An efficient control over human running animation with extension of planar hopper model

Abstract

The most important goal of character animation is to efficiently control the motions of a character. Until now, many techniques have been proposed for human gait animation, and some techniques have been created to control the emotions in gaits such as "tired walking" and "brisk walking" by using parameter interpolation or motion data mapping. Since it is very difficult to automate the control over the emotion of a motion, the emotions of a character model have been generated by creative animators. The paper proposes a human running model based on a one-leg-planar hopper with a self-balancing mechanism. The proposed technique exploits genetic programming to find an optimal movement. We extend the energy minimization technique to generate various motions in accordance with emotional specifications, for instance, "brisk running".