activity
20092026
most citedAutonomous Quadrotor Landing using Deep Reinforcement Learning

41 citations · 189 across the 29 of their papers we have counts for

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5 papers · 1 filter

cs.LG2026

LUCID: Latent-Skill Unified Control via Imagined Dynamics for Long-Horizon Humanoid Loco-Manipulation

Cheng Guo, Mingzhe Ni, Angelo Cangelosi +1

Long-horizon humanoid loco-manipulation requires composing versatile whole-body skills and reliable high-level decision making. Existing methods often coordinate pretrained skills…

cs.LG2023★ 2 cited

To Whom are You Talking? A Deep Learning Model to Endow Social Robots with Addressee Estimation Skills

Carlo Mazzola, Marta Romeo, Francesco Rea +2

Communicating shapes our social word. For a robot to be considered social and being consequently integrated in our social environment it is fundamental to understand some of the dy…

cs.LG2023★ 4 cited

Towards Multi-User Activity Recognition through Facilitated Training Data and Deep Learning for Human-Robot Collaboration Applications

Francesco Semeraro, Jon Carberry, Angelo Cangelosi

Human-robot interaction (HRI) research is progressively addressing multi-party scenarios, where a robot interacts with more than one human user at the same time. Conversely, resear…

cs.LG2020★ 8 cited

A robot that counts like a child: a developmental model of counting and pointing

Leszek Pecyna, Angelo Cangelosi, Alessandro Di Nuovo

In this paper, a novel neuro-robotics model capable of counting real items is introduced. The model allows us to investigate the interaction between embodiment and numerical cognit…

cs.LG2009★ 8 cited

Cross-situational and supervised learning in the emergence of communication

José F. Fontanari, Angelo Cangelosi

Scenarios for the emergence or bootstrap of a lexicon involve the repeated interaction between at least two agents who must reach a consensus on how to name N objects using H words…