Taking humanoid soccer to the next level: An interview with RoboCup trustee Alessandra Rossi

A core objective of RoboCup is to promote and advance robotics and AI research through the challenges offered by its various leagues. The ultimate goal of the soccer competition is that, by 2050, a team of fully autonomous humanoid robots will defeat the most recent winner of the FIFA World Cup. To bring this vision closer to reality, the RoboCup Federation has announced several changes to the leagues. We spoke with Alessandra Rossi, a trustee who has been involved in the humanoid soccer league for many years, to learn more.

Alessandra Rossi is an Assistant Professor of Computer Science at the University of Naples “Federico II”. She began her journey with RoboCup in 2016 and has since become a key figure in the community, serving on various technical and executive committees before being elected to the Board of Trustees in 2025.

One of the major strategic changes announced is the merger of the Standard Platform League (SPL) and the KidSize Humanoid League. This move aims to align the leagues toward a shared objective and create a new roadmap for the 2050 goal. Rossi noted that while the goal remains the same, the path must adapt to rapid advancements in hardware and large language models (LLMs).

Soccer serves as a complex benchmark for robotics, requiring integration of physical control, strategy, and human-like communication. Recent improvements have seen robots moving at speeds close to running. To increase complexity, the number of robots per team has been raised to three, and the role of human handlers on the field has been significantly reduced.

Regarding hardware, the federation remains open to multiple platforms rather than strictly enforcing a single standard. This flexibility prevents research from being limited by hardware that may become obsolete quickly. Rossi emphasized that the solutions developed for RoboCup—ranging from multi-agent systems to social robotics—have applications far beyond the soccer field, contributing to the broader field of AI and human-robot interaction.