Quadrupedal Locomotion via Event-Based Predictive Control and QP-Based Virtual Constraints
This work addresses the challenge of efficient and stable locomotion for quadrupedal robots, particularly in dynamic environments, though it appears incremental by building on existing MPC and virtual constraint methods.
The paper tackled real-time locomotion control for quadrupedal robots by developing a hierarchical nonlinear control algorithm combining event-based MPC and QP-based virtual constraints, resulting in significantly reduced computational burden and robust performance in full-order simulations of a 22-degree-of-freedom robot.
This paper aims to develop a hierarchical nonlinear control algorithm, based on model predictive control (MPC), quadratic programming (QP), and virtual constraints, to generate and stabilize locomotion patterns in a real-time manner for dynamical models of quadrupedal robots. The higher level of the proposed control scheme is developed based on an event-based MPC that computes the optimal center of mass (COM) trajectories for a reduced-order linear inverted pendulum (LIP) model subject to the feasibility of the net ground reaction force (GRF). The asymptotic stability of the desired target point for the reduced-order model under the event-based MPC approach is investigated. It is shown that the event-based nature of the proposed MPC approach can significantly reduce the computational burden associated with the real-time implementation of MPC techniques. To bridge the gap between reduced- and full-order models, QP-based virtual constraint controllers are developed at the lower level of the proposed control scheme to impose the full-order dynamics to track the optimal trajectories while having all individual GRFs in the friction cone. The analytical results of the paper are numerically confirmed on full-order simulation models of a 22 degree of freedom quadrupedal robot, Vision 60, that is augmented by a robotic manipulator. The paper numerically investigates the robustness of the proposed control algorithm against different contact models.