human-robot interaction

SECURE Project

Safety Enables Cooperation in Uncertain Robotic Environments

Incorporating End-to-End Speech Recognition Models for Sentiment Analysis

Previous work on emotion recognition demonstrated a synergistic effect of combining several modalities such as auditory, visual, and transcribed text, to estimate the affective state of a speaker. Among these, the linguistic modality is crucial for …

On the Robustness of Speech Emotion Recognition for Human-Robot Interaction with Deep Neural Networks

Speech emotion recognition (SER) is an important aspect of effective human-robot collaboration and received a lot of attention from the research community. For example, many neural network-based architectures were proposed recently and pushed the …

Language-modulated Actions using Deep Reinforcement Learning for Safer Human-Robot Interaction

Spoken language can be an efficient and intuitive way to warn robots about threats. Guidance and warnings from a human can be used to inform and modulate a robot’s actions. An open research question is how the instructions and warnings can be …

EmoRL: Real-time Acoustic Emotion Classification using Deep Reinforcement Learning

Acoustically expressed emotions can make communication with a robot more efficient. Detecting emotions like anger could provide a clue for the robot indicating unsafe/undesired situations. Recently, several deep neural network-based models have been …

Robot that performs language instructions

Presented at European Researchers' Night in the Parlamentarium, Brussels, Belgium.

Simultaneous Human-Robot Adaptation for Effective Skill Transfer

In this paper, we propose and implement a human-in-the loop robot skill synthesis framework that involves simultaneous adaptation of the human and the robot. In this framework, the human demonstrator learns to control the robot in real-time to make …


Human Learning for Robot Skill GenerationT