Learning Control Policies from Optimal Trajectories
Christoph Zelch,Jan Peters,Oskar von Stryk,Christoph Zelch,Jan Peters,Oskar von Stryk
The ability to optimally control robotic systems offers significant advantages for their performance. While time-dependent optimal trajectories can numerically be computed for high dimensional nonlinear system dynamic models, constraints and objectives, finding optimal feedback control policies for such systems is hard. This is unfortunate, as without a policy, the control of real-world systems re...
