Niklas Funk

Niklas Funk joined the Institute for Intelligent Autonomous Systems (IAS) at TU Darmstadt in September 2020 as a Ph.D. student.

Previously, 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.

Research Interests

Reinforcement Learning, Control, Robotics

Key References

Reinforcement Learning and Combinatorial Optimization for Robotic Assembly

• Funk, N.; Chalvatzaki, G.; Belousov, B.; Peters, J. (2021). Learn2Assemble with Structured Representations and Search for Robotic Architectural Construction, Conference on Robot Learning (CoRL).   Download Article [PDF]   BibTeX Reference [BibTex]
• Wibranek, B.; Liu, Y.; Funk, N.; Belousov, B.; Peters, J.; Tessmann, O. (2021). Reinforcement Learning for Sequential Assembly of SL-Blocks: Self-Interlocking Combinatorial Design Based on Machine Learning, Proceedings of the 39th eCAADe Conference.   Download Article [PDF]   BibTeX Reference [BibTex]

Dexterous Manipulation

• Funk, N.; Schaff, C.; Madan, R.; Yoneda, T.; Urain, J.; Watson, J.; Gordon, E.; Widmaier, F; Bauer, S.; Srinivasa, S.; Bhattacharjee, T.; Walter, M.; Peters, J. (submitted). Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation, IEEE Robotics and Automation Letters.   Download Article [PDF]   BibTeX Reference [BibTex]

Event-triggered Control

• Funk, N.; Baumann, D.; Berenz, V.; Trimpe, S. (2021). Learning event-triggered control from data through joint optimization, IFAC Journal of Systems and Control, 16, pp.100144.   Download Article [PDF]   BibTeX Reference [BibTex]

Supervised Theses and Projects

• MS Thesis (co-supervised with Boris Belousov), Frederik Wegner, Learning Vision-Based Tactile Representations for Robotic Architectural Assembly
• RL:IP'20w (with Belousov, B.; Chalvatzaki, G.), Jan Emrich, Simon Kiefhaber, Probabilistic Object Tracking Using Depth Carmera
• RL:IP'20w-21s (with Belousov, B.; Chalvatzaki, G.), Leon Magnus, Svenja Menzenbach, Max Siebenborn, Object Tracking for Robotic Assembly
• RL:IP'20w (Belousov, B.; Chalvatzaki, G.;Wibranek, B.), Jan Schneider, Architectural Assembly: Simulation and Optimization