Human Motion Simulation: Predictive DynamicsSimulate 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.
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Contents
| 1 | |
| 7 | |
3 Posture Prediction and Optimization | 41 |
4 Recursive Dynamics | 69 |
5 Predictive Dynamics | 95 |
Experiments and Modeling | 127 |
7 Predicting the Biomechanics of Walking | 149 |
Other editions - View all
Human Motion Simulation: Predictive Dynamics Karim Abdel-Malek,Jasbir Arora No preview available - 2013 |
Human Motion Simulation: Predictive Dynamics Karim Abdel-Malek,Jasbir Arora No preview available - 2013 |
Common terms and phrases
Abdel-Malek algorithm analysis ankle anthropometry approach Arora B-spline benchmark test Biomech biomechanics biped box-lifting calculated chapter computational constraints coordinate system cost functions curve defined design variables determinants Digital Human Modeling eccentric contractions end-effector equations of motion Ergonomics fatigue flexion foot Frey-Law gait cycle global human motion human walking IEEE initial and final inverse dynamics inverse kinematics joint angle joint displacement joint limits joint profiles joint torques key frames knee knot vector lifting motion Marler method minimizing motion capture motion prediction multi-objective optimization muscle Nebel nonlinear normal objective function obtained optimization problem Paper presented parameters position posture prediction potential energy predictive dynamics Rahmatalla recursive represent resultant active forces rotation segmental links shoulder shown in Figure SNOPT strength surfaces subjects task tion trajectories transformation matrix University of Iowa upper validation vector velocity virtual Walking Cycle walking motion Xiang