Presentation of one of the best paper award on the RoboCup 2025 symposium.
An necessary facet of autonomous soccer-playing robots issues correct detection of the ball. That is the main focus of labor by Can Lin, Daniele Affinita, Marco Zimmatore, Daniele Nardi, Domenico Bloisi, and Vincenzo Suriani, which received one of the best paper award on the current RoboCup symposium. The symposium takes place alongside the annual RoboCup competitors, which this yr was held in Salvador, Brazil. We caught up with a few of the authors to seek out out extra concerning the work, how their methodology could be transferred to purposes past RoboCup, and their future plans for the competitors.
Might you begin by giving us a quick description of the issue that you just had been making an attempt to unravel in your paper “Self-supervised Function Extraction for Enhanced Ball Detection on Soccer Robots”?
Daniele Affinita: The principle problem we confronted was that deep studying typically requires a considerable amount of labeled information. This isn’t a significant downside for frequent duties which have already been studied, as a result of you possibly can often discover labeled datasets on-line. However when the duty is very particular, like in RoboCup, it is advisable acquire and label the information your self. Which means gathering the information and manually annotating it earlier than you possibly can even begin making use of deep studying. This course of isn’t scalable and calls for a big human effort.
The thought behind our paper was to cut back this human effort. We approached the issue by self-supervised studying, which goals to study helpful representations of the information. In spite of everything, deep studying is basically about studying latent representations from the out there information.
Might you inform us a bit extra about your self-supervised studying framework and the way you went about creating it?
Daniele: Initially, let me introduce what self-supervised studying is. It’s a method of studying the construction of the information with out gaining access to labels. That is often performed by what we name pretext duties. These are duties that don’t require express labels, however as a substitute exploit the construction of the information. For instance, in our case we labored with pictures. You may randomly masks some patches and practice the mannequin to foretell the lacking elements. By doing so, the mannequin is compelled to study significant options from the information.
In our paper, we enriched the information through the use of not solely uncooked pictures but additionally exterior steerage. This got here from a bigger mannequin which we discuss with because the instructor. This mannequin was skilled on a special process which is extra normal than the goal process we aimed for. This manner the bigger mannequin can present steerage (an exterior sign) that helps the self-supervision to focus extra on the precise process we care about.
In our case, we wished to foretell a decent circle across the ball. To information this, we used an exterior pretrained mannequin (YOLO) for object detection, which as a substitute predicts a unfastened bounding field across the ball. We are able to arguably say that the bounding field, a rectangle, is extra normal than a circle. So on this sense, we had been making an attempt to make use of exterior steerage that doesn’t remedy precisely the underlying process.
Overview of the information preparation pipeline.
Have been you in a position to check this mannequin out at RoboCup 2025?
Daniele: Sure, we deployed it at RoboCup 2025 and confirmed nice enhancements over our earlier benchmark, which was the mannequin we utilized in 2024. Particularly, we seen that the ultimate coaching requires a lot much less information. The mannequin was additionally extra strong underneath totally different lighting situations. The difficulty we had with earlier fashions was that they had been tailor-made for particular conditions. However in fact, all of the venues are totally different, the lighting and the brightness are totally different, there may be shadows on the sector. So it’s actually necessary to have a dependable mannequin and we actually seen a fantastic enchancment this yr.
What’s your group identify, and will you speak a bit concerning the competitors and the way it went?
Daniele: So our group is SPQR. We’re from Rome, and we have now been competing in RoboCup for a very long time.
Domenico Blois: We began in 1998, so we’re one of many oldest groups in RoboCup.
Daniele: Yeah, I wasn’t even born then! Our group began with the four-legged robots. After which the league shifted extra in direction of biped robots as a result of they’re tougher, they require steadiness and, general it’s more durable to stroll on simply two legs.
Our group has grown so much throughout current years. We’ve been following a really optimistic development, going from ninth place in 2019 to 3rd place on the German Open in 2025, and we acquired 4th place at RoboCup 2025. Our current success has attracted extra college students to the group. So it’s form of a loop – you win extra, you appeal to extra college students, and you’ll work extra on the challenges proposed by RoboCup.
SPQR group.
Domenico: I wish to add that additionally, from a analysis standpoint, we have now received three finest paper awards within the final 5 years, and we have now been proposing some new tendencies in direction of, for instance, using LLMs for coding (as a robotic’s behaviour generator underneath the supervision of a human coach). So we are attempting to maintain the open analysis subject energetic in our group. We wish to win the matches however we additionally wish to remedy the analysis issues which are sure along with the competitors.
One of many necessary contributions of our paper is in direction of using our algorithms outdoors RoboCup. For instance, we are attempting to use the ball detector in precision farming. We wish to use the identical method to detect rounded fruits. That is one thing that’s actually necessary for us; to exit the context of Robocup and to make use of Robocup instruments for brand new approaches in different fields. So if we lose a match, it’s not a giant deal for us. We wish our college students, our group members, to be open minded in direction of using RoboCup as a place to begin for understanding teamwork and for understanding how you can cope with strict deadlines. That is one thing that RoboCup may give us. We attempt to have a group that’s prepared for each kind of problem, not solely inside RoboCup, but additionally different forms of AI purposes. Profitable isn’t all the pieces for us. We’d want to make use of our personal code and never win, than win utilizing code developed by others. This isn’t optimum for reaching first place, however we wish to train our college students to be ready for the analysis that’s outdoors of RoboCup.
You stated that you just’ve beforehand received two different finest paper awards. What did these papers cowl?
Domenico: So the final two finest papers had been form of visionary papers. In a single paper, we wished to offer an perception in how you can use the spectators to assist the robots rating. For instance, should you cheer louder, the robots are likely to kick the ball. So that is one thing that isn’t really used within the competitors now, however is one thing extra in direction of the 2050 problem. So we wish to think about how it will likely be 10 years from now.
The different paper was referred to as “play in all places”, so you possibly can, for instance, play with various kinds of ball, you possibly can play outdoors, you possibly can even play and not using a particular aim, you possibly can play utilizing Coca-Cola cans as goalposts. So the robotic has to have a normal method that isn’t associated to the precise subject utilized in RoboCup. That is in distinction to different groups which are very particular. We’ve a special method and that is one thing that makes it more durable for us to win the competitors. Nevertheless, we don’t wish to win the competitors, we wish to obtain this aim of getting, in 2050, this match between the RoboCup winners and the FIFA World Cup winners.
I’m enthusiastic about what you stated about transferring the strategy for ball detection to farming and different purposes. Might you say extra about that analysis?
Vincenzo Suriani: Our lab has been concerned in some totally different initiatives regarding farming purposes. The Flourish mission ran from 2015 – 2018. Extra not too long ago, the CANOPIES mission has focussed on precision agriculture for everlasting crops the place farmworkers can effectively work along with groups of robots to carry out agronomic interventions, like harvesting or pruning.
We’ve one other mission that’s about detecting and harvesting grapes. There’s a big effort in bringing information again from RoboCup to different initiatives, and vice versa.
Domenico: Our imaginative and prescient now’s to deal with the brand new technology of humanoid robots. We participated in a brand new occasion, the World Humanoid Robotic Video games, held in Beijing in August 2025, as a result of we wish to use the platform of RoboCup for different kinds of purposes. The thought is to have a single platform with software program that’s derived from RoboCup code that can be utilized for different purposes. When you have a humanoid robotic that should transfer, you possibly can reuse the identical code from RoboCup as a result of you need to use the identical stabilization, the identical imaginative and prescient core, the identical framework (kind of), and you’ll simply change some modules and you’ll have a very totally different kind of software with the identical robotic with kind of the identical code. We wish to go in direction of this concept of reusing code and having RoboCup as a check mattress. It’s a very powerful check mattress, however you need to use the ends in different fields and in different purposes.
Trying particularly at RoboCup, what are your future plans for the group? There are some massive modifications deliberate for the RoboCup Leagues, so may you additionally say how this would possibly have an effect on your plans?
Domenico: We’ve a really robust group and a few of the group members will do a PhD within the coming years. Certainly one of our targets was to maintain the scholars contained in the college and the analysis ward, and we had been profitable on this, as a result of now they’re very passionate concerning the RoboCup competitors and about AI normally.
By way of the modifications, there shall be a brand new league inside RoboCup that may be a merger of the usual platform league (SPL) and the humanoid kid-size league. The humanoid adult-size league will stay, so we have to resolve whether or not to affix the brand new merged league, or transfer to adult-sized robots. In the mean time we don’t have too many particulars, however what we all know is that we’ll go in direction of a brand new period of robots. We acquired robots from Booster and we are actually buying one other G1 robotic from Unitree. So we are attempting to have a whole household of recent robots. After which I believe we are going to go in direction of the league that’s chosen by the opposite groups within the SPL league. However for now we are attempting to arrange an occasion in October in Rome with two different groups to change concepts and to know the place we wish to go. There will even be a workshop to debate the analysis facet.
Vincenzo: We’re additionally in dialogue about one of the best dimension of robotic for the competitors. We’re going to have two totally different positions, as a result of robots have gotten cheaper and there are groups which are pushing to maneuver extra rapidly to an even bigger platform. Alternatively, there are groups that wish to keep on with a smaller platform in an effort to do analysis on multi brokers. We’ve seen lots of purposes for a single robotic however not many purposes with a set of robots which are cooperating. And this has been traditionally one of many core elements of analysis we did in RoboCup, and likewise outdoors of RoboCup.
There are many factors of view on which robotic dimension to make use of, as a result of there are a number of elements, and we don’t know the way quick the world will change in two or three years. We are attempting to form the foundations and the situations to play for subsequent yr, however, due to how rapidly issues are altering, we don’t know what one of the best determination shall be. And likewise the analysis we’re going to do shall be affected by the choice we make on this.
There shall be some modifications to different leagues within the close to future too; the small and center sizes will shut in two years most likely, and the simulation league additionally. Quite a bit will occur within the subsequent 5 years, most likely greater than over the last 10-15 years. This can be a vital yr as a result of the choices are based mostly on what we will see, what we will spot sooner or later, however we don’t have all the knowledge we’d like, so it will likely be difficult.
For instance, the SPL has a giant, most likely the largest, neighborhood among the many RoboCup leagues. We’ve lots of groups which are grouping by curiosity and so there are groups which are sticking to engaged on this particular downside with a particular platform and groups which are making an attempt to maneuver to a different platform and one other downside. So even inside the identical neighborhood we’re going to have multiple standpoint and hopes for the longer term. At a sure level we are going to attempt to determine what’s the finest for all of them.
Daniele: I simply wish to add that in an effort to obtain the 2050 problem, in my view, it’s essential to have only one league encompassing all the pieces. So up thus far, totally different leagues have been specializing in totally different analysis issues. There have been leagues focusing solely on technique, others focusing solely on the {hardware}, our league focusing primarily on the coordination and dynamic dealing with of the gameplay. However on the finish of the day, in an effort to compete with people, there have to be just one league bringing all these single features collectively. From my standpoint, it completely is sensible to maintain merging leagues collectively.
Concerning the authors
|
Daniele Affinita is a PhD scholar in Machine Studying at EPFL, specializing within the intersection of Machine Studying and Robotics. He has over 4 years of expertise competing in RoboCup with the SPQR group. In 2024, he labored at Sony on area adaptation methods. He holds a Bachelor’s diploma in Laptop Engineering and a Grasp’s diploma in Synthetic Intelligence and Robotics from Sapienza College of Rome. |
|
Vincenzo Suriani earned his Ph.D. in Laptop Engineering in 2024 from Sapienza College of Rome, with a specialization in synthetic intelligence, robotic imaginative and prescient, and multi-agent coordination. Since 2016, he has served as Software program Growth Chief of the Sapienza Soccer Robotic Staff, contributing to main robotic competitions and worldwide initiatives similar to EUROBENCH, SciRoc, and Tech4YOU. He’s presently a Analysis Fellow on the College of Basilicata, the place he focuses on creating clever environments for software program testing automation. His analysis, acknowledged with award-winning papers on the RoboCup Worldwide Symposium (2021, 2023, 2025), facilities on robotic semantic mapping, object recognition, and human–robotic interplay. |
|
Domenico Daniele Bloisi is an affiliate professor of Synthetic Intelligence on the Worldwide College of Rome UNINT. Beforehand, he was affiliate professor on the College of Basilicata, assistant professor on the College of Verona, and assistant professor at Sapienza College of Rome. He acquired his PhD, grasp’s and bachelor’s levels in Laptop Engineering from Sapienza College of Rome in 2010, 2006 and 2004, respectively. He’s the writer of greater than 80 peer-reviewed papers printed in worldwide journals and conferences within the subject of synthetic intelligence and robotics, with a deal with picture evaluation, multi-robot coordination, visible notion and data fusion. Dr. Bloisi conducts analysis within the subject of melanoma and oral carcinoma prevention by automated medical picture evaluation in collaboration with specialised medical groups in Italy. As well as, Dr. Bloisi is WP3 chief of the EU H2020 SOLARIS mission, unit chief for the PRIN PNRR RETINA mission, unit chief for the PRIN 2022 AIDA mission. Since 2015, he’s the group supervisor of the SPQR robotic soccer group taking part within the RoboCup world competitions |
|
Can Lin is a grasp scholar in Information Science at Sapienza college of Rome. He holds a bachelor diploma in Laptop science and Synthetic intelligence from the identical college. He joined the SPQR group in September of 2024, specializing in duties associated to laptop imaginative and prescient. |
Lucy Smith
is Managing Editor for AIhub.
