Zobrazeno 1 - 10
of 271
pro vyhledávání: '"A. Ugur Emre"'
Autor:
Dogangun, Fatih, Bahar, Serdar, Yildirim, Yigit, Temir, Bora Toprak, Ugur, Emre, Dogan, Mustafa Doga
As robotics continue to enter various sectors beyond traditional industrial applications, the need for intuitive robot training and interaction systems becomes increasingly more important. This paper introduces Robotic Augmented Reality for Machine P
Externí odkaz:
http://arxiv.org/abs/2410.13412
Autor:
Aktas, Hakan, Ugur, Emre
This paper proposes a novel neural network model capable of discovering high-level skill representations from unlabeled demonstration data. We also propose a bi-level planning pipeline that utilizes our model using a gradient-based planning approach.
Externí odkaz:
http://arxiv.org/abs/2410.10045
Affordances represent the inherent effect and action possibilities that objects offer to the agents within a given context. From a theoretical viewpoint, affordances bridge the gap between effect and action, providing a functional understanding of th
Externí odkaz:
http://arxiv.org/abs/2404.15648
Autor:
Yildirim, Yigit, Ugur, Emre
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 important aspect of navigation systems. To use learning-based techniq
Externí odkaz:
http://arxiv.org/abs/2404.11246
Trustworthiness is a crucial concept in the context of human-robot interaction. Cooperative robots must be transparent regarding their decision-making process, especially when operating in a human-oriented environment. This paper presents a comprehen
Externí odkaz:
http://arxiv.org/abs/2404.04069
Socially compliant navigation is an integral part of safety features in Human-Robot Interaction. Traditional approaches to mobile navigation prioritize physical aspects, such as efficiency, but social behaviors gain traction as robots appear more in
Externí odkaz:
http://arxiv.org/abs/2403.15813
Human brain and behavior provide a rich venue that can inspire novel control and learning methods for robotics. In an attempt to exemplify such a development by inspiring how humans acquire knowledge and transfer skills among tasks, we introduce a no
Externí odkaz:
http://arxiv.org/abs/2403.04001
Autor:
Yildirim, Yigit, Ugur, Emre
Learning from Demonstration (LfD) is a widely used technique for skill acquisition in robotics. However, demonstrations of the same skill may exhibit significant variances, or learning systems may attempt to acquire different means of the same skill
Externí odkaz:
http://arxiv.org/abs/2402.08424
Autor:
Utku, Aydin Emre, Ada, Suzan Ece, Hatipoglu, Muhammet, Derman, Mustafa, Ugur, Emre, Samur, Evren
Metabolic energy consumption of a powered lower-limb exoskeleton user mainly comes from the upper body effort since the lower body is considered to be passive. However, the upper body effort of the users is largely ignored in the literature when desi
Externí odkaz:
http://arxiv.org/abs/2402.00135
Discovering the symbols and rules that can be used in long-horizon planning from a robot's unsupervised exploration of its environment and continuous sensorimotor experience is a challenging task. The previous studies proposed learning symbols from s
Externí odkaz:
http://arxiv.org/abs/2401.01123