Supervised Theses and Projects

• MS Thesis (with Aditya Bhatt), Max Siebenborn, Learning Humanoid Controllers from MPC Experts
• MS Thesis (with Aditya Bhatt), Moritz Meser, Model Predictive Control for Designing Humanoid Skills
• RL'IP24s (with Firas Al-Hafez), Oleg Kaidanov, Yusuf Süvari, Imitation Learning for Humanoid Locomotion
• RL'IP23w-24s, Tim Lukas Faust, Habib Maraqten, Erfan Aghadavoodi, Velocity-History-Based Soft Actor-Critic: Tackling IROS'24 Competition "AI Olympics with RealAIGym"
• MS Thesis (with Niklas Funk), Andranik Aristakesyan, Analyzing Graph Attention
• BS Thesis (with Tim Schneider; Alap Kshirsagar), Duc Huy Nguyen, Simulation of Vision-Based Tactile Sensors
• MS Thesis (with Tim Schneider; Alap Kshirsagar; Gemma Roig), Felix Nonnengießer, Visuotactile Sensing for In-Hand Object Pose Tracking
• BS Thesis (with Tim Schneider; Alap Kshirsagar), Dominik Horstkötter, Learning to Assemble SL-Block Structures from Vision and Touch
• RL'IP23-24s (with Niklas Funk), Erik Helmut, Luca Dziarski, Visuotactile Shear Force Estimation
• RL:IP'23 (with Tim Schneider) Duc Huy Nguyen, TacEx: A Library for Simulating Tactile Sensors in Isaac Orbit
• RL:IP'23s (with Mehrzad Esmaeili), Noah Becker, Zhijingshui Yang, Tool Contact Force Estimation With Visuotactile Sensors for Robot Drawing
• RL:IP'22w (with Tim Schneider; Alap Kshirsagar), Irina Rath, Dominik Horstkötter, Tactile Active Exploration of Object Shapes
• RL:IP'22w (with Tim Schneider; Alap Kshirsagar), Mario Gomez, Frederik Heller, Object Hardness Estimation with Tactile Sensors
• RL:IP'22w (with Tim Schneider; Alap Kshirsagar), Ruben Spari, Duc Huy Nguyen, Simulation of Vision-Based Tactile Sensors
• RL:IP'22w (with Tim Schneider; Yuxi Liu), Paul Hallmann, Nicolas Nonnengießer, Task and Motion Planning for Sequential Assembly
• BS Thesis (with Tim Schneider; Alap Kshirsagar), Alina Böhm, Robotic Tactile Exploratory Procedures for Identifying Object Properties
• MS Thesis (with Niklas Funk; Anton Savchenko), Paul-Otto Müller, Learning Interpretable Representations for Visuotactile Sensors
• MS Thesis (co-supervised with Niklas Funk), Xiangyu Xu, Visuotactile Grasping From Human Demonstrations
• RL:IP'22s (with Mehrzad Esmaeili; Yuxi Liu), Bingqun Liu, A Digital Framework for Interlocking SL-Blocks Assembly with Robots
• RL:IP'22s (with Tim Schneider; Yuxi Liu), Paul Hallmann, Patrick Siebke, Nicolas Nonnengießer, Multi-View Multi-Marker Object Tracking
• BS Thesis (co-supervised with Junning Huang), Max Siebenborn, Evaluating Decision Transformer Architecture on Robot Learning Tasks
• Seminar Humanoid Robotics, Timo Imhof, A Review of the Decision Transformer Architecture
• MS Thesis (co-supervised with Fabio Muratore), Theo Gruner, Wasserstein-Optimal Bayesian System Identification for Domain Randomization
• MS Thesis (co-supervised with Hany Abdulsamad), Tim Schneider, Active Inference for Robotic Manipulation
• MS Thesis (Funk, N.; Calandra, R.), Frederik Wegner, Learning Vision-Based Tactile Representations for Robotic Architectural Assembly
• RL:IP'20w-21s (with Fabio Muratore), Theo Gruner, Arlene Kühn, Florian Wiese, Likelihood-Free Inference for Domain Randomization
• RL:IP'20w (with Funk, N.; Chalvatzaki, G.), Jan Emrich, Simon Kiefhaber, Probabilistic Object Tracking Using Depth Carmera
• RL:IP'20w-21s (with Funk, N.; Chalvatzaki, G.), Leon Magnus, Svenja Menzenbach, Max Siebenborn, Object Tracking for Robotic Assembly
• RL:IP'20w (with Funk, N.; Chalvatzaki, G.;Wibranek, B.), Jan Schneider, Architectural Assembly: Simulation and Optimization
• MS Thesis (co-supervised with Davide Tateo), Jan Rathjens, Accelerated Policy Search
• MS Thesis (with Guoping Zhao), Rustam Galljamov, Sample-Efficient Learning-Based Controller for Bipedal Walking in Robotic Systems
• MS Thesis (co-supervised with Hany Abdulsamad), Tim Dorau, Distributionally Robust Optimization for Optimal Control
• RL:IP'20s (Chalvatzaki, G.; Wibranek, B.), Schneider, J., Schneider, T., Architectural Assembly w/ Tactile Skills: Simulation and Optimization
• RL:IP'20s (Tosatto, S.; Wibranek, B.), Wietschorke, L., Liu, Y., Chen, J. Reinforcement Learning for Architectural Combinatorial Optimization
• MS Thesis (Abdulsamad, H.; Lutter, M.), Markus Semmler, Sequential Bayesian Optimal Experimental Design for Nonlinear Dynamics
• RL:IP'19w (with Michael Lutter), Rustam Galljamov, Searching for a Better Policy Architecture for the OpenAI Bipedal Walker Environment
• RL:IP'19w (co-supervised with Tuan Dam), Maximilian Hensel, A Functional Mirror Descent Perspective on Reinforcement Learning
• RL:IP'19s, Maximilian Hensel, Kai Cui, Likelihood-free Inference in Reinforcement Learning
• BS Thesis (co-supervised with Fabio Muratore), Christian Eilers, Bayesian Optimization for Learning from Randomized Simulations
• MS Thesis (co-supervised with Hany Abdulsamad), Matthias Schultheis, Bayesian Reinforcement Learning for System Identification
• MS Thesis (co-supervised with Hany Abdulsamad), Pascal Klink, Generalization and transferability in reinforcement learning
• RL:IP'18 (Muratore, F.), Eschmann, J., Menzenbach, R., Eilers, C.
• MS Thesis, Alymbek Sadybakasov, Learning vision-based tactile skills for robotic architectural assembly
• BS Thesis, Lennart Ebeling, Experimental validation of an MPC-POMDP model of ball catching
• MS Thesis, David Nass, Risk-sensitive policy search with applications to robot-badminton
• MS Thesis, Yunlong Song, Minimax and entropic proximal policy optimization
• RL:IP'17w (Robot Learning: Integrated Project, Winter 2017), Alymbek Sadybakasov, Goal-directed reward generation
• RL:IP'17s (Robot Learning: Integrated Project, Summer 2017), Alymbek Sadybakasov, Interpolation of skills in the game of robopong
• RL:IP'16w (Robot Learning: Integrated Project, Winter 2016), Yunlong Song, Rong Zhi, Learning intuitive physics from videos
• RL:IP'16s (Robot Learning: Integrated Project, Summer 2016), Tang, J., Staschewski, T., Gou, H. Playing badminton with robots