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 a lot of leagues, will this 12 months happen in Brazil, from 15-21 July. Upfront of kick-off, we spoke to 2 members of the RoboCup Soccer 3D Simulation League: Govt Committee Member Klaus Dorer, and Stefan Glaser, who’s on the Upkeep Committee and who has been not too long ago creating 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 primary focus is on workforce 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 been engaged on a brand new simulator for the 3D League. What was the thought behind this new simulator?
Klaus: The purpose is to convey us nearer to the {hardware} leagues in order that the simulator might 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 purpose of creating it potential 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 practical, however not within the sense that it’s straightforward to transpose it to an actual Nao robotic.

Stefan Glaser: The concept for creating 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 by way of plugins. It helps a number of physics engines within the backend and offers a versatile scripting interface for configuration and diversifications of the simulation. Nonetheless, all this flexibility comes with the value of complexity. Along with that, SimSpark makes use of customized robotic mannequin specs and communication protocols, limiting the quantity of accessible 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 want to tackle these two main points: complexity and standardization. Within the ML group, the MuJoCo physics engine has grow to be a very fashionable 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 a number of ready-to-use robotic mannequin specs for all kinds of digital in addition to real-world robots. In the course of final 12 months, they (MuJoCo) added a function 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’ve within the simulation league, the place we begin with an empty area after which the brokers join on demand and kind the groups. When this function 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 growth 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 growth on Easter Monday so it’s not even three months previous!

I believe it is likely to be helpful to clarify a 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 example, there’s 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’ve 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 by way of the server – there isn’t a direct communication between the brokers allowed in Simulation League. So we’ve a common setup the place the simulation server has to have the ability to settle for as much as 22 connections and handle the state of affairs 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 can obtain sensor info and may 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 may management the motors by velocity, by power, by place, which is rather more versatile – it’s nearer to what we all know from actual robots.

I believe that, not less than initially, it will likely 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 practical. For instance, in SimSpark the bottom contact was rather more forgiving. So should you step onerous on the bottom, you don’t fall instantly with a SimSpark robotic however with a MuJoCo robotic this will likely be rather more practical. Certainly, in actual robots floor contact is considerably much less forgiving.

I had a query concerning the imaginative and prescient side – 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 a restricted area of view of ±60° horizontally and vertically. Inside that area of view you’ll detect the top, the arms, the ft of different gamers, or the ball, for instance, or completely different options of the sphere. Much like widespread real-world imaginative and prescient pipelines, every detection consists of a label, a course vector and the gap info. The knowledge has some noise on it like actual robots have, too, however groups don’t have to course of digicam photographs. They get the detections instantly 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 practical in SimSpark with the implementation we had there. Nonetheless, it must be potential with MuJoCo. Nonetheless, for the primary model, I used the identical means the standard simulator handled the imaginative and prescient. Which means groups don’t want to coach a imaginative and prescient mannequin, and don’t have to deal with digicam photographs to get began. This reduces the load considerably and in addition shifts the main target of the issue in the direction of movement and determination 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 meanwhile it’s probably not in a state the place you may play a complete competitors.

Klaus: That’s often 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 workforce will attempt to educate the robotic to kick so far as potential. 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’re not certain what number of groups will take part. Our workforce (MagmaOffenburg) will definitely participate. It is going to be attention-grabbing to see how nicely the groups carry out as a result of nobody is aware of how far a very good kick is on this simulator. It’s a bit like in Method One when the foundations change and nobody is aware of which workforce would be the main workforce.

Do you’ve 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 primary protocol, the identical sensor info, and so forth. The concept 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 want to take the chance to make a step ahead by way of protocols, as a result of I additionally wish to combine different Leagues within the long-term. They often 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 massive thought is that this isn’t simply used within the 3D Simulation league, but additionally as a helpful simulator for the Humanoid League and in addition for the Normal Platform League (SPL). So if that seems to be true, then it will likely 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) side?
Stefan: We’d prefer it to be potential for the motions and behaviors within the simulator to be ported to actual robots. From my perspective, it might be helpful the opposite means spherical too.

We, as a Simulation League, often develop for the Simulation League and subsequently want to get the behaviors operating on an actual robotic. However the {hardware} groups often have an analogous subject once they wish to check high-level determination making. They could have two to 5 robots on the sphere, and in the event that they wish to play a high-level decision-making match and practice in that regard, they all the time should deploy a number of robots. If in addition they wish to have an opponent, they should double the quantity of robots with a purpose to play a sport to see how the technique would end up. The Sim2Real side can be attention-grabbing for these groups, as a result of they need to be capable of take what they deployed on the true robotic and it also needs to work within the simulation. They’ll then use the simulation to coach high-level expertise like workforce play, participant positioning and so forth, which is a difficult side for the true robotic leagues like SPL or the Humanoid Leagues.

Klaus: And the rationale we all know it is because we’ve a workforce within the Simulation League and we’ve a workforce within the Humanoid League. In order that’s another excuse why we’re eager to convey these items 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 objective line, that’s fail protected. All of the referee choices are taken by the system itself. We’ve got a human referee however they by no means have to intervene. Nonetheless, 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 onerous coded. We’ve got a number of fouls which might 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 might be a pleasant AI studying job to get some conditions judged by human referees after which practice an AI mannequin to raised 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 primary algorithm which progress the sport as such, however judging fouls and deciding on particular conditions will not be but applied within the new simulator.

What are the subsequent steps for creating the simulator?
Stefan: One of many subsequent main steps will likely be to refine the physics simulation. For example, although there exists a ball within the simulation, it isn’t but very well refined. There are a number of physics parameters which we’ve to resolve on to replicate the true world nearly as good as potential. This may probably require a sequence of experiments with a purpose to get to the proper values for numerous facets. On this side I’m hoping for some engagement of the group, as it’s a nice analysis alternative and I personally would favor the group to resolve on a generally accepted parameter set primarily based on a stage of proof that I can’t simply present all on my own. So in case somebody is taken with refining the physics of the simulation such that it finest displays the true world, you might be welcome to hitch!

One other main subsequent step would be the growth 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 probably be judged by an skilled system particularly designed for this goal. The simulation league has developed a set of foul situation specs which I plan to adapt. In a second step, I want 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: Nicely, with our workforce we’ve 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 workforce perspective.

Stefan: I’m going to Brazil with a purpose to promote the simulator, not only for the Simulation League, but additionally throughout the boundaries for the Humanoid Leagues and the SPL Leagues. I believe that this simulator is a superb likelihood to convey 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 one in every of my main highlights for this 12 months, I’d say.

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

Klaus Dorer is professor for synthetic intelligence, autonomous methods 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 workforce chief of the RoboCup simulation league groups magmaFreiburg (since 1999), residing methods, magmaFurtwangen and is now workforce chief of magmaOffenburg since 2009. Since 2014, he has additionally been a part of the humanoid grownup measurement league workforce Sweaty.

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