1 citations · 3 across the 8 of their papers we have counts for
8 papers
Self-supervised Physics-Informed Manipulation of Deformable Linear Objects with Non-negligible Dynamics
Youyuan Long, Gokhan Solak, Sara Zeynalpour +2
We address dynamic manipulation of deformable linear objects by presenting SPiD, a physics-informed self-supervised learning framework that couples an accurate deformable object mo…
Safe Learning for Contact-Rich Robot Tasks: A Survey from Classical Learning-Based Methods to Safe Foundation Models
Heng Zhang, Rui Dai, Gokhan Solak +3
Contact-rich tasks pose significant challenges for robotic systems due to inherent uncertainty, complex dynamics, and the high risk of damage during interaction. Recent advances in…
OmniVIC: A Self-Improving Variable Impedance Controller with Vision-Language In-Context Learning for Safe Robotic Manipulation
Heng Zhang, Wei-Hsing Huang, Gokhan Solak +1
We present OmniVIC, a universal variable impedance controller (VIC) enhanced by a vision language model (VLM), which improves safety and adaptation in any contact-rich robotic mani…
Anticipatory Fall Detection in Humans with Hybrid Directed Graph Neural Networks and Long Short-Term Memory
Younggeol Cho, Gokhan Solak, Olivia Nocentini +3
Detecting and preventing falls in humans is a critical component of assistive robotic systems. While significant progress has been made in detecting falls, the prediction of falls…
A Survey on Imitation Learning for Contact-Rich Tasks in Robotics
Toshiaki Tsuji, Yasuhiro Kato, Gokhan Solak +4
This paper comprehensively surveys research trends in imitation learning for contact-rich robotic tasks. Contact-rich tasks, which require complex physical interactions with the en…
Context-aware collaborative pushing of heavy objects using skeleton-based intention prediction
Gokhan Solak, Gustavo J. G. Lahr, Idil Ozdamar +1
In physical human-robot interaction, force feedback has been the most common sensing modality to convey the human intention to the robot. It is widely used in admittance control to…