RoboCup@Work League: Interview with Christoph Steup

RoboCup@Work League groups on the occasion in Brazil.

RoboCup is a global scientific initiative with the purpose of advancing the state-of-the-art of clever robots, AI and automation. The annual RoboCup occasion, the place groups collect from throughout the globe to participate in competitions throughout various leagues, this 12 months came about in Salvador, Brazil from 15-21 July. In a sequence of interviews, we’ve been assembly among the RoboCup trustees, committee members, and members, to seek out out extra about their respective leagues. Christoph Steup is an Government Committee member and oversees the @Work League. Forward of the occasion in Brazil, we spoke to Christoph to seek out out extra concerning the @Work League, the duties that groups want to finish, and future plans for the League.

Might you begin by giving us an introduction to the @Work league?

The @Work League, together with the Logistics League, types the Industrial League. Our purpose is to imitate among the points of commercial manufacturing methods. An vital facet of that is manufacturing unit automization and attempting to imitate the manufacturing unit of the longer term, the place you might have autonomous robots constructing merchandise in line with buyer design. In these factories of the longer term, a single piece can be produced individually for every buyer. Factories these days have massive conveyor belts and a variety of automization, with the duties largely performed in the identical manner, and you may solely construct stuff effectively if you happen to construct tens of millions of things. We’re engaged on constructing particular person items, the place automization remains to be potential, and even a single piece could be constructed successfully. However clearly, in our RoboCup competitions, we’re not fascinated by constructing on a manufacturing unit scale – we’re doing it on a really small scale. Which means our robots are usually 80 centimeters lengthy, the biggest are round 70 centimeters broad, and a few of them are additionally 80 centimeters excessive. So let’s say they slot in a one metre cubed field. Additionally, all our operations are performed on the bottom. That is only for simplification as a result of constructing massive tables to make it extra real looking would additionally improve the fee for RoboCup and wouldn’t give a lot further worth.

What our robots must do is transport objects from completely different workstations. So we’ve a default configuration the place the world begins, and there are workstations with objects mendacity on them, and a few of these objects must be transported to different workstations. The robotic wants to do this utterly autonomously. So this is without doubt one of the particular issues concerning the @Work League, that it’s utterly autonomous and there may be solely a single restart allowed per workforce. So which means the robotic actually must be dependable. One of many massive variations between medium groups and superb groups is that the superb groups carry out nicely on a regular basis whereas the medium groups have some good runs and a few unhealthy runs.

In addition to the item transportation that you simply talked about, and there different duties that the groups want to hold out?

There are some particular duties in our league, just like the precision placement activity the place the robotic wants to suit an object right into a cavity that’s primarily the identical form and dimension as the item. It’s slightly bit like the sport that infants do to coach their dexterity.

We even have a activity that’s impressed by a conveyor belt, however we’re utilizing a desk that’s continuously turning. The robots want to understand stuff whereas the desk is popping. This seems slightly bit foolish as a result of nobody would really put a rotating desk in a manufacturing unit, nonetheless that is our manner of truly mimicking a conveyor belt. The conveyor belt itself can be actually, actually troublesome to combine into the competitors, so we simply abstracted that and use this rotating desk to really have the identical problem however in a extra manageable manner. And it’s nonetheless a really, very arduous problem.

Then there are some particular challenges that we combine. For instance, that robots must report their state again in order that we are able to observe what the robotic is doing. We even have a problem the place people are within the loop. For instance, the robotic brings items to a sure workstation the place a human is current, the human assembles the items, after which the human wants to offer an indication to the robotic, after which the robotic will take the piece away and put it someplace else. That is designed to actually mimic the automated manufacturing unit stream.

Previously we additionally had a problem the place the robots wanted to open a drawer, take one thing out after which shut the drawer once more. We’ve additionally had duties the place the robotic has to deal with fragile objects, like sweets, the place the robotic actually wanted to watch out in manipulating them. So normally, what differentiates us most from the Logistics League is that we’re focusing rather a lot on manipulation and all of the difficulties that include manipulation and unknown objects, whereas Logistics is extra tailor-made in direction of large-scale logistics processes with all their optimization and planning.

I used to be fortunate sufficient to attend RoboCup final 12 months in Eindhoven and what the groups had been doing was actually spectacular. It was additionally fascinating to see how various the robots had been, and the way groups had been approaching the duties in distinct methods, with completely different grabbers and so forth.

Sure, this distinction in approaches is said to the historical past of our League, which is slightly bit just like the Logistics League. The Logistics League was initially a sponsored demonstration by Festo, which is a big firm from Germany that creates instruments, however in addition they have a didactics space the place they supply instruments to assist folks perceive manufacturing unit optimization. The @Work League was sponsored by Kuka, the robotics firm, and, to start with, they required each workforce to compete with the Kuka youBot. So this was just about the default platform for our league, however sooner or later Kuka dropped from a sponsor to simply an advisor to the league, and these days they don’t seem to be a part of the league in any respect. So when the Kuka youBot was going out of fee, the groups looked for options and now we’re introduced with all kinds of robots which can be competing within the league, which I personally discover actually cool. Now we’ve all these completely different robots, all these completely different approaches, and a few work higher in some situations and worse in others. So we actually have a scientific method to the issue and we’re actually getting some insights into how one can sort out this drawback on a number of ranges.

Have you ever observed that among the challenges particularly are harder normally for all of the groups?

In 2018 we launched a problem of so-called arbitrary surfaces that are surfaces unknown to the groups which can be placed on high of the workstations. The groups want to have the ability to cope with these surfaces. There are two surfaces which can be actually, actually terrible for the groups – one is grass that we just about stole from the soccer competitions! We simply thought it could be humorous to strive it, and it was a very fascinating drawback, particularly for among the grippers of the completely different groups. For instance, the present world champion, they’ve a inflexible gripper to allow them to have pressure suggestions once they grasp. Nonetheless, the grass is actually troublesome for them – due to their rigidity, they at all times grasp the grass itself after which they pull up the grass with the item. And this led to some fascinating issues, like they’re transporting the precise floor round and never solely the item. This isn’t an issue for groups utilizing a versatile gripper. Nonetheless, then again, the versatile gripper makes it actually troublesome to evaluate you probably have grasped the item as a result of you might have very unhealthy pressure suggestions. So there are two completely different approaches which have their professionals and cons in numerous situations.

Three robots from the @Work competitors in Brazil.

Are you introducing any new duties for this 12 months?

Sure and no. So really we’re introducing a totally new problem which is completely different from what we’ve performed earlier than. The brand new problem is the so-called sensible farming problem, which is opening our league to a complete new area of purposes, as a result of we are actually agriculture. We’re engaged on this with Studica, a robotics firm from Canada, whose {hardware} we’re utilizing. We’ve already given it a strive on the German Open. This problem comes with some new specifics and one these is that the groups solely get the robotic shortly earlier than the competitors. So that they don’t actually know the robotic largely upfront, and they should assemble, program and design the robotic in a really brief time. To compensate for this, we cut back the quantity of optimization and robustness that’s vital. As a result of it’s an agriculture setting, we’ve completely different objects, like fruits, that the groups must deal with. This makes it slightly bit extra difficult as a result of fruits have a extra arbitrary form and completely different ranges of ripeness that must be detected. We even have some grapes which can be hanging on a wall, which is a totally completely different type of manipulation activity than earlier than, as a result of earlier than the groups simply wanted to understand issues from surfaces, however now they actually need to pluck stuff from a wall in a dependable manner. So that is the brand new problem. It additionally comes with a variety of software program challenges as a result of the computational energy of this robotic could be very restricted as a result of it solely has a Raspberry Pi. For instance, there may be not a variety of picture processing potential, particularly in comparison with the present robots, a few of which even have GPUs embedded.

Is there a selected a part of the {hardware} or software program that you simply’ve seen among the largest developments in over the past 12 months or so?

Yeah, I believe one massive change I noticed over time was a change from customized neural networks for object detection to off-the-shelf elements. So just about all groups these days use YOLO networks, which you will get pre-trained and so they simply deploy them on GPUs that they embedded into their robots. That is additionally one of many the reason why the robots actually grew in dimension over the previous couple of years as a result of they wanted house for the bigger computational energy. This really made it potential for lots of groups to reliably detect the objects. Object detection was an enormous drawback to start with of the league and these days it’s probably not an enormous problem – most groups are actually good at that. Generally they’re slightly bit startled with decoy objects – these are objects within the area that aren’t actually a part of the duty, and they’re unknown to the groups beforehand. Generally they’re, let’s say, evil decoys that appear to be an object and there’s some mismatches that the groups do, however that is changing into very uncommon.

I believe the second massive change is a change to bigger manipulators with extra levels of freedom. So to start with, everybody had a really small manipulator with solely 5 levels of freedom, which restricted the working vary, and these days just about all groups have a six diploma of freedom manipulator with a wide variety. Which means they don’t want to maneuver their robotic when they’re in entrance of a workstation, which makes them a lot sooner and in addition rather more exact.

Might you discuss concerning the future plans for the League?

There are some things we’re fascinated about.

On the subject of the competitors itself, we had a dialogue with the groups about what they’re fascinated by doing sooner or later. Two issues got here up that they actually need to have. One is cellular obstacles, so they need different objects to maneuver autonomously by the world. We’re within the course of of making that, in cooperation with EduArt, which is an organization from Germany that additionally supplies small academic robots. And the second factor we need to introduce is a type of humanoid robotic that the groups can use to really deal with particular manipulation duties that can not be performed merely with a robotic manipulator.

When it comes to creating an entry-level League, we’ve been engaged on this and one potential concept is to make use of the smart-farming problem because the entry level. By means of the collaboration with Studica, we are able to present groups with the robotic and so they get to maintain it after the competitors. On the German Open I spoke to the Quickly-Manufactured Rescue League about this crossover between the Rescue and the Junior Leagues, and they’re very eager to collaborate.

We’re additionally speaking with the Logistics League. Their sponsor, Festo, has dropped out of their league and now they should reorganize. We’re questioning if it could be worthwhile to deliver our leagues nearer collectively, and even fuse them collectively to a single RoboCup Industrial league. The Logistics League needs to do extra manipulation, and the @Work League needs to do extra planning, so we’re closing the hole naturally between the 2. Nonetheless, that is only a thought for the time being – we have to see how the groups react to that.

About Christoph

Christoph Steup is an lively researcher specializing in numerous fields of robotics, together with swarm robotics, precision farming, and weather-resilient autonomous driving. He presently works on the Fraunhofer Institute for Transportation and Infrastructure Techniques (IVI), the place he leads the Swarm Expertise Group. Previous to this position, he headed the Computational Intelligence in Robotics group on the Otto von Guericke College Magdeburg. Christoph’s involvement with RoboCup started in 2015 when he joined the robOTTO workforce of Otto von Guericke College as workforce chief. His contributions to the RoboCup group expanded as he grew to become a member of the Technical Committee for the @Work League in 2017. In 2019, he additional superior his participation by becoming a member of the Government Committee of the league.