3 papers
eess.SY2024
Data-driven architecture to encode information in the kinematics of robots and artificial avatars
Francesco De Lellis, Marco Coraggio, Nathan C. Foster +3
We present a data-driven control architecture for modifying the kinematics of robots and artificial avatars to encode specific information such as the presence or not of an emotion…
eess.SY2023
In vivo learning-based control of microbial populations density in bioreactors
Sara Maria Brancato, Davide Salzano, Francesco De Lellis +3
A key problem toward the use of microorganisms as bio-factories is reaching and maintaining cellular communities at a desired density and composition so that they can efficiently c…
eess.SY2023
Guaranteeing Control Requirements via Reward Shaping in Reinforcement Learning
Francesco De Lellis, Marco Coraggio, Giovanni Russo +2
In addressing control problems such as regulation and tracking through reinforcement learning, it is often required to guarantee that the acquired policy meets essential performanc…