An Input-to-State Stability Perspective on Robust Locomotion
Tucker, Maegan, Ames, Aaron D.
–arXiv.org Artificial Intelligence
Uneven terrain necessarily transforms periodic walking into a non-periodic motion. As such, traditional stability analysis tools no longer adequately capture the ability of a bipedal robot to locomote in the presence of such disturbances. This motivates the need for analytical tools aimed at generalized notions of stability -- robustness. Towards this, we propose a novel definition of robustness, termed \emph{$\delta$-robustness}, to characterize the domain on which a nominal periodic orbit remains stable despite uncertain terrain. This definition is derived by treating perturbations in ground height as disturbances in the context of the input-to-state-stability (ISS) of the extended Poincar\'{e} map associated with a periodic orbit. The main theoretic result is the formulation of robust Lyapunov functions that certify $\delta$-robustness of periodic orbits. This yields an optimization framework for verifying $\delta$-robustness, which is demonstrated in simulation with a bipedal robot walking on uneven terrain.
arXiv.org Artificial Intelligence
Jun-8-2023
- Country:
- North America > United States > California > Los Angeles County > Pasadena (0.04)
- Genre:
- Research Report (0.64)
- Technology:
- Information Technology > Artificial Intelligence > Robots > Locomotion (1.00)