7 papers
Adaptive Optimal Control for Avatar-Guided Motor Rehabilitation in Virtual Reality
Francesco De Lellis, Maria Lombardi, Egidio De Benedetto +2
A control-theoretic framework for autonomous avatar-guided rehabilitation in virtual reality, based on interpretable, adaptive motor guidance through optimal control, is presented.…
A bioreactor-based architecture for in vivo model-based and sim-to-real learning control of microbial consortium composition
Sara Maria Brancato, Davide Salzano, Davide Fiore +3
Microbial consortia offer significant biotechnological advantages over monocultures for bioproduction. However, industrial deployment is hampered by the lack of scalable architectu…
Breaking the mould of Social Mixed Reality - State-of-the-Art and Glossary
Marta BieÅkiewicz, Julia Ayache, Panayiotis Charalambous +15
This article explores a critical gap in Mixed Reality (MR) technology: while advances have been made, MR still struggles to authentically replicate human embodiment and socio-motor…
Online Phase Estimation of Human Oscillatory Motions using Deep Learning
Antonio Grotta, Francesco De Lellis
Accurately estimating the phase of oscillatory systems is essential for analyzing cyclic activities such as repetitive gestures in human motion. In this work we introduce a learnin…
Hierarchical Policy-Gradient Reinforcement Learning for Multi-Agent Shepherding Control of Non-Cohesive Targets
Stefano Covone, Italo Napolitano, Francesco De Lellis +1
We propose a decentralized reinforcement learning solution for multi-agent shepherding of non-cohesive targets using policy-gradient methods. Our architecture integrates target-sel…
Emergent Cooperative Strategies for Multi-Agent Shepherding via Reinforcement Learning
Italo Napolitano, Andrea Lama, Francesco De Lellis +1
We present a decentralized reinforcement learning (RL) approach to address the multi-agent shepherding control problem, departing from the conventional assumption of cohesive targe…