Search Results for author: Juan G. Victores

Found 8 papers, 1 papers with code

Neural Style Transfer with Twin-Delayed DDPG for Shared Control of Robotic Manipulators

no code implementations1 Feb 2024 Raul Fernandez-Fernandez, Marco Aggravi, Paolo Robuffo Giordano, Juan G. Victores, Claudio Pacchierotti

In this context, we propose a custom NST framework for transferring a set of styles to the motion of a robotic manipulator, e. g., the same robotic task can be carried out in an angry, happy, calm, or sad way.

Style Transfer

Real Evaluations Tractability using Continuous Goal-Directed Actions in Smart City Applications

no code implementations1 Feb 2024 Raul Fernandez-Fernandez, Juan G. Victores, David Estevez, Carlos Balaguer

As a consequence of this, the robot joint trajectories for execution must be fully computed to comply with this feature-agnostic encoding.

Evolutionary Algorithms

Neural Policy Style Transfer

no code implementations1 Feb 2024 Raul Fernandez-Fernandez, Juan G. Victores, Jennifer J. Gago, David Estevez, Carlos Balaguer

The implementation of three different Q-Network architectures (Shallow, Deep and Deep Recurrent Q-Network) to encode the policies within the NPST framework is proposed and the results obtained in the experiments with each of these architectures compared.

Atari Games reinforcement-learning +1

Deep Robot Sketching: An application of Deep Q-Learning Networks for human-like sketching

no code implementations1 Feb 2024 Raul Fernandez-Fernandez, Juan G. Victores, Carlos Balaguer

In this work, we propose the introduction of Reinforcement Learning for improving the control of artistic robot applications.

Q-Learning reinforcement-learning

Sequence-to-Sequence Natural Language to Humanoid Robot Sign Language

no code implementations9 Jul 2019 Jennifer J. Gago, Valentina Vasco, Bartek Łukawski, Ugo Pattacini, Vadim Tikhanoff, Juan G. Victores, Carlos Balaguer

Natural language to sign language translation presents several challenges to developers, such as the discordance between the length of input and output data and the use of non-manual markers.

Sign Language Translation Translation

Robotic Ironing with 3D Perception and Force/Torque Feedback in Household Environments

1 code implementation16 Jun 2017 David Estevez, Juan G. Victores, Raul Fernandez-Fernandez, Carlos Balaguer

From this point cloud, the garment is segmented and a custom Wrinkleness Local Descriptor (WiLD) is computed to determine the location of the present wrinkles.

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