Master Thesis on the Co-Adaptation of Robots

The goal of this Master thesis is to develop simulation tools necessary to evaluate co-adaptation techniques, and to develop new approaches for learning the behaviour and design of robots using deep learning and deep reinforcement learning.

Master Thesis on “Safe Constrained Differential Dynamic Programming”

In this thesis, an extensive investigation of constrained DDP methods will be performed and the major selected ones will be implemented in simulation environment for trajectory optimizations of different robots such as a simple point robot, 2D car-like robot, 3D quadrotor robot and cart-pole system. In this context, the methods will be compared in terms of convergence speed, computational complexity, sensitivity to initializations and parameter selections.