Advanced AI - Mechanics & Control

 The overall goal of the Mechanics and Control team is to

Develop dynamic robots that can move and interact in the real world with a grace, agility, and robustness similar to that of humans and animals.

In the field of mechanics, this includes investigating novel principles for robot design, such as parallel and compliant or flexible mechanisms, along with a rigorous analysis and mathematical modeling in terms of geometry, kinematics, and dynamics. To achieve this, we aim to develop a thorough understanding of the way how dynamic robots interact with their environment and produce realistic and computationally manageable models of this interaction, for example, considering extreme impact forces, friction, and slip.

In the field of control, we are equally interested in predicting the robot’s state from incomplete and noisy sensor data, as well as in planning and stabilizing dynamic movements in real-world contexts, such as walking, running, jumping, and brachiating. Thereby we exploit both model-based (optimal control, hybrid optimization, whole-body control) and learning-based (RL, data-driven) approaches, as well as combinations of both. Underactuated robots such as quadrupeds and humanoids are particularly interesting in this means as they are challenging to control due to their hybrid dynamics.

Team lead: Dr.-Ing. Dennis Mronga
Deputy: Dr. Melya Boukheddimi