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Found 13 papers, 1 papers with code
How much informative is your XAI? A decision-making assessment task to objectively measure the goodness of explanations
There is an increasing consensus about the effectiveness of user-centred approaches in the explainable artificial intelligence (XAI) field.
Real-time Addressee Estimation: Deployment of a Deep-Learning Model on the iCub Robot
Addressee Estimation is the ability to understand to whom a person is talking, a skill essential for social robots to interact smoothly with humans.
To Whom are You Talking? A Deep Learning Model to Endow Social Robots with Addressee Estimation Skills
Communicating shapes our social word.
I am Only Happy When There is Light: The Impact of Environmental Changes on Affective Facial Expressions Recognition
Human-robot interaction (HRI) benefits greatly from advances in the machine learning field as it allows researchers to employ high-performance models for perceptual tasks like detection and recognition.
Robots with Different Embodiments Can Express and Influence Carefulness in Object Manipulation
Humans have an extraordinary ability to communicate and read the properties of objects by simply watching them being carried by someone else.
Synthesis and Execution of Communicative Robotic Movements with Generative Adversarial Networks
Object manipulation is a natural activity we perform every day.
A User-Centred Framework for Explainable Artificial Intelligence in Human-Robot Interaction
The framework aims to provide a structure for interactive XAI solutions thought for non-expert users.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
From Movement Kinematics to Object Properties: Online Recognition of Human Carefulness
This study is a step towards endowing a humanoid robot with this last capability.
Property-Aware Robot Object Manipulation: a Generative Approach
When transporting an object, we unconsciously adapt our movement to its properties, for instance by slowing down when the item is fragile.
Cognitive architecture aided by working-memory for self-supervised multi-modal humans recognition
The ability to recognize human partners is an important social skill to build personalized and long-term human-robot interactions, especially in scenarios like education, care-giving, and rehabilitation.
Careful with That! Observation of Human Movements to Estimate Objects Properties
Our final goal is to enable a robot to autonomously infer the degree of care required in object handling and to discriminate whether the item is light or heavy, just by observing a human manipulation.
Self-supervised reinforcement learning for speaker localisation with the iCub humanoid robot
In the future robots will interact more and more with humans and will have to communicate naturally and efficiently.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Action similarity judgment based on kinematic primitives
The results show that both the model and human performance are highly accurate in an action similarity task based on kinematic-level features, which can provide an essential basis for classifying human actions.
