiffness in Dynamic Condition , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[32]  Caihong Li,et al.  A new hybrid algorithm of dynamic obstacle avoidance based on dynamic rolling planning and RBFNN , 2007, 2007 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[33]  Devendra K. Chaturvedi.  Modeling with Artificial Neural Network , 2017 .