Tackling the 3D Simulation League: an interview with Klaus Dorer and Stefan Glaser

A screenshot from the brand new simulator that will likely be trialled for a particular problem at RoboCup2025.

The annual RoboCup occasion, the place groups collect from throughout the globe to participate in competitions throughout quite a lot of leagues, will this 12 months happen in Brazil, from 15-21 July. Prematurely of kick-off, we spoke to 2 members of the RoboCup Soccer 3D Simulation League: Government Committee Member Klaus Dorer, and Stefan Glaser, who’s on the Upkeep Committee and who has been just lately growing a brand new simulator for the League.

Might begin by simply giving us a fast introduction to the Simulation League?
Klaus Dorer: There are two Simulation Leagues in Soccer: the 2D Simulation League and the 3D Simulation League. The 2D Simulation League, because the identify suggests, is a flat league the place the gamers and ball are simulated with simplified physics and the principle focus is on crew technique. The 3D Simulation League is way nearer to actual robots; it simulates 11 versus 11 Nao robots. The extent of management is like with actual robots, the place you progress every motor of the legs and the arms and so forth to attain motion.

I perceive that you’ve got been engaged on a brand new simulator for the 3D League. What was the thought behind this new simulator?
Klaus: The goal is to carry us nearer to the {hardware} leagues in order that the simulator could be extra helpful. The present simulator that we use within the 3D Simulation League is known as SimSpark. It was created within the early 2000s with the goal of constructing it attainable to play 11 vs 11 gamers. With the {hardware} constraints of that point, there needed to be some compromises on the physics to have the ability to simulate 22 gamers on the similar time. So the simulation is bodily considerably life like, however not within the sense that it’s straightforward to transpose it to an actual Nao robotic.

Stefan Glaser: The thought for growing a brand new simulator has been round for just a few years. SimSpark is a really highly effective simulation framework. The bottom framework is area impartial (not soccer particular) and particular simulations are realized through plugins. It helps a number of physics engines within the backend and supplies a versatile scripting interface for configuration and diversifications of the simulation. Nevertheless, all this flexibility comes with the worth of complexity. Along with that, SimSpark makes use of customized robotic mannequin specs and communication protocols, limiting the quantity of obtainable robotic fashions and requiring groups to develop customized communication layers just for speaking with SimSpark. Because of this, SimSpark has not been extensively adopted within the RoboCup group.

With the brand new simulator, I wish to tackle these two main points: complexity and standardization. Within the ML group, the MuJoCo physics engine has change into a very talked-about alternative for studying environments after Google DeepMind acquired it and launched it open supply. Its requirements for world and robotic mannequin specs are extensively adopted in the neighborhood and there exist lots of ready-to-use robotic mannequin specs for all kinds of digital in addition to real-world robots. In the midst of final 12 months, they (MuJoCo) added a characteristic which lets you manipulate the world illustration throughout simulation (including and eradicating objects to / from the simulation whereas preserving the simulation state). That is one important requirement we now have within the simulation league, the place we begin with an empty subject after which the brokers join on demand and kind the groups. When this characteristic has been added, I made a decision to make a step ahead and attempt to implement a brand new simulator for the 3D Simulation League primarily based on MuJoCo. Initially, I needed to begin improvement in C/C++ to attain most efficiency, however then determined to begin in Python to scale back complexity and make it extra accessible for different builders. I began improvement on Easter Monday so it’s not even three months previous!

I feel it is perhaps helpful to elucidate a little bit bit extra concerning the setup of our league and the necessities of the simulator. If we take the FIFA sport (in your favourite gaming gadget) for instance, there may be one simulation occurring which simulates 22 gamers and the choice making is a part of the simulation having full entry to the state of the world. Within the 3D Simulation League we now have two groups with 11 robots on the sphere, however we even have 22 particular person agent softwares that are linked to the simulation server, every controlling one single robotic. Every linked agent solely receives sensor info associated to their robotic within the simulation. They’re additionally solely allowed to speak through the server – there is no such thing as a direct communication between the brokers allowed in Simulation League. So we now have a basic setup the place the simulation server has to have the ability to settle for as much as 22 connections and handle the scenario there. This performance has been the most important focus for me for the final couple of months and this half is already working nicely. Groups can join their brokers, which is able to obtain sensor info and might actuate joints of the robotic within the simulation and so forth. They’re additionally capable of choose completely different robotic fashions in the event that they like.

An illustration of the simulator set-up.

Presumably the brand new simulator has a greater illustration of the physics of an actual robotic.
Klaus: Precisely. For instance, how the motors are managed is now a bit completely different and far nearer to actual robots. So after I did my first experiments, I noticed the robotic collapse and I assumed it was precisely how an actual robotic would collapse! In SimSpark we additionally had falling robots however the motor management within the new simulator is completely different. Now you possibly can management the motors by pace, by pressure, by place, which is far more versatile – it’s nearer to what we all know from actual robots.

I feel that, a minimum of initially, it is going to be harder for the Simulation League groups to get the robots to do what they need them to do, as a result of it’s extra life like. For instance, in SimSpark the bottom contact was far more forgiving. So should you step exhausting on the bottom, you don’t fall instantly with a SimSpark robotic however with a MuJoCo robotic this will likely be far more life like. Certainly, in actual robots floor contact is considerably much less forgiving.

I had a query concerning the imaginative and prescient facet – how do the person brokers “see” the place of the opposite brokers on the sphere?
Stefan: We simulate a digital imaginative and prescient pipeline on the server aspect. You’ve gotten a restricted subject of view of ±60° horizontally and vertically. Inside that subject of view you’ll detect the pinnacle, the arms, the toes of different gamers, or the ball, for instance, or completely different options of the sphere. Much like frequent real-world imaginative and prescient pipelines, every detection consists of a label, a path vector and the gap info. The data has some noise on it like actual robots have, too, however groups don’t must course of digicam photographs. They get the detections immediately from the simulation server.

We’ve beforehand had a dialogue about shifting in the direction of getting digicam photographs of the simulation to combine into the imaginative and prescient pipeline on the agent aspect. This was by no means actually life like in SimSpark with the implementation we had there. Nevertheless, it ought to be attainable with MuJoCo. Nevertheless, for the primary model, I used the identical means the normal simulator handled the imaginative and prescient. Which means that groups don’t want to coach a imaginative and prescient mannequin, and don’t must deal with digicam photographs to get began. This reduces the load considerably and likewise shifts the main target of the issue in the direction of movement and resolution making.

Will the simulator be used at RoboCup 2025?
Stefan: We plan to have a problem with a brand new simulator and I’ll attempt to present some demo video games. In the mean time it’s probably not in a state the place you possibly can play a complete competitors.

Klaus: That’s normally how we proceed with new simulators. We’d not transfer from one to the opposite with none intermediate step. We could have a problem this 12 months at RoboCup 2025 with the brand new MuJoCo simulator the place every collaborating crew will attempt to train the robotic to kick so far as attainable. So, we won’t be taking part in a complete sport, we gained’t have a number of robots, only a single robotic stepping in entrance of the ball and kicking the ball. That’s the technical problem for this 12 months. Groups will get an thought of how the simulator works, and we’ll get an thought of what must be modified within the simulator to proceed.

This new problem will likely be voluntary, so we aren’t positive what number of groups will take part. Our crew (MagmaOffenburg) will definitely participate. Will probably be fascinating to see how nicely the groups carry out as a result of nobody is aware of how far a great kick is on this simulator. It’s a bit like in Formulation One when the foundations change and nobody is aware of which crew would be the main crew.

Do you might have an thought of how a lot adaptation groups must make if and once you transfer to the brand new simulator for the complete matches?
Stefan: As a long-term member of 3D Simulation League, I do know the previous simulator SimSpark fairly nicely, and know the protocols concerned and the way the processes work. So the primary model of the brand new simulator is designed to make use of the identical fundamental protocol, the identical sensor info, and so forth. The thought is that the groups can use the brand new simulator with minimal effort in adapting their present agent software program. So they need to be capable of get began fairly quick.

Though, when designing a brand new platform, I wish to take the chance to make a step ahead by way of protocols, as a result of I additionally need to combine different Leagues within the long-term. They normally produce other management mechanisms, and so they don’t use the identical protocol that’s distinguished in 3D Simulation. Subsequently there must be some flexibility sooner or later. However for the primary model, the thought was to get the Simulation League prepared with minimal effort.

Klaus: The large thought is that this isn’t simply used within the 3D Simulation league, but in addition as a helpful simulator for the Humanoid League and likewise for the Normal Platform League (SPL). So if that seems to be true, then it is going to be fully profitable. For the Kick Problem this 12 months, for instance, we use a T1 robotic that could be a Humanoid League robotic.

Might you say one thing about this simulation to actual world (Sim2Real) facet?
Stefan: We’d prefer it to be attainable for the motions and behaviors within the simulator to be ported to actual robots. From my viewpoint, it might be helpful the opposite means spherical too.

We, as a Simulation League, normally develop for the Simulation League and due to this fact wish to get the behaviors working on an actual robotic. However the {hardware} groups normally have the same problem once they need to check high-level resolution making. They could have two to 5 robots on the sphere, and in the event that they need to play a high-level decision-making match and prepare in that regard, they all the time must deploy lots of robots. If in addition they need to have an opponent, they must double the quantity of robots with the intention to play a sport to see how the technique would end up. The Sim2Real facet can also be fascinating for these groups, as a result of they need to be capable of take what they deployed on the true robotic and it must also work within the simulation. They’ll then use the simulation to coach high-level expertise like crew play, participant positioning and so forth, which is a difficult facet for the true robotic leagues like SPL or the Humanoid Leagues.

Klaus: And the rationale we all know it is because we now have a crew within the Simulation League and we now have a crew within the Humanoid League. In order that’s one more reason why we’re eager to carry this stuff nearer collectively.

How does the refereeing work within the Simulation League?
Klaus: A pleasant factor about Simulation Leagues is that there’s a program which is aware of the true state of the world so we are able to construct within the referee contained in the simulator and it’ll not fail. For issues like offside, whether or not the ball handed the aim line, that’s fail protected. All of the referee selections are taken by the system itself. Now we have a human referee however they by no means must intervene. Nevertheless, there are conditions the place we wish synthetic intelligence to play a job. This isn’t at present the case in SimSpark as a result of the foundations are all exhausting coded. Now we have lots of fouls which can be debatable. For instance, there are various fouls that groups agree mustn’t have been a foul, and different fouls that aren’t known as that ought to have been. It will be a pleasant AI studying job to get some conditions judged by human referees after which prepare an AI mannequin to higher decide the foundations for what’s a foul and what isn’t a foul. However that is at present not the case.

Stefan: On the brand new simulator I’m not that far into the event that I’ve applied the automated referee but. I’ve some fundamental algorithm which progress the sport as such, however judging fouls and deciding on particular conditions just isn’t but applied within the new simulator.

What are the subsequent steps for growing the simulator?
Stefan: One of many subsequent main steps will likely be to refine the physics simulation. For example, despite the fact that there exists a ball within the simulation, it isn’t but very well refined. There are lots of physics parameters which we now have to resolve on to mirror the true world nearly as good as attainable. This may doubtless require a collection of experiments with the intention to get to the right values for varied elements. On this facet I’m hoping for some engagement of the group, as it’s a nice analysis alternative and I personally would like the group to resolve on a generally accepted parameter set primarily based on a degree of proof that I can’t simply present all on my own. So in case somebody is all in favour of refining the physics of the simulation such that it greatest displays the true world, you’re welcome to affix!

One other main subsequent step would be the improvement of the automated referee of the soccer simulation, deciding on fouls, dealing with misbehaving brokers and so forth. Within the first model, foul situations will doubtless be judged by an professional system particularly designed for this objective. The simulation league has developed a set of foul situation specs which I plan to adapt. In a second step, I wish to combine and help the event of AI primarily based foul detection fashions. However yeah, one step after the opposite.

What are you significantly trying ahead to at RoboCup2025?
Klaus: Properly, with our crew we now have been vice world champion seven instances in a row. This 12 months we’re actually hoping to make it to world champion. We’re very skilled in getting losses in finals and this 12 months we’re trying ahead to altering that, from a crew perspective.

Stefan: I’m going to Brazil with the intention to promote the simulator, not only for the Simulation League, but in addition throughout the boundaries for the Humanoid Leagues and the SPL Leagues. I feel that this simulator is a superb probability to carry individuals from all of the leagues collectively. I’m significantly within the particular necessities of all of the groups of the completely different leagues. This understanding will assist me tailor the brand new simulator in the direction of their wants. That is considered one of my main highlights for this 12 months, I’d say.

You could find out extra concerning the new simulator on the mission webpage, and from the documentation.

Klaus Dorer is professor for synthetic intelligence, autonomous techniques and software program engineering at Offenburg College, Germany. He’s additionally a member of the Institute for Machine Studying and Analytics IMLA. He has been crew chief of the RoboCup simulation league groups magmaFreiburg (since 1999), dwelling techniques, magmaFurtwangen and is now crew chief of magmaOffenburg since 2009. Since 2014, he has additionally been a part of the humanoid grownup dimension league crew Sweaty.

Stefan Glaser is educating assistant for synthetic intelligence and clever autonomous techniques on the Offenburg College, Germany. He has been a part of the RoboCup simulation league crew magmaOffenburg since 2009 and the RoboCup humanoid grownup dimension league crew Sweaty since 2014.