Multilayered Kinodynamics Simulation for Detailed Whole-Body Motion Generation and Analysis

Abstract

This study generates and analyzes unsafe human motions that cannot be measured experimentally in laboratories with dynamic consistency. Detailed whole-body motions are generated by a multilayered kinodynamics simulation (MLKD Sim) that uses a detailed digital whole-body human model and a simple motion-representation model that parametrically represents human motion mechanisms. First, we develop the simple motion-representation model that represents human motions and contact force data that are experimentally measured in a laboratory (deep data), and we identify this model’s parameters based on these deep data. Forward dynamics computation of this motion-representation model with changing model and/or environmental parameters simulates motion modification as well as a contact force with dynamic consistency. Finally, the mapping function from the motion-representation model’s motion to the detailed motion identified from the deep data is used to reconstruct the detailed whole-body motion. MLKD Sim results correspond with the experimentally measured data well. Unsafe motion simulation results imply that when sprinting in an unknown environment, we need to protect, in order, the knee ankle, and hip joints. This study conducts detailed dynamics and kinematics analysis of unsafe human motions that cannot be measured experimentally in laboratories to prevent injuries, falls, and fatigue, and these results should find applications in the fields of medicine and welfare.