Autonomously Extracting Robot-Internal Information for Explanations

Scope

Our research group works at the intersection of Artificial Intelligence and Robotics, focusing on making autonomous robots more transparent and understandable. We are exploring how Foundation Models can be used to generate explanations for robot behavior by combining robot-internal information (such as sensor data, trajectories, and logs) with explainable AI (xAI) techniques.

Tasks

• Development and implementation of robotic manipulation tasks (in simulation or on real robots).
• Integration of learned models for perception and control.
• Assisting in implementing and testing xAI techniques and connecting them to Foundation Models.

Requirements

• Solid knowledge base and experience in deep learning, and robotics.
• Coding skills in Python. Experience with Foundation Models and robot simulation is a plus.
• Knowledge of xAI is beneficial.

What we offer

• An exciting role in a dynamic research environment.
• The chance to work with state-of-the-art robotics and AI technologies.
• Close collaboration with supervisors.
• The opportunity to gain valuable research experience in AI & Robotics.