- eBook ISBN 9780124046016
- Print ISBN 9780124051904
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.
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.
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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
Chapter 2. Human Modeling: Kinematics
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
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
Chapter 4. Recursive Dynamics