Sensitivity of Legged Balance Control to Uncertainties and Sampling Period
This addresses robustness in balance control for legged robots like bipeds and quadrupeds, but is incremental as it applies existing robust control theory to a specific problem.
The study quantified the effect of sensor and actuator uncertainties on balance control in legged robots, finding that sampling periods up to 200 ms had no impact on maximum tracking error or safety guarantees.
We propose to quantify the effect of sensor and actuator uncertainties on the control of the center of mass and center of pressure in legged robots, since this is central for maintaining their balance with a limited support polygon. Our approach is based on robust control theory, considering uncertainties that can take any value between specified bounds. This provides a principled approach to deciding optimal feedback gains. Surprisingly, our main observation is that the sampling period can be as long as 200 ms with literally no impact on maximum tracking error and, as a result, on the guarantee that balance can be maintained safely. Our findings are validated in simulations and experiments with the torque-controlled humanoid robot Toro developed at DLR. The proposed mathematical derivations and results apply nevertheless equally to biped and quadruped robots.