activity
20192024
most citedPredictive Event Segmentation and Representation with Neural Networks: A Self-Supervised Model Assessed by Psychological Experiments

1 citations · 2 across the 5 of their papers we have counts for

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6 papers · 1 filter

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.RO2020

Reward Conditioned Neural Movement Primitives for Population Based Variational Policy Optimization

M. Tuluhan Akbulut, Utku Bozdogan, Ahmet Tekden +1

The aim of this paper is to study the reward based policy exploration problem in a supervised learning approach and enable robots to form complex movement trajectories in challengi…

cs.RO2020

Exploration with Intrinsic Motivation using Object-Action-Outcome Latent Space

Melisa Sener, Yukie Nagai, Erhan Oztop +1

One effective approach for equipping artificial agents with sensorimotor skills is to use self-exploration. To do this efficiently is critical, as time and data collection are cost…

cs.RO2020

ACNMP: Skill Transfer and Task Extrapolation through Learning from Demonstration and Reinforcement Learning via Representation Sharing

M. Tuluhan Akbulut, Erhan Oztop, M. Yunus Seker +3

To equip robots with dexterous skills, an effective approach is to first transfer the desired skill via Learning from Demonstration (LfD), then let the robot improve it by self-exp…

cs.RO2019

Belief Regulated Dual Propagation Nets for Learning Action Effects on Groups of Articulated Objects

Ahmet E. Tekden, Aykut Erdem, Erkut Erdem +3

In recent years, graph neural networks have been successfully applied for learning the dynamics of complex and partially observable physical systems. However, their use in the robo…