Control Systems

Control systems translate decisions into motion. Sitting between high-level planners (“go pick that up”) and low-level actuators (motors and joints), they ensure that every movement is stable, safe, and physically achievable.

Classic robots followed predefined motion trajectories using PID loops. But humanoids operate in messier conditions: slippery floors, variable contact, shifting payloads. Today’s systems blend model-predictive control (MPC) with learned policies, allowing them to adapt in real time.Researchers are exploring neural feedback controllers trained in simulation and fine-tuned on hardware aiming for resilience, precision, and rapid recovery from disturbance. The frontier lies in closed-loop stacks, where perception, planning, and execution constantly inform one another. This integration is essential for humanoids to move fluidly and safely in complex environments.