Towards principled algorithms for stochastic optimal control of nonlinear mechanical systems
Nowadays, achieving efficient computations of optimal trajectories for robotic systems represents a hard problem. In particular, the presence of nonlinearities and uncertainties affecting the outcome makes this task very challenging.
With the objective of introducing optimal control strategies that address those difficulties, in this talk Dr Bonalli will discuss a framework based on Sequential Convex Programming (SCP), from both theoretical and numerical perspectives.
First, he will detail the operating principle of SCP under deterministic settings, allowing to satisfactorily handle nonlinearities. Then, he will show how this framework may be molded to additionally cope with uncertainties.