3 citations · 7 across the 11 of their papers we have counts for
11 papers
An LLM-Based Automatic Sportscast Solution for Robot Soccer Matches
Francesco Petri, Michele Brienza, Daniele Nardi +3
RoboCup has always been a scenario to develop systems that solve real-world problems. Driven by the main goal of playing against the 2050 FIFA World Cup champions, the RoboCup Socc…
Semantic Audio-driven Understanding for Dynamic Humanoid Whole Body Control
J. M. A. Marcelo, M. Brienza, E. Bugli +4
Recent advances in humanoid robotics and reinforcement learning have enabled the acquisition of highly expressive whole-body motion policies. However, most robotic performances rem…
R2F: Repurposing Ray Frontiers for LLM-free Object Navigation
Francesco Argenziano, John Mark Alexis Marcelo, Michele Brienza +5
Zero-shot open-vocabulary object navigation has progressed rapidly with the emergence of large Vision-Language Models (VLMs) and Large Language Models (LLMs), now widely used as hi…
LOST-3DSG: Lightweight Open-Vocabulary 3D Scene Graphs with Semantic Tracking in Dynamic Environments
Sara Micol Ferraina, Michele Brienza, Francesco Argenziano +4
Tracking objects that move within dynamic environments is a core challenge in robotics. Recent research has advanced this topic significantly; however, many existing approaches rem…
Context Matters! Relaxing Goals with LLMs for Feasible 3D Scene Planning
Emanuele Musumeci, Michele Brienza, Francesco Argenziano +4
Embodied agents need to plan and act reliably in real and complex 3D environments. Classical planning (e.g., PDDL) offers structure and guarantees, but in practice it fails under n…
Real-Time Multimodal Signal Processing for HRI in RoboCup: Understanding a Human Referee
Filippo Ansalone, Flavio Maiorana, Daniele Affinita +8
Advancing human-robot communication is crucial for autonomous systems operating in dynamic environments, where accurate real-time interpretation of human signals is essential. Robo…
EMPOWER: Embodied Multi-role Open-vocabulary Planning with Online Grounding and Execution
Francesco Argenziano, Michele Brienza, Vincenzo Suriani +2
Task planning for robots in real-life settings presents significant challenges. These challenges stem from three primary issues: the difficulty in identifying grounded sequences of…
Multi-Agent Planning Using Visual Language Models
Michele Brienza, Francesco Argenziano, Vincenzo Suriani +2
Large Language Models (LLMs) and Visual Language Models (VLMs) are attracting increasing interest due to their improving performance and applications across various domains and tas…
LLCoach: Generating Robot Soccer Plans using Multi-Role Large Language Models
Michele Brienza, Emanuele Musumeci, Vincenzo Suriani +4
The deployment of robots into human scenarios necessitates advanced planning strategies, particularly when we ask robots to operate in dynamic, unstructured environments. RoboCup o…
LLM Based Multi-Agent Generation of Semi-structured Documents from Semantic Templates in the Public Administration Domain
Emanuele Musumeci, Michele Brienza, Vincenzo Suriani +2
In the last years' digitalization process, the creation and management of documents in various domains, particularly in Public Administration (PA), have become increasingly complex…
MARIO: Modular and Extensible Architecture for Computing Visual Statistics in RoboCup SPL
Domenico D. Bloisi, Andrea Pennisi, Cristian Zampino +5
This technical report describes a modular and extensible architecture for computing visual statistics in RoboCup SPL (MARIO), presented during the SPL Open Research Challenge at Ro…