An interview with Nicolai Ommer: the RoboCupSoccer Small Dimension League

Kick-off in a Small Dimension League match. Picture credit score: Nicolai Ommer.

RoboCup is a global scientific initiative with the aim of advancing the cutting-edge of clever robots, AI and automation. The annual RoboCup occasion is because of happen from 15-21 July in Salvador, Brazil. The Soccer element of RoboCup contains numerous Leagues, with certainly one of these being the Small Dimension League (SSL). We caught up with Govt Committee member Nicolai Ommer to seek out out extra concerning the SSL, how the auto referees work, and the way groups use AI.

May begin by giving us a fast introduction to the Small Dimension League?

Within the Small Dimension League (SSL) we’ve got 11 robots per group – the one bodily RoboCup soccer league to have the complete variety of gamers. The robots are small, cylindrical robots on wheels and so they can transfer in any path. They’re self-built by the groups, so groups should do each the {hardware} and the programming, and a variety of issues should work collectively to make a group work. The AI is central. We don’t have brokers, so groups have a central laptop on the subject the place they’ll do all of the computation after which they ship the instructions to the robots in numerous abstractions. Some groups will simply ship velocity instructions, different groups ship a goal.

We now have a central imaginative and prescient system – that is maintained by the League, and has been since 2010. There are cameras above the sector to trace all of the robots and the ball, so everybody is aware of the place the robots are.

The robots can transfer as much as 4 meters per second (m/s), after this level it will get fairly unstable for the robots. They will change path in a short time, and the ball may be kicked at 6.5 m/s. It’s fairly quick and we’ve already needed to restrict the kick pace. Beforehand we had a restrict of 8 m/s and earlier than that 10m/s. Nonetheless, no robotic can catch a ball with this pace, so we determined to scale back it and put extra concentrate on passing. This provides the keeper and the defenders an opportunity to really intercept a kick.

It’s so quick that for people it’s fairly obscure all of the issues which are happening. And that’s why, some years in the past, we launched auto refs, which assist so much in monitoring, particularly issues like collisions and so forth, the place the human referee can’t watch the whole lot on the similar time.

How do the auto refs work then, and is there a couple of working on the similar time?

Once we developed the present system, to maintain issues truthful, we determined to have a number of implementations of an auto ref system. These impartial techniques implement the identical guidelines after which we do a majority vote on the choices.

To do that we would have liked a center element, so some years in the past I began this undertaking to have a brand new sport controller. That is the person interface (UI) for the human referee who sits at a pc. Within the UI you see the present sport state, you’ll be able to manipulate the sport state, and this element coordinates the auto refs. The auto refs can join and report fouls. If just one auto ref detects the foul, it received’t rely it. However, if each auto refs report the foul inside the time window, then it’s counted. A part of the problem was to make this all visible for the operator to know. The human referee has the final phrase and makes the ultimate resolution.

We managed to ascertain two implementations. The goal was to have three implementations, which makes it simpler to type a majority. Nonetheless, it nonetheless works with simply two implementations and we’ve had this for a number of years now. The implementations are from two completely different groups who’re nonetheless energetic.

How do the auto refs cope with collisions?

We are able to detect collisions from the info. Nonetheless, even for human referees it’s fairly exhausting to find out who was at fault when two robots collide. So we needed to simply outline a rule, and all of the implementations of the auto ref implement the identical rule. We wrote within the rulebook actually particularly the way you calculate if a collision occurred and who was at fault. The primary consideration relies on the rate – beneath 1.5m/s it’s not a collision, above 1.5m/s it’s. There’s additionally one other issue, referring to the angle calculation, that we additionally take note of to find out which robotic was at fault.

What else do the auto refs detect?

Different fouls embody the kick pace, after which there’s fouls referring to the adherence to regular sport process. For instance, when the opposite group has a free kick, then the opposing robots ought to preserve a sure distance from the ball.

The auto refs additionally observe non-fouls, in different phrases sport occasions. For instance, when the ball leaves the sector. That’s the commonest occasion. This one is definitely not really easy to detect, significantly if there’s a chip kick (the place the ball leaves the taking part in floor). With the digital camera lens, the parabola of the ball could make it seem like it’s outdoors the sector of play when it isn’t. You want a sturdy filter to cope with this.

Additionally, when the auto refs detect a aim, we don’t belief them fully. When a aim is detected, we name it a “potential aim”. The match is halted instantly, all of the robots cease, and the human referee can test all of the accessible information earlier than awarding the aim.

You’ve been concerned within the League for numerous years. How has the League and the efficiency of the robots advanced over that point?

My first RoboCup was in 2012. The introduction of the auto refs has made the play much more fluent. Earlier than this, we additionally launched the idea of ball placement, so the robots would place the ball themselves for a free kick, or kick off, for instance.

From the {hardware} facet, the principle enchancment lately has been dribbling the ball in one-on-one conditions. There has additionally been an enchancment within the specialised expertise carried out by robots with a ball. For instance, some years in the past, one group (ZJUNlict) developed robots that would pull the ball backwards with them, transfer round defenders after which shoot on the aim. This was an sudden motion, which we hadn’t seen earlier than. Earlier than this you needed to do a move to trick the defenders. Our group, TIGERs Mannheim, has additionally improved on this space now. Nevertheless it’s actually tough to do that and requires a variety of tuning. It actually is determined by the sector, the carpet, which isn’t standardized. So there’s somewhat little bit of luck that your particularly constructed {hardware} is definitely performing effectively on the competitors carpet.

The Small Dimension League Grand Ultimate at RoboCup 2024 in Eindhoven, Netherlands. TIGERs Mannheim vs. ZJUNlict. Video credit score: TIGERs Mannheim. You will discover the TIGERs’ YouTube channel right here.

What are among the challenges within the League?

One massive problem, and in addition perhaps it’s factor for the League, is that we’ve got a variety of undergraduate college students within the groups. These college students have a tendency to go away the groups after their Bachelor’s or Grasp’s diploma, the group members all change fairly usually, and that signifies that it’s tough to retain data within the groups. It’s a problem to maintain the efficiency of the group; it’s even exhausting to breed what earlier members achieved. That’s why we don’t have massive steps ahead, as a result of groups should repeat the identical issues when new members be part of. Nonetheless, it’s good for the scholars as a result of they actually study so much from the expertise.

We’re constantly engaged on figuring out issues which we are able to make accessible for everybody. In 2010 the imaginative and prescient system was established. It was an enormous issue, which means that groups didn’t should do laptop imaginative and prescient. And we’re at present taking a look at establishing requirements for wi-fi communication – that is at present completed by everybody on their very own. We need to advance the League, however on the similar time, we additionally need to have this nature of having the ability to study, having the ability to do all of the issues themselves in the event that they need to.

You really want to have a group of individuals from completely different areas – mechanical engineering, electronics, undertaking administration. You additionally should get sponsors, and it’s important to promote your undertaking, get college students in your group.

May you discuss among the AI parts to the League?

Most of our software program is script-based, however we apply machine studying for small, refined issues.

In my group, for instance, we do mannequin calibration with fairly easy algorithms. We now have a selected mannequin for the chip kick, and one other for the robotic. The wheel friction is kind of difficult, so we provide you with a mannequin after which we accumulate the info and use machine studying to detect the parameters.

For the precise match technique, one good instance is from the group CMDragons. One 12 months you possibly can actually observe that they’d skilled their mannequin in order that, as soon as they scored aim, they upvoted the technique that they utilized earlier than that. You can actually see that the opponent reacted the identical means on a regular basis. They had been in a position to rating a number of objectives, utilizing the identical technique repeatedly, as a result of they realized that if one technique labored, they may use it once more.

For our group, the TIGERs, our software program could be very a lot based mostly on calculating scores for the way good a move is, how effectively can a move be intercepted, and the way we are able to enhance the state of affairs with a specific move. That is hard-coded generally, with some geometry-based calculations, however there may be additionally some fine-tuning. If we rating a aim then we monitor again and see the place the move got here from and we give bonuses on among the rating calculations. It’s extra difficult than this, after all, however typically it’s what we attempt to do by studying in the course of the sport.

Folks typically ask why we don’t do extra with AI, and I believe the principle problem is that, in comparison with different use instances, we don’t have that a lot information. It’s exhausting to get the info. In our case we’ve got actual {hardware} and we can’t simply do matches all day lengthy for days on finish – the robots would break, and so they have to be supervised. Throughout a contest, we solely have about 5 to seven matches in whole. In 2016, we began to file all of the video games with a machine-readable format. All of the positions are encoded, together with the referee selections, and the whole lot is in a log file which we publish centrally. I hope that with this rising quantity of knowledge we are able to truly apply some machine studying algorithms to see what earlier matches and former methods did, and perhaps get some insights.

What plans do you may have to your group, the TIGERs?

We now have truly received the competitors for the final 4 years. We hope that there will probably be another groups who can problem us. Our defence has not likely been challenged so we’ve got a tough time discovering weaknesses. We truly play in opposition to ourselves in simulation.

One factor that we need to enhance on is precision as a result of there may be nonetheless some guide work to get the whole lot calibrated and dealing as exactly as we would like it. If some small element is just not working, for instance the dribbling, then it dangers the entire event. So we’re engaged on making all these calibration processes simpler, and to do extra automated information processing to find out the perfect parameters. In recent times we’ve labored so much on dribbling within the 1 vs 1 conditions. This has been a very massive enchancment for us and we’re nonetheless engaged on that.

About Nicolai

Nicolai Ommer is a Software program Engineer and Architect at QAware in Munich, specializing in designing and constructing sturdy software program techniques. He holds a B.Sc. in Utilized Pc Science and an M.Sc. in Autonomous Techniques. Nicolai started his journey in robotics with Crew TIGERs Mannheim, collaborating in his first RoboCup in 2012. His dedication led him to hitch the RoboCup Small Dimension League Technical Committee and, in 2023, the Govt Committee. Keen about innovation and collaboration, Nicolai combines tutorial perception with sensible expertise to push the boundaries of clever techniques and contribute to the worldwide robotics and software program engineering communities.