Simulation and Prediction of the Motion of a Human in a Vertical Jumping Task

Abstract

In this work, we offer an optimization based motion prediction of a vertical jumping task for a human. The human model has 55 degrees of freedom. This is a multi-objective optimization problem where the mechanical energy and discomfort are minimized at the same time and an additional motion capture tracking objective function is used to have a more natural motion, specially for less determinant degrees of freedom in the jumping task. The problem is subject to all the Newtonian motion constraints such as ZMP constraint while on the ground and projectile motion constraints for a dynamic system (6 independent constraints that determine the changes in the net linear and angular momentum of the system) while off the ground. In this simulation the height of jump can either be specified by the user or maximized by the optimization module. This simulation is able to predict both the kinematic and dynamic effects of different inputs on the motion where kinematic effects refer to changes in the motion and dynamic effects refer to changes in forces and torques. Different inputs consist of but are not limited to: changes in the human size, mass, strength properties, changes in the mass and inertia of the equipments attached to the human and changes in the height of jump (for specified height jumps).