most citedRAMPA: Robotic Augmented Reality for Machine Programming by DemonstrAtion

11 citations · 13 across the 6 of their papers we have counts for

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cs.RO2026

Trajectory Learning with Graph Representations for Social Robot Navigation

Berke Kartal, Burcu Kilic, Yigit Yildirim +1

Autonomous mobile robots are expected to exhibit socially compliant navigation for minimizing pedestrian disturbance. While capturing social interactions and incorporating pedestri…

cs.RO202411 cited

RAMPA: Robotic Augmented Reality for Machine Programming by DemonstrAtion

Fatih Dogangun, Serdar Bahar, Yigit Yildirim +3

This paper introduces Robotic Augmented Reality for Machine Programming by Demonstration (RAMPA), the first ML-integrated, XR-driven end-to-end robotic system, allowing training an…

cs.RO2024

Neuro-Symbolic Skill Discovery for Conditional Multi-Level Planning

Hakan Aktas, Yigit Yildirim, Ahmet Firat Gamsiz +3

This paper proposes a novel learning architecture for acquiring generalizable high-level symbolic skills from a few unlabeled low-level skill trajectory demonstrations. The archite…

cs.RO2024

Bidirectional Human Interactive AI Framework for Social Robot Navigation

Tuba Girgin, Emre Girgin, Yigit Yildirim +2

Trustworthiness is a crucial concept in the context of human-robot interaction. Cooperative robots must be transparent regarding their decision-making process, especially when oper…

cs.RO20241 cited

Learning Early Social Maneuvers for Enhanced Social Navigation

Yigit Yildirim, Mehmet Suzer, Emre Ugur

Socially compliant navigation is an integral part of safety features in Human-Robot Interaction. Traditional approaches to mobile navigation prioritize physical aspects, such as ef…

cs.RO20241 cited

Learning Social Navigation from Demonstrations with Deep Neural Networks

Yigit Yildirim, Emre Ugur

Traditional path-planning techniques treat humans as obstacles. This has changed since robots started to enter human environments. On modern robots, social navigation has become an…