Push-to-See: Learning Non-Prehensile Manipulation to Enhance Instance Segmentation via Deep Q-Learning (2022)
Conference Proceeding
Serhan, B., Pandya, H., Kucukyilmaz, A., & Neumann, G. (2022). Push-to-See: Learning Non-Prehensile Manipulation to Enhance Instance Segmentation via Deep Q-Learning. In IEEE International Conference on Robotics and Automation (ICRA 2022) (1513-1519). https://doi.org/10.1109/ICRA46639.2022.9811645

Efficient robotic manipulation of objects for sorting and searching often rely upon how well the objects are perceived and the available grasp poses. The challenge arises when the objects are irregular, have similar visual features (e.g., textureless... Read More about Push-to-See: Learning Non-Prehensile Manipulation to Enhance Instance Segmentation via Deep Q-Learning.

Intelligent control of exoskeletons through a novel learning-from-demonstration method (2020)
Presentation / Conference
Ugur, E., Samur, E., Ugurlu, B., Erol Barkana, D., Kucukyilmaz, A., & Bebek, O. (2020, September). Intelligent control of exoskeletons through a novel learning-from-demonstration method. Poster presented at Cybathlon Symposium 2020, Zurich, Switzerland

We present a novel concept that enables the intelligent and adaptive control of exoskeletons through exploiting our state-of-the-art learning from demonstration (LfD) method, namely Conditional Neural Movement Primitives (CNMPs) [1], on our integrate... Read More about Intelligent control of exoskeletons through a novel learning-from-demonstration method.