Feature-Based Locomotion Controllers

摘要

This paper introduces an approach to control of physics-based char-acters based on high-level features of movement, such as center-of-mass, angular momentum, and end-effectors. Objective terms are used to control each feature, and are combined by a prioriti-zation algorithm. We show how locomotion can be expressed in terms of a small number of features that control balance and end-effectors. This approach is used to build controllers for human balancing, standing jump, and walking. These controllers provide numerous benefits: human-like qualities such as arm-swing, heel-off, and hip-shoulder counter-rotation emerge automatically during walking; controllers are robust to changes in body parameters; con-trol parameters and goals may be modified at run-time; control pa-rameters apply to intuitive properties such as center-of-mass height; and controllers may be mapped onto entirely new bipeds with dif-ferent topology and mass distribution, without modifications to the controller itself. No motion capture or off-line optimization process is used.