8 research outputs found
Sensitivity of Legged Balance Control to Uncertainties and Sampling Period
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 torquecontrolled humanoid robot Toro developed at DLR. The proposed
mathematical derivations and results apply nevertheless equally
to biped and quadruped robots
Sensitivity of Legged Balance Control to Uncertainties and Sampling Period
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 torquecontrolled humanoid robot Toro developed at DLR. The proposed
mathematical derivations and results apply nevertheless equally
to biped and quadruped robots