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

A screenshot from the brand new simulator that might 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 yr 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 lately 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 group 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 intention is to carry us nearer to the {hardware} leagues in order that the simulator may be extra helpful. The present simulator that we use within the 3D Simulation League is named SimSpark. It was created within the early 2000s with the intention of creating 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 real looking, however not within the sense that it’s simple to transpose it to an actual Nao robotic.

Stefan Glaser: The thought for creating a brand new simulator has been round for a number of 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 variations of the simulation. Nonetheless, 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 accessible robotic fashions and requiring groups to develop customized communication layers just for speaking with SimSpark. On account of this, SimSpark has not been extensively adopted within the RoboCup group.

With the brand new simulator, I want to handle these two main points: complexity and standardization. Within the ML group, the MuJoCo physics engine has turn into 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 locally and there exist a whole lot of ready-to-use robotic mannequin specs for all kinds of digital in addition to real-world robots. In the course of final yr, 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’ve got 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 wished 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 feel it is perhaps 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 machine) for example, 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’ve got two groups with 11 robots on the sector, 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 got a normal 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 main focus for me for the final couple of months and this half is already working properly. 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 totally 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 totally different and far nearer to actual robots. So once 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 totally different. Now you’ll be able to management the motors by velocity, by pressure, by place, which is way more versatile – it’s nearer to what we all know from actual robots.

I feel that, at the very least initially, it will likely be tougher for the Simulation League groups to get the robots to do what they need them to do, as a result of it’s extra real looking. For instance, in SimSpark the bottom contact was way more forgiving. So if you happen to step laborious on the bottom, you don’t fall instantly with a SimSpark robotic however with a MuJoCo robotic this might be way more real looking. 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 sector?
Stefan: We simulate a digital imaginative and prescient pipeline on the server aspect. You will have 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 totally different options of the sector. Just like frequent real-world imaginative and prescient pipelines, every detection consists of a label, a course vector and the space 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 straight from the simulation server.

We’ve beforehand had a dialogue about transferring 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 real looking in SimSpark with the implementation we had there. Nonetheless, it needs to be attainable with MuJoCo. Nonetheless, for the primary model, I used the identical manner the normal simulator handled the imaginative and prescient. Because of this 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 in addition shifts the main focus of the issue in the direction of movement and choice 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 not likely in a state the place you’ll be able to 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 yr at RoboCup 2025 with the brand new MuJoCo simulator the place every taking part group will attempt to educate the robotic to kick so far as attainable. So, we won’t be taking part in a complete sport, we received’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 yr. Groups will get an thought of how the simulator works, and we’ll get an thought of what needs to be modified within the simulator to proceed.

This new problem might be voluntary, so we’re not positive what number of groups will take part. Our group (MagmaOffenburg) will definitely participate. Will probably be attention-grabbing to see how properly the groups carry out as a result of nobody is aware of how far a superb kick is on this simulator. It’s a bit like in Components One when the principles change and nobody is aware of which group would be the main group.

Do you’ve gotten an thought of how a lot adaptation groups should make if and whenever 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 properly, 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 to 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 outstanding in 3D Simulation. Subsequently there needs to 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 in addition as a helpful simulator for the Humanoid League and in addition for the Commonplace Platform League (SPL). So if that seems to be true, then it will likely be utterly profitable. For the Kick Problem this yr, for instance, we use a T1 robotic that may 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 attainable for the motions and behaviors within the simulator to be ported to actual robots. From my viewpoint, it could be helpful the opposite manner spherical too.

We, as a Simulation League, often develop for the Simulation League and due to this fact want to get the behaviors operating on an actual robotic. However the {hardware} groups often have an identical subject after they wish to check high-level choice making. They could have two to 5 robots on the sector, and in the event that they wish to play a high-level decision-making match and prepare in that regard, they at all times need to deploy a whole lot of robots. If additionally they wish to have an opponent, they need to double the quantity of robots so as to play a sport to see how the technique would end up. The Sim2Real side can also be attention-grabbing for these groups, as a result of they need to be capable to take what they deployed on the actual robotic and it also needs to work within the simulation. They’ll then use the simulation to coach high-level abilities like group play, participant positioning and so forth, which is a difficult side for the actual robotic leagues like SPL or the Humanoid Leagues.

Klaus: And the explanation we all know it is because we’ve got a group within the Simulation League and we’ve got a group within the Humanoid League. In order that’s one more reason why we’re eager to carry 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 actual 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 secure. All of the referee choices are taken by the system itself. We now have a human referee however they by no means must intervene. Nonetheless, there are conditions the place we want synthetic intelligence to play a job. This isn’t presently the case in SimSpark as a result of the principles are all laborious coded. We now have a whole lot of fouls which are 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 could be a pleasant AI studying job to get some conditions judged by human referees after which prepare an AI mannequin to raised decide the principles for what’s a foul and what isn’t a foul. However that is presently not the case.

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

What are the following steps for creating the simulator?
Stefan: One of many subsequent main steps might be to refine the physics simulation. As an example, regardless that there exists a ball within the simulation, it’s not but very well refined. There are a whole lot of physics parameters which we’ve got to determine on to mirror the actual world pretty much as good as attainable. It will possible require a sequence of experiments so as 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 determine 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 inquisitive about refining the physics of the simulation such that it finest displays the actual 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 possible be judged by an knowledgeable 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 assist the event of AI primarily based foul detection fashions. However yeah, one step after the opposite.

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

Stefan: I’m going to Brazil so as 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 likelihood to carry folks from all of the leagues collectively. I’m notably within the particular necessities of all of the groups of the totally different leagues. This understanding will assist me tailor the brand new simulator in the direction of their wants. That is certainly one of my main highlights for this yr, I might say.

You will discover out extra concerning the new simulator on the undertaking webpage, and from the documentation.

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

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