Berk Gueler

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

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

Publications

Teleoperation

1. •     Bib
     Manschitz, S.; Guler, B.; Ma, W.; Ruiken, D. (2025). Sampling-Based Grasp and Collision Prediction for Assisted Teleoperation, IEEE International Conference on Robotics and Automation (ICRA).
2. •     Bib
     Guler, B.; Pompetzki, K.; Manschitz, S.; Peters, J. (2025). Towards Assistive Teleoperation for Knot Untangling, German Robotics Conference (GRC).

physical Human-Robot Interaction (pHRI)

1. •   Bib
     Guler, B. (2023). Deep Reinforcement Learning to Optimize Task Performance in Human-Robot Co-manipulation, Master Thesis.
2. •       Bib
     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.
3. •     Bib
     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.