Enhancing Social Human-Robot Interaction with Deep Reinforcement Learning.
This research aims to develop an autonomous social robot for elderly individuals. The robot
will learn from the interaction and change its behaviors in order to enhance the interaction …
will learn from the interaction and change its behaviors in order to enhance the interaction …
AIR-Act2Act: Human–human interaction dataset for teaching non-verbal social behaviors to robots
To better interact with users, a social robot should understand the users' behavior, infer the
intention, and respond appropriately. Machine learning is one way of implementing robot …
intention, and respond appropriately. Machine learning is one way of implementing robot …
A social human-robot interaction simulator for reinforcement learning systems
JPR Belo, RAF Romero - 2021 20th international conference …, 2021 - ieeexplore.ieee.org
Social robotics represents a branch of human-robot interaction that aims to develop robots to
operate in unstructured environments in direct partnership with human beings. Social robots …
operate in unstructured environments in direct partnership with human beings. Social robots …
[PDF][PDF] Socially-aware reinforcement learning for personalized human-robot interaction
H Ritschel - 2018 - opus.bibliothek.uni-augsburg.de
This research in the context of Human-Robot Interaction explores how to tailor the robot
behavior to the human's individual preferences in real-time. Algorithmically, Reinforcement …
behavior to the human's individual preferences in real-time. Algorithmically, Reinforcement …
Learning socially appropriate robot approaching behavior toward groups using deep reinforcement learning
Deep reinforcement learning has recently been widely applied in robotics to study tasks
such as locomotion and grasping, but its application to social human-robot interaction (HRI) …
such as locomotion and grasping, but its application to social human-robot interaction (HRI) …
Human-like Social Learning for Social Robots: A Systematic Review
Social learning is a learning paradigm aiming to make the process of teaching new skills to
an artificial intelligent agent (such as a robot) as close as possible to the process we employ …
an artificial intelligent agent (such as a robot) as close as possible to the process we employ …
On-the-fly detection of user engagement decrease in spontaneous human-robot interaction
AB Youssef, G Varni, S Essid… - International Journal of …, 2019 - telecom-paris.hal.science
In this paper, we address the detection of engagement decrease of users spontaneously
interacting with a socially assistive robot in a public space. We first describe the UE-HRI …
interacting with a socially assistive robot in a public space. We first describe the UE-HRI …
Editorial Introduction to Special Issue on Machine Learning for Social Human-Robot Interaction
The fast-paced development of learning models and training tactics in the field of artificial
intelligence is motivating robotics community to employ machine learning-based data-driven …
intelligence is motivating robotics community to employ machine learning-based data-driven …
Deep reinforcement learning for the autonomous adaptive behavior of social robots
Social assistive robots are conceived to cooperate with humans in many areas like
healthcare, education, or assistance. In situations where the workforce is scarce and when …
healthcare, education, or assistance. In situations where the workforce is scarce and when …
Teaching robot's proactive behavior using human assistance
In recent years, there has been a growing interest in enabling autonomous social robots to
interact with people. However, many questions remain unresolved regarding the social …
interact with people. However, many questions remain unresolved regarding the social …