Zobrazeno 1 - 10
of 412
pro vyhledávání: '"Sanfeliu, Alberto"'
Autor:
Viyuela, Oscar Gil, Sanfeliu, Alberto
Human-Robot Collaboration (HRC) has evolved into a highly promising issue owing to the latest breakthroughs in Artificial Intelligence (AI) and Human-Robot Interaction (HRI), among other reasons. This emerging growth increases the need to design mult
Externí odkaz:
http://arxiv.org/abs/2410.00517
Autor:
Gil, Oscar, Sanfeliu, Alberto
Human motion trajectory prediction is a very important functionality for human-robot collaboration, specifically in accompanying, guiding, or approaching tasks, but also in social robotics, self-driving vehicles, or security systems. In this paper, a
Externí odkaz:
http://arxiv.org/abs/2311.10582
Autor:
Singamaneni, Phani Teja, Bachiller-Burgos, Pilar, Manso, Luis J., Garrell, Anaís, Sanfeliu, Alberto, Spalanzani, Anne, Alami, Rachid
Socially aware robot navigation is gaining popularity with the increase in delivery and assistive robots. The research is further fueled by a need for socially aware navigation skills in autonomous vehicles to move safely and appropriately in spaces
Externí odkaz:
http://arxiv.org/abs/2311.06922
Autor:
Crowley, James L., Coutaz, Joëlle L, Grosinger, Jasmin, Vázquez-Salceda, Javier, Angulo, Cecilio, Sanfeliu, Alberto, Iocchi, Luca, Cohn, Anthony G.
Publikováno v:
IEEE Pervasive Computing, 2022
We propose a hierarchical framework for collaborative intelligent systems. This framework organizes research challenges based on the nature of the collaborative activity and the information that must be shared, with each level building on capabilitie
Externí odkaz:
http://arxiv.org/abs/2212.08659
Autor:
Gil, Óscar, Sanfeliu, Alberto
The navigation of robots in dynamic urban environments, requires elaborated anticipative strategies for the robot to avoid collisions with dynamic objects, like bicycles or pedestrians, and to be human aware. We have developed and analyzed three anti
Externí odkaz:
http://arxiv.org/abs/2210.08280
Autor:
Ciarfuglia, Thomas A., Motoi, Ionut M., Saraceni, Leonardo, Fawakherji, Mulham, Sanfeliu, Alberto, Nardi, Daniele
Publikováno v:
Computers and Electronics in Agriculture, Volume 205, February 2023, 107624
Detection, segmentation and tracking of fruits and vegetables are three fundamental tasks for precision agriculture, enabling robotic harvesting and yield estimation applications. However, modern algorithms are data hungry and it is not always possib
Externí odkaz:
http://arxiv.org/abs/2208.13001
This paper presents the design of deep learning architectures which allow to classify the social relationship existing between two people who are walking in a side-by-side formation into four possible categories --colleagues, couple, family or friend
Externí odkaz:
http://arxiv.org/abs/2207.02890
In this work, we propose a gesture based language to allow humans to interact with robots using their body in a natural way. We have created a new gesture detection model using neural networks and a custom dataset of humans performing a set of body g
Externí odkaz:
http://arxiv.org/abs/2206.07538
In this work we argue that in Human-Robot Collaboration (HRC) tasks, the Perception-Action cycle in HRC tasks can not fully explain the collaborative behaviour of the human and robot and it has to be extended to Perception-Intention-Action cycle, whe
Externí odkaz:
http://arxiv.org/abs/2206.00304
Recent advances in 3D human shape reconstruction from single images have shown impressive results, leveraging on deep networks that model the so-called implicit function to learn the occupancy status of arbitrarily dense 3D points in space. However,
Externí odkaz:
http://arxiv.org/abs/2205.04087