Chair of Cyber-Physical-Systems https://validator.w3.org/feed/docs/rss2.html Neural and Probabilistic Robotics Recognition of prior learning Autonomes Industrieroboterlabor der Zukunft (AI-Robot-Lab) Innovationslabor für Automation, Robotik und KI K1-MET P3.3 & P3.4 Active transfer learning with neural networks through human-robot interactions (TRAIN) Digital Underground Mining: Sensorik, KI und IoT für Echtzeitüberwachung und Prozessoptimierung im Untertagebau (MineView) Humanoide Roboter und multimodale Manipulationstechnologien für die industrielle Produktion und Logistik (RoboWork) FFG Project Grant – RoboWork TechFest 2025 IIT Bombay Mrs. Regina Schelch (Secretary) Cynthia Ani Björn Ellensohn, M.Sc. Lange Nacht der Forschung – 24th of May 2024 Unitree Go1 190.018 Introduction to Machine Learning (4SH VU, SS) Julia Schmelz Peyman Kahrizi Multi-modale, taktil-visuelle Robotergreifsysteme für industrielle Anwendungen (MUTAVIA) Statistics XMas 2025 – 12th of Dec 2025 Journal Paper accepted at Minerals Engineering Orbbec Femto – Depth Camera Katharina Binder (Secretary) Ouster 3D LiDAR Prof. Elmar Rueckert (Chair) Dr. Christian Rauch (Deputy Chair) Robot FRANKA EMIKA Panda Journal Paper accepted at Energy Reports Vedant Dave, M.Sc. Sai Puneeth Reddy Gottam, M.Sc. 190.021 Einführung in die Datenmodellierung (4ECTS VU, WS) Nachhaltige Nutzung von Aushubmaterialien des Tief- & Tunnelbaus mithilfe sensorgestützter Technologien (NNATT) 190.015 Applied Machine and Deep Learning (5SH IL, WS) People Team Ing. Konrad Bartsch (Technician) Masterprüfungen MMB / Master’s Exams Journal Paper accepted at Transactions on Machine Learning Research (TMLR) CPS Conveyer Belt M.Sc. Thesis, Real-Time 3D Reconstruction and Rendering of Vision-Language Embeddings Ottronic GmbH Geislinger GmbH AI and Learning in Robotics Journal Paper accepted at Engineering Applications of Artificial Intelligence Conference Paper Accepted at Humanoids 2025 FFG Project Grant – MINEView Guenther Hutter, M.Sc. B.Sc. Thesis of Mr. Maximilian Pettinger: “6D Object Pose Estimation Using Classical and Deep Learning Approaches” Home