Publications related to An HMM-based Real-time Intervention Methodology for a Social Robot Supporting Learning

Related publications (13)

Principles and Guidelines for Evaluating Social RobotNavigation Algorithms

A major challenge to deploying robots widely is navigation in human-populated environments, commonly referred to as social robot navigation. While the field of social navigation has advanced tremendously in recent years, the fair evaluation of algorithms t ...

ASSOC COMPUTING MACHINERY2025

A Stochastic Approach to Contact-rich Manipulation

Julius Maximilian Jankowski

For robots to operate in unstructured environments, they are required to interact with objects through contact. Those contacts may be used to push objects to the side, deform objects, or manipulate objects in-hand. This thesis addresses the problem of cont ...

EPFL2025

Stereo Hand-Object Reconstruction for Human-to-Robot Handover

Andrea Cavallaro

Jointly estimating hand and object shape facilitates the grasping task in human-to-robot handovers. Relying on handcrafted prior knowledge about the geometric structure of the object fails when generalising to unseen objects, and depth sensors fail to dete ...

2025

GRADE: Generating Realistic and Dynamic Environments for robotics research with Isaac Sim

Chenghao Xu

Photorealistic synthetic data and novel rendering techniques significantly advanced computer vision research. However, datasets focused on computer vision applications cannot be easily applied to robotics because they typically lack physics-related informa ...

SAGE Publications2025

An augmented reality-based wearable system for handheld-free and intuitive robot programming

Junsoo Kim

Industrial robots have been programmed to optimize mass production by executing predefined trajectories with their high speed, precision, and repeatability over long production cycles. However, the rise of Industry 4.0 and the increasing demand for diverse ...

2025

Adaptive Social Learning for Tracking Rare Transition Markov Chains

Ali H. Sayed, Virginia Bordignon, Malek Khammassi

Adaptive Social Learning (ASL) enables consistent truth learning in nonstationary environments. In this framework, agents linked by a graph, exchange their local beliefs with neighbors to track some underlying state of interest. This state can drift over t ...

European Signal Processing Conference, EUSIPCO2024

A Minimum-Jerk Approach to Handle Singularities in Virtual Fixtures

Sylvain Calinon

Implementing virtual fixtures in guiding tasks constrains the movement of the robot's end effector to specific curves within its workspace. However, incorporating guiding frameworks may encounter discontinuities when optimizing the reference target positio ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2024

The stability of deep learning for 21cm foreground removal across various sky models and frequency-dependent systematics

Te Chen, Jean-Paul Richard Kneib, Daniel Felipe Forero Sanchez, Emma Elizabeth Tolley, Michele Bianco

Deep learning (DL) has recently been proposed as a novel approach for 21cm foreground removal. Before applying DL to real observations, it is essential to assess its consistency with established methods, its performance across various simulation models, an ...

2024

A game-based approach for evaluating and customizing handwriting training using an autonomous social robot

Pierre Dillenbourg, Barbara Bruno, Chenyang Wang, Daniel Carnieto Tozadore

Handwriting learning is a long and complex process that takes about ten years to be fully mastered. Nearly one-third of all children aged 4-12 experiences handwriting difficulties and, sadly, most of them are left to fight them on their own, due to the sca ...

IEEE2022

The effect of gamified robot-enhanced training on motor performance in chronic stroke survivors

Pierre Dillenbourg, Friedhelm Christoph Hummel, Barbara Bruno, Maximilian Jonas Wessel, Arzu Güneysu Özgür, Andéol Geoffroy Cadic-Melchior, Giulia Dominijanni, Valérie Rita Madeleine Zufferey

Task-specific training constitutes a core element for evidence-based rehabilitation strategies targeted at improving upper extremity activity after stroke. Its combination with additional treatment strategies and neurotechnologybased solutions could furthe ...

ELSEVIER SCI LTD2022

Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation

Andreas Krause, Maryam Kamgarpour

We consider model-based multi-agent reinforcement learning, where the environment transition model is unknown and can only be learned via expensive interactions with the environment. We propose H-MARL (Hallucinated Multi-Agent Reinforcement Learning), a no ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2022

Design of Hesitation Gestures for Nonverbal Human-Robot Negotiation of Conflicts

Aude Billard

When the question of who should get access to a communal resource first is uncertain, people often negotiate via nonverbal communication to resolve the conflict. What should a robot be programmed to do when such conflicts arise in Human-Robot Interaction? ...

ASSOC COMPUTING MACHINERY2021

Matching Seqlets: An Unsupervised Approach for Locality Preserving Sequence Matching

Pascal Fua, Xinchao Wang

In this paper, we propose a novel unsupervised approach for sequence matching by explicitly accounting for the locality properties in the sequences. In contrast to conventional approaches that rely on frame-to-frame matching, we conduct matching using sequ ...

2021