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Human Motion Simulation
Predictive Dynamics
1st Edition - May 30, 2013
Authors: Karim Abdel-Malek, Jasbir Singh Arora
Hardback ISBN:
9 7 8 - 0 - 1 2 - 4 0 5 1 9 0 - 4
eBook ISBN:
9 7 8 - 0 - 1 2 - 4 0 4 6 0 1 - 6
Simulate realistic human motion in a virtual world with an optimization-based approach to motion prediction. With this approach, motion is governed by human performance measures,… Read more
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Simulate realistic human motion in a virtual world with an optimization-based approach to motion prediction. With this approach, motion is governed by human performance measures, such as speed and energy, which act as objective functions to be optimized. Constraints on joint torques and angles are imposed quite easily. Predicting motion in this way allows one to use avatars to study how and why humans move the way they do, given specific scenarios. It also enables avatars to react to infinitely many scenarios with substantial autonomy. With this approach it is possible to predict dynamic motion without having to integrate equations of motion -- rather than solving equations of motion, this approach solves for a continuous time-dependent curve characterizing joint variables (also called joint profiles) for every degree of freedom.
- Introduces rigorous mathematical methods for digital human modelling and simulation
- Focuses on understanding and representing spatial relationships (3D) of biomechanics
- Develops an innovative optimization-based approach to predicting human movement
- Extensively illustrated with 3D images of simulated human motion (full color in the ebook version)
Students in advanced biomechanics courses, kinesiology, exercise science, human motion, etc. A reference for professionals studying human movements, such as biomechanists, motor behaviorists, ergonomists, safety equipment designers, and rehabilitation specialists
Dedication
Preface
Acknowledgments
Current Faculty and Staff
Current Students
Past Students and Collaborators
Past Summer Interns
Visiting Faculty and Scientists
Chapter 1. Introduction
1.1 What is predictive dynamics?
1.2 How does predictive dynamics work?
1.3 Why data-driven human motion prediction does not work
1.4 Concluding remarks
References
Chapter 2. Human Modeling: Kinematics
2.1 Introduction
2.2 General rigid body displacement
2.3 Concept of extended vectors and homogeneous coordinates
2.4 Basic transformations
2.5 Composite transformations
2.6 Directed transformation graphs
2.7 Determining the position of a multi-segmental link: forward kinematics
2.8 The Denavit–Hartenberg representation
2.9 The kinematic skeleton
2.10 Establishing coordinate systems
2.11 The Santos® model
2.12 Variations in anthropometry
2.13 A 55-DOF whole body model
2.14 Global DOFs and virtual joints
2.15 Concluding remarks
References
Chapter 3. Posture Prediction and Optimization
3.1 What is optimization?
3.2 What is posture prediction?
3.3 Inducing behavior
3.4 Posture prediction versus inverse kinematics
3.5 Optimization-based posture prediction
3.6 A 3-DOF arm example
3.7 Development of human performance measures
3.8 Motion between two points
3.9 Joint profiles as B-spline curves
3.10 Motion prediction formulation
3.11 A 15-DOF motion prediction
3.12 Optimization algorithm
3.13 Motion prediction of a 15-DOF model
3.14 Multi-objective problem statement
3.15 Design variables and constraints
3.16 Concluding remarks
References
Chapter 4. Recursive Dynamics
4.1 Introduction
4.2 General static torque
4.3 Dynamic equations of motion
4.4 Formulation of regular Lagrangian equation
4.5 Recursive Lagrangian equations
4.6 Examples using a 2-DOF arm
4.7 Trajectory planning example
4.8 Arm lifting motion with load example
4.9 Concluding remarks
References
Chapter 5. Predictive Dynamics
5.1 Introduction
5.2 Problem formulation
5.3 Dynamic stability: zero-moment point
5.4 Performance measures
5.5 Inner optimization
5.6 Constraints
5.7 Types of constraints
5.8 Discretization and scaling
5.9 Numerical example: single pendulum
5.10 Example formulations
5.11 Concluding remarks
References
Chapter 6. Strength and Fatigue: Experiments and Modeling
6.1 Joint space
6.2 Strength influences
6.3 Strength assessment
6.4 Normative strength data
6.5 Representing strength percentiles
6.6 Mapping strength to digital humans: strength surfaces
6.7 Fatigue
6.8 Strength and fatigue interaction
6.9 Concluding remarks
References
Chapter 7. Predicting the Biomechanics of Walking
7.1 Introduction
7.2 Joints as degrees of freedom (DOF)
7.3 Muscle versus joint space
7.4 Spatial kinematics model
7.5 Dynamics formulation
7.6 Gait model
7.7 Zero-Moment point (ZMP)
7.8 Calculating ground reaction forces (GRF)
7.9 Optimization formulation
7.10 Numerical discretization
7.11 Example: predicting the gait
7.12 Cause and effect
7.13 Implementations of the predictive dynamics walking formulation
7.14 Concluding remarks
References
Chapter 8. Predictive Dynamics: Lifting
8.1 Human skeletal model
8.2 Equations of motion and sensitivities
8.3 Dynamic stability and ground reaction forces (GRF)
8.4 Formulation
8.5 Predictive dynamics optimization formulation
8.6 Computational procedure for multi-objective optimization
8.7 Predictive dynamics simulation
8.8 Validation
8.9 Concluding remarks
References
Chapter 9. Validation of Predictive Dynamics Tasks
9.1 Introduction
9.2 Motion determinants
9.3 Motion capture systems
9.4 Methods
9.5 Validation of predictive walking task
9.6 Validation of box-lifting task
9.7 Feedback to the simulation
9.8 Concluding remarks
References
Chapter 10. Concluding Remarks
10.1 Benefits of predictive dynamics
10.2 Applications
10.3 Future research
Reference
Bibliography
Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Chapter 8
Chapter 9
Chapter 10
Index
- No. of pages: 288
- Language: English
- Published: May 30, 2013
- Imprint: Academic Press
- Hardback ISBN: 9780124051904
- eBook ISBN: 9780124046016
KA
Karim Abdel-Malek
Karim Abdel-Malek is a professor in the Department of Biomedical Engineering and the Department of Mechanical and Industrial Engineering at the University of Iowa. He obtained his PhD in Mechanical Engineering from the University of Pennsylvania. Dr. Abdel-Malek is the Founder and Director of the Virtual Soldier Research (VSR) program; Director of the Center for Computer Aided Design; former Associate Editor of the International Journal of Robotics and Automation; former Editor-in-Chief of the International Journal of Human Factors Modeling & Simulation; and a Fellow of the American Institute for Medical and Biological Engineering (AIMBE).
Affiliations and expertise
Professor of Biomedical Engineering and Mechanical & Industrial Engineering, University of IowaJA
Jasbir Singh Arora
Dr. Arora is the F. Wendell Miller Distinguished Professor, Emeritus, of Civil, Environmental and Mechanical Engineering at the University of Iowa. He was also Director of the Optimal Design Laboratory and Associate Director of the Center for Computer Aided Design. He is an internationally recognized expert in the fields of optimization, numerical analysis, and real-time implementation. His research interests include optimization-based digital human modeling, dynamic response optimization, optimal control of systems, design sensitivity analysis and optimization of nonlinear systems, and parallel optimization algorithms. Dr. Arora has authored two books, co-authored or edited five others, written 160 journal articles, 27 book chapters, 130 conference papers, and more than 300 technical reports.
Affiliations and expertise
Department of Civil and Environmental Engineering & Department of Mechanical Engineering, University of Iowa