Controller parameter optimization for multiple balance strategies

Full-state feedback parametric controllers are proposed for standing balance of humanoid robots in response to impulsive and constant pushes. We take use of multiple models to approach multiple strategies for standing balance. For each model, we design a controller acting on each state variable and optimize controller parameters for different push sizes, directions and locations. We show the performance of multiple models with optimized parametric controllers in response to different external pushes. By comparing the capabilities of handling disturbances, each joint contributions to standing balance are also explored.