Masters Thesis: Predictive Modeling for Smooth Handover Point Estimation

11.07.2024, Abschlussarbeiten, Bachelor- und Masterarbeiten

Are you interested in leveraging machine learning to create intelligent robotics systems as part of the MITI research group at the Klinikum rechts der Isar?

Background: The effective and efficient transfer of medical materials is an integral part in healthcare environments, where timely and accurate handovers can impact the attention and cognitive load of staff.

Be part of the research project TUM4HealthTech, with the aim of optimizing existing processes in the inpatient clinical area through a comprehensive integration of innovative technologies to relieve the staff. The project is a cooperation between the MITI research group at the University clinic and the fml chair (Fördertechnik Materialfluss Logistik).

Scope of the thesis: This thesis aims to develop a predictive modeling approach to optimize the handover point estimation based on RGB(D) data. The first step will be to create a suitable dataset to approximate the situation. By leveraging machine learning and data analytics, this research seeks to predict the optimal handover position, ensuring a smoother and more reliable transfer of medical materials.

Requirements:
• Currently studying for a master’s degree in a technical program
• Previous experience implementing machine learning algorithms with common libraries
• Strong Experience with Python and Computer Vision
• Interest in robotic applications and Human-Robot-Interaction
• Structured, independent, and careful way of working
• Good knowledge of German and / or English

If you have become curious and would like to write your thesis with us, then apply to us with your CV and proof of grades (Bachelor's and, if applicable, Master's) a short introduction with your interests and previous experiences would be appreciated.

Kontakt: sonja.stabenow@tum.de

Mehr Information

https://web.med.tum.de/miti/startseite/