Balancing and Walking Using Full Dynamics LQR Control With Contact Constraints
This work addresses the challenge of efficient and effective torque control for humanoid robots, offering a simpler alternative to complex controllers, though it is incremental in demonstrating this for specific tasks.
The paper tackled the problem of controlling humanoid robots for balancing and walking tasks by using a simple contact-consistent LQR control approach, showing that it achieves performance competitive with state-of-the-art optimization-based methods without requiring complex algorithms.
Torque control algorithms which consider robot dynamics and contact constraints are important for creating dynamic behaviors for humanoids. As computational power increases, algorithms tend to also increase in complexity. However, it is not clear how much complexity is really required to create controllers which exhibit good performance. In this paper, we study the capabilities of a simple approach based on contact consistent LQR controllers designed around key poses to control various tasks on a humanoid robot. We present extensive experimental results on a hydraulic, torque controlled humanoid performing balancing and stepping tasks. This feedback control approach captures the necessary synergies between the DoFs of the robot to guarantee good control performance. We show that for the considered tasks, it is only necessary to re-linearize the dynamics of the robot at different contact configurations and that increasing the number of LQR controllers along desired trajectories does not improve performance. Our result suggest that very simple controllers can yield good performance competitive with current state of the art, but more complex, optimization-based whole-body controllers. A video of the experiments can be found at https://youtu.be/5T08CNKV1hw.