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 part of RoboCup contains a variety of Leagues, with certainly one of these being the Small Dimension League (SSL). We caught up with Govt Committee member Nicolai Ommer to search out out extra in regards to the SSL, how the auto referees work, and the way groups use AI.

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

Within the Small Dimension League (SSL) we have now 11 robots per staff – the one bodily RoboCup soccer league to have the complete variety of gamers. The robots are small, cylindrical robots on wheels they usually can transfer in any course. They’re self-built by the groups, so groups should do each the {hardware} and the programming, and loads of issues should work collectively to make a staff work. The AI is central. We don’t have brokers, so groups have a central pc on the subject the place they will 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’ve got 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 course in a short time, and the ball might be kicked at 6.5 m/s. It’s fairly quick and we’ve already needed to restrict the kick velocity. Beforehand we had a restrict of 8 m/s and earlier than that 10m/s. Nonetheless, no robotic can catch a ball with this velocity, so we determined to cut back it and put extra give attention to passing. This provides the keeper and the defenders an opportunity to truly 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 every little thing on the similar time.

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

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

To do that we would have liked a center part, so some years in the past I began this venture to have a brand new sport controller. That is the consumer interface (UI) for the human referee who sits at a pc. Within the UI you see the present sport state, you possibly can manipulate the sport state, and this part 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 determination.

We managed to determine 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 totally different groups who’re nonetheless lively.

How do the auto refs cope with collisions?

We will detect collisions from the info. Nonetheless, even for human referees it’s fairly arduous 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 speed – 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 into consideration to find out which robotic was at fault.

What else do the auto refs detect?

Different fouls embrace the kick velocity, after which there’s fouls referring to the adherence to regular sport process. For instance, when the opposite staff 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, notably if there’s a chip kick (the place the ball leaves the enjoying floor). With the digicam 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 strong 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 examine all of the out there knowledge earlier than awarding the aim.

You’ve been concerned within the League for a variety of years. How has the League and the efficiency of the robots developed 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} aspect, the primary enchancment lately has been dribbling the ball in one-on-one conditions. There has additionally been an enchancment within the specialised abilities carried out by robots with a ball. For instance, some years in the past, one staff (ZJUNlict) developed robots that would pull the ball backwards with them, transfer round defenders after which shoot on the aim. This was an surprising motion, which we hadn’t seen earlier than. Earlier than this you needed to do a cross to trick the defenders. Our staff, TIGERs Mannheim, has additionally improved on this space now. Nevertheless it’s actually troublesome to do that and requires loads of tuning. It actually relies on the sector, the carpet, which isn’t standardized. So there’s a bit little bit of luck that your particularly constructed {hardware} is definitely performing properly on the competitors carpet.

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

What are a number of the challenges within the League?

One huge problem, and in addition possibly it’s a great factor for the League, is that we have now loads of undergraduate college students within the groups. These college students have a tendency to depart the groups after their Bachelor’s or Grasp’s diploma, the staff members all change fairly recurrently, and that signifies that it’s troublesome to retain data within the groups. It’s a problem to maintain the efficiency of the staff; it’s even arduous 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 be taught so much from the expertise.

We’re constantly engaged on figuring out issues which we will make out there for everybody. In 2010 the imaginative and prescient system was established. It was an enormous issue, that means that groups didn’t should do pc imaginative and prescient. And we’re presently taking a look at establishing requirements for wi-fi communication – that is presently performed by everybody on their very own. We wish to advance the League, however on the similar time, we additionally wish to have this nature of with the ability to be taught, with the ability to do all of the issues themselves in the event that they wish to.

You really want to have a staff of individuals from totally different areas – mechanical engineering, electronics, venture administration. You additionally should get sponsors, and it’s a must to promote your venture, get college students in your staff.

Might you discuss a number of the AI components to the League?

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

In my staff, for instance, we do mannequin calibration with fairly easy algorithms. We’ve got a particular mannequin for the chip kick, and one other for the robotic. The wheel friction is kind of difficult, so we give you a mannequin after which we acquire the info and use machine studying to detect the parameters.

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

For our staff, the TIGERs, our software program may be very a lot based mostly on calculating scores for the way good a cross is, how properly can a cross be intercepted, and the way we will enhance the state of affairs with a specific cross. That is hard-coded generally, with some geometry-based calculations, however there’s additionally some fine-tuning. If we rating a aim then we monitor again and see the place the cross got here from and we give bonuses on a number of the rating calculations. It’s extra difficult than this, in fact, however generally 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 feel the primary problem is that, in comparison with different use circumstances, we don’t have that a lot knowledge. It’s arduous to get the info. In our case we have now actual {hardware} and we can’t simply do matches all day lengthy for days on finish – the robots would break, they usually should 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 every little thing is in a log file which we publish centrally. I hope that with this rising quantity of information we will really apply some machine studying algorithms to see what earlier matches and former methods did, and possibly get some insights.

What plans do you have got in your staff, the TIGERs?

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

One factor that we wish to enhance on is precision as a result of there’s nonetheless some handbook work to get every little thing calibrated and dealing as exactly as we wish it. If some small element will not be working, for instance the dribbling, then it dangers the entire match. So we’re engaged on making all these calibration processes simpler, and to do extra computerized knowledge processing to find out the most effective parameters. Lately we’ve labored so much on dribbling within the 1 vs 1 conditions. This has been a extremely huge 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 strong 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 Staff TIGERs Mannheim, collaborating in his first RoboCup in 2012. His dedication led him to affix 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.