Computationally-Robust and Efficient Prioritized Whole-Body Controller with Contact Constraints
This work addresses the challenge of efficient and robust control for humanoid robots, particularly in dynamic locomotion, but it appears incremental as it builds on existing whole-body control frameworks.
The paper tackled the problem of multi-objective control for humanoid robots by developing a prioritized whole-body controller that improves computational efficiency and robustness, demonstrated through simulation and real experiments on a passive-ankle bipedal robot.
In this paper, we devise methods for the multi- objective control of humanoid robots, a.k.a. prioritized whole- body controllers, that achieve efficiency and robustness in the algorithmic computations. We use a form of whole-body controllers that is very general via incorporating centroidal momentum dynamics, operational task priorities, contact re- action forces, and internal force constraints. First, we achieve efficiency by solving a quadratic program that only involves the floating base dynamics and the reaction forces. Second, we achieve computational robustness by relaxing task accelerations such that they comply with friction cone constraints. Finally, we incorporate methods for smooth contact transitions to enhance the control of dynamic locomotion behaviors. The proposed methods are demonstrated both in simulation and in real experiments using a passive-ankle bipedal robot.