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Found 7 papers, 1 papers with code
Neural Style Transfer with Twin-Delayed DDPG for Shared Control of Robotic Manipulators
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.
Real Evaluations Tractability using Continuous Goal-Directed Actions in Smart City Applications
As a consequence of this, the robot joint trajectories for execution must be fully computed to comply with this feature-agnostic encoding.
Neural Policy Style Transfer
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.
Deep Robot Sketching: An application of Deep Q-Learning Networks for human-like sketching
In this work, we propose the introduction of Reinforcement Learning for improving the control of artistic robot applications.
Quick, Stat!: A Statistical Analysis of the Quick, Draw! Dataset
In this paper, a statistical analysis of three of the classes contained in the Quick, Draw!
Robot Imitation through Vision, Kinesthetic and Force Features with Online Adaptation to Changing Environments
This paper presents online evolutionary strategies, as a change of paradigm within CGDA execution.
Robotic Ironing with 3D Perception and Force/Torque Feedback in Household Environments
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.
