Human Balancing on a Log: A Switched Multi-Layer Controller

Abstract

We study the task of balancing a human on a log that is fixed in place. Balancing on a log is substantially more challenging than balancing on a flat surface due to increased instability -- nonetheless, we are able to balance by composing simple (e.g., PID, LQR) controllers in a bio-inspired switched multi-layer configuration. The controller consists of an upper-layer LQR planner (akin to the central nervous system) that coordinates ankle and hip torques, and lower-layer PID trackers (akin to local motor units) that follow this plan subject to nonlinear dynamics. The controller switches between three operational modes depending on the state of the human. The efficacy of the controller is verified in simulation, where our controller is able to stabilize the human for a variety of initial conditions and disturbances. We also introduce a controller that outputs muscle activations to perform the same balancing task.