Imitation Learning from MPC for Quadrupedal Multi-Gait Control

Understand

We present a learning algorithm for training a single policy that imitates multiple gaits of a walking robot.

• To achieve this, we use and extend MPC-Net, which is an Imitation Learning approach guided by Model Predictive Control (MPC).
• The strategy of MPC-Net differs from many other approaches since its objective is to minimize the control Hamiltonian, which derives from the principle of optimality.
• To represent the policies, we employ a mixture-of-experts network (MEN) and observe that the performance of a policy improves if each expert of a MEN specializes in controlling exactly one mode of a hybrid system, such as a walking robot.