An LLM-Based Automatic Sportscast Solution for Robot Soccer Matches
Computer Vision and Pattern Recognition
Summary
The authors created a system that watches RoboCup soccer games and talks about what happens in real time, like a sports commentator. It uses a combination of tracking robot movements and turning that data into clear, accurate spoken summaries without mistakes. This system works both while games are happening live and afterward for review. It also adapts well to different kinds of robots playing together on the field.
Authors
Francesco Petri, Michele Brienza, Daniele Nardi, Domenico Daniele Bloisi, Aldo Gangemi, Vincenzo Suriani
Abstract
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 Soccer leagues need to constantly measure how the research community is progressing. Computing visual statistics from match videos is a crucial way to track this evolution. To address this challenge, this paper introduces a fully autonomous, real-time sports commentator for RoboCup matches. By bridging the gap between raw kinematic tracking and natural language generation, our neuro-symbolic architecture extracts precise statistics from video streams and turns them into fluent, hallucination-free narration. The proposed system is capable of generating statistics and commentary both during live match streaming and in post-game analysis, easily adapting to the new dynamism of the league where different humanoid robots of different sizes share the field. Supplemental materials are available at https://lab-rococo-sapienza.github.io/MARIO/