Robotics, Reinforcement Learning, Control
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Niklas Funk
TU Darmstadt, FG IAS,
Hochschulstr. 10, 64289 Darmstadt
Office.
Room E325, Building S2|02
+49-6151-16-25372
niklas.funk@tu-darmstadt.de
Niklas Funk joined the Institute for Intelligent Autonomous Systems (IAS) at TU Darmstadt in September 2020 as a Ph.D. student.
Niklas received his bachelor‘s degree in Electrical Engineering and Information Technology, as well as his master’s degree in Robotics, Systems and Control from ETH Zurich. During his studies, he focused on the intersection between machine learning and control and completed several applied projects. He finished off his masters with the thesis – „Learning Event-triggered Control from Data through Joint Optimization“, which was conducted at the Max-Planck Institute for Intelligent Systems under the supervision of Dominik Baumann and Sebastian Trimpe, and has been awarded with the ETH medal.
Currently, Niklas is working in the broad field of autonomous robotic assembly. On the one hand, he is exploring algorithms enabling combinatorial reasoning and generalization. In particular, his recent research focuses on combining learned graph-based representations with powerful inductive biases and model-based search. On the other hand, he is also interested in developing fine, precise, and dexterous robotic assembly skills, eventually adding tactile feedback.
Reinforcement Learning, Control, Robotics, Graph-based Representations, Tactile Sensing
Year | Type | Together with | Student(s) | Topic |
---|---|---|---|---|
2023 | Integrated Project | Kay Hansel | Max Zimmermann, Marius Zöller, Andranik Aristakesyan | Learn to Play Tangram with Graph-based Reinforcement Learning |
2022 | Master Thesis | Boris Belousov | Paul-Otto Müller | Learning Interpretable Representations for Visuotactile Sensors |
2022 | Master Thesis | Boris Belousov | Xiangyu Xu | Visuotactile Grasping From Human Demonstrations |
2022 | Master Thesis | Sebastian Szelag | Multi-Agent Reinforcement Learning for Assembly | |
2022 | Integrated Project | Kay Hansel | Max Zimmermann, Dominik Marino, Maximilian Langer | Learn to Play Tangram with Graph-based Reinforcement Learning |
2022 | Integrated Project | Kay Hansel | Maximilian Langer | Learn to Play Tangram with Graph-based Reinforcement Learning |
2022 | Master Thesis | Georgia Chalvatzaki | Simon Kiefhaber | Leveraging Energy-Based Models for Multi-Object 6D Pose Estimation |
2022 | Bachelor Thesis | Pascal Klink | Leon Magnus | Real-time Object Tracking for Assembly |
2022 | Bachelor Thesis | Svenja Menzenbach | Leveraging Learned Graph-based Heuristics for efficiently solving the Combinatorics of Assembly | |
2021 | Master Thesis | Boris Belousov | Frederik Wegner | Learning Vision-Based Tactile Representations for Robotic Architectural Assembly |
2021 | Integrated Project | Belousov, B.; Chalvatzaki, G. | Jan Emrich, Simon Kiefhaber | Probabilistic Object Tracking Using Depth Carmera |
2021 | Integrated Project | Belousov, B.; Chalvatzaki, G. | Leon Magnus, Svenja Menzenbach, Max Siebenborn | Object Tracking for Robotic Assembly |
2021 | Integrated Project | Belousov, B.; Chalvatzaki, G.; Wibranek, B. | Jan Schneider | Architectural Assembly: Simulation and Optimization |