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cs.RO2025
A Machine Learning Approach to Sensor Substitution from Tactile Sensing to Visual Perception for Non-Prehensile Manipulation
Idil Ozdamar, Doganay Sirintuna, Arash Ajoudani
Mobile manipulators are increasingly deployed in complex environments, requiring diverse sensors to perceive and interact with their surroundings. However, equipping every robot wi…
cs.RO2025
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…
cs.RO2024
Pushing in the Dark: A Reactive Pushing Strategy for Mobile Robots Using Tactile Feedback
Idil Ozdamar, Doganay Sirintuna, Robin Arbaud +1
For mobile robots, navigating cluttered or dynamic environments often necessitates non-prehensile manipulation, particularly when faced with objects that are too large, irregular,…