Extended Capture Point and Optimization-based Control for Quadrupedal Robot Walking on Dynamic Rigid Surfaces
This work addresses the problem of robust locomotion for legged robots on moving surfaces, which is incremental as it builds on existing capture point and control methods.
The study tackled stabilizing quadrupedal robot walking on dynamic rigid surfaces by extending the capture point concept for online motion planning and designing a QP-based feedback controller that explicitly accounts for surface movement. Simulation results validated the approach, showing improved walking performance compared to a previous offline method.
Stabilizing legged robot locomotion on a dynamic rigid surface (DRS) (i.e., rigid surface that moves in the inertial frame) is a complex planning and control problem. The complexity arises due to the hybrid nonlinear walking dynamics subject to explicitly time-varying holonomic constraints caused by the surface movement. The first main contribution of this study is the extension of the capture point from walking on a static surface to locomotion on a DRS as well as the use of the resulting capture point for online motion planning. The second main contribution is a quadratic-programming (QP) based feedback controller design that explicitly considers the DRS movement. The stability and robustness of the proposed control approach are validated through simulations of a quadrupedal robot walking on a DRS with a rocking motion. The simulation results also demonstrate the improved walking performance compared with our previous approach based on offline planning and input-output linearizing control that does not explicitly guarantee the feasibility of ground contact constraints.