Automatic task-specific model reduction for humanoid robots

Simple inverted pendulum models and their variants are often used to control humanoid robots in order to simplify the control design process. These simple models have significantly fewer degrees of freedom than the full robot model. The design and choice of these simple models are based on the designer's intuition, and the reduced state mapping and the control input mapping are manually chosen. This paper presents an automatic model reduction procedure for humanoid robots, which is task-specific. It also presents an optimization framework that uses the auto-generated task-specific reduced models to control humanoid robots. Successful simulation results of balancing, fast arm swing, and hip rock and roll motion tasks are demonstrated.