Berk Gueler
Research Interests
Assitive Teleoperation, Shared Control / Autonomy, Deformable Linear Object Manipulation, physical Human-Robot Interaction
Affiliation
TU Darmstadt, Intelligent Autonomous Systems, Computer Science Department
Honda Research Institute
Contact
berk.gueler@tu-darmstadt.de
Room D202, Building S2|02, TU Darmstadt, FB-Informatik, FG-IAS, Hochschulstr. 10, 64289 Darmstadt
+49-6151-16-21817
Berk Güler joined the Intelligent Autonomous System lab on July 15, 2023, as a PhD student. He is currently working in a joint research project with the Honda Research Institute in Offenbach am Main.
Before his PhD, Berk Güler completed his Master's Degree in Mechanical Engineering at the Koç University where he specialized in the area of physical Human-Robot Interaction (pHRI). He conducted his thesis entitled “Deep Reinforcement Learning to Optimize Task Performance for pHRI" under the supervision of Prof. Çağatay Başdoğan. During his Master's studies, he was a research fellow at the KUIS AI Center. Berk Güler hold a Bachelor's degree in Control and Automation Engineering from Istanbul Technical University
Teaching
Robot Learning (Fall - 2023)
I am looking for BSc & MSc students who would like to work on manipulation/perception of deformable linear objects! Feel free to reach out from my e-mail address: berk@robot-learning.de
Supervised Theses and Projects
| Thesis/Project | Topic | Student(s) | Together with |
| Robot Learning: IP 1+2 | Control Barrier Functions for Assistive Teleoperation | Yihui Huang,Yuanzheng Sun | Kay Hansel |
| Robot Learning: IP 1 | Real-Time Deformable Object Instance Segmentation and Tracking | Jiahong Xue, Yu Deng, Teng Cao | Yufeng Jin |
Publications
TeleoperationManschitz, S.; Guler, B.; Ma, W.; Ruiken, D. (2024). Sampling-Based Grasp and Collision Prediction for Assisted Teleoperation, ICRA 2025 AcceptedGuler, B.; Pompetzki, K.; Manschitz, S.; Peters, J. (2025). Toward Assistive Teleoperation Framework for Deformable Linear Object Manipulation, German Robotics Conference 2025
physical Human-Robot Interaction (pHRI)Guler, B.; Dincer, E. U.; Aydin, Y.; Oguz, O. S.; Basdogan, C. (2025). Learning-Based Optimization of Admittance Controller for Enhanced Task Performance in Physical Human-Robot Co-Manipulation, Submitted on T-RO
- Guler, B. (2023). Deep Reinforcement Learning to Optimize Task Performance in Human-Robot Co-manipulation, Master Thesis.
- Guler, B.; Niaz, P.P.; Madani, A.; Aydin Y.; Basdogan, C. (2022). An adaptive admittance controller for collaborative drilling with a robot based on subtask classification via deep learning, Mechatronics, 2022, 86, pp.102851, Elsevier.
- Madani, A.; Niaz, P.P.; Guler, B.; Aydin Y.; Basdogan, C. (2022). Robot-Assisted Drilling on Curved Surfaces with Haptic Guidance under Adaptive Admittance Control, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp.3723-3730, IEEE.