Thesis in the Field of Humanoid Robots & AI - Different Focus Topics

Job description

At the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, we turn the latest scientific findings into technical innovations, and in doing so contribute to shaping the future. With your thesis, you will support our Human-AI Interaction team and work on practice-oriented projects carried out in cooperation with industry or research partners. This allows you to apply your theoretical knowledge directly in practice. In our research group, we develop complex experimental setups and demonstrators to test humanoid robots in human-centered environments. We are looking for students to support our team for six months, starting immediately. Just a ten-minute walk from KIT Campus South, your chance awaits to become part of our renowned research institution. We offer five focus topics. Choose yours: Multi-Agent Orchestration for Humanoid Robots: coordinate and localize multiple humanoid robots Sim-to-Real Transfer for Humanoid Robots: transfer behavior trained in simulation to the real robot Imitation Learning for Humanoid Robots: robots learn fetch-and-carry tasks by imitating human demonstrations Teleoperated Monitoring with a Humanoid Robot: control and monitor a humanoid robot remotely Human-AI Interaction Harness for Humanoid Robots in Care: a runtime environment that allows AI agents to use robots and sensors safely in care settings Sounds exciting? Then apply now and state in your application which focus topic interests you most. In the interview, we will discuss the topic and direction of your thesis together. Be part of change Your tasks depend on the chosen focus topic: 1. Multi-Agent Orchestration for Humanoid Robots Research and design of a multi-agent orchestration architecture for humanoid robots in buildings Development of strategies for distributed localization and orientation (e.g., sensor fusion, RTLS integration) Implementation of a prototype for coordinating multiple agents/robots in a building Evaluation of localization accuracy, robustness, and scalability 2. Sim-to-Real Transfer for Humanoid Robots Setup of a simulation environment for tool-fetching tasks (e.g., in Isaac Sim) Implementation of reinforcement learning policies for grasping and transport manipulation in simulation Application of domain randomization and transfer strategies (sim-to-real) Validation of the trained policies on the real humanoid robot and documentation of the transfer 3. Imitation Learning for Humanoid Robots Collection and preparation of demonstration data for tool-fetching tasks (e.g., via teleoperation or kinematic recording) Implementation and training of an imitation learning model to reproduce human fetch-and-carry manipulations Evaluation of generalization to different tools and placement locations Testing on the humanoid robot and documentation of the results 4. Teleoperated Monitoring with a Humanoid Robot Design and implementation of a teleoperation control pipeline for a humanoid robot Development of methods for visualizing sensor and environment data for the operator Testing of low-latency control in human-centered environments (e.g., elevator buttons, doors, corridors) Evaluation of the suitability of teleoperated monitoring in terms of reaction time and situational awareness 5. Human-AI Interaction Harness for Humanoid Robots in Care Design of a generic runtime environment (harness) for AI agents in care scenarios Unified integration of tools and information sources (cameras, sensors, RTLS, HMI systems, robots) Management of context and world state (states of people, objects, and machines) for care activities Implementation of authorization and verification mechanisms for safe action execution Prototypical implementation using the example of "moving hospital beds" and documentation What you contribute You are enrolled at a university or university of applied sciences and study computer science, robotics, mechanical engineering, software engineering, or a comparable field Basic knowledge of Python (ideally with PyTorch) and/or C++ Familiarity with ROS2 Depending on the focus topic, an advantage: experience with simulation and reinforcement learning, e.g., Isaac Sim (sim-to-real), C++ (teleoperation), interest in AI agents and multi-agent systems (orchestration, harness), or in learning-based methods (imitation learning) You enjoy programming and like to learn new things You bring scientific curiosity and enjoy professional discussions and exchange Good German and English skills What we offer Central location: Only a few minutes' walk from KIT Campus South and excellent public transport connections. Flexible working hours: Your studies come first, and we will find the right arrangement together. Flexible working: Remote work is possible by individual arrangement with your supervisor. Practice-oriented projects: Collaboration with industry partners and application of research results in humanoid robotics. Individual supervision: Benefit from our professional guidance and open, communicative exchange within the team. Exciting tasks and room for ideas: A high degree of personal responsibility and the opportunity to actively contribute your own ideas. We value and promote the diversity of our employees' skills and therefore welcome all applications – regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability. Our tasks are diverse and adaptable – for applicants with disabilities, we work together to find solutions that best promote their abilities. With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future. Ready for a change? Then apply now and make a difference! Once we have received your online application, you will receive an automatic confirmation of receipt. We will then get back to you as soon as possible and let you know what happens next. If you have any questions, please contact: David Lerch +49 160 1112937 Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB Requisition Number: 85807 Application Deadline: