Capturability-based Pattern Generation for Walking with Variable Height
This work addresses the challenge of robust bipedal locomotion on uneven surfaces for robotics applications, representing an incremental advancement by extending existing capturability concepts to variable height.
The authors tackled the problem of enabling 3D walking over uneven terrains by generalizing capturability analysis from the linear inverted pendulum to the variable-height inverted pendulum, resulting in a method that computes capture inputs fast enough for real-time model predictive control and is demonstrated in dynamic simulations.
Capturability analysis of the linear inverted pendulum (LIP) model enabled walking with constrained height based on the capture point. We generalize this analysis to the variable-height inverted pendulum (VHIP) and show how it enables 3D walking over uneven terrains based on capture inputs. Thanks to a tailored optimization scheme, we can compute these inputs fast enough for real-time model predictive control. We implement this approach as open-source software and demonstrate it in dynamic simulations.