Real steel: the broken robot necks and baby steps of RoboCup 2012

Marcell is very German. He has blond hair, a melodic accent, and lives in Bonn, in the far west of Germany, where he's working on his PhD at the local university. He lives a quiet life in a calm town, biking to work and staying near relatives, but seems just as much in his element in the hectic environment of RoboCup. This is his fourth time at RoboCup, and Copedo is his fourth robot in as many years. At Bonn he works with Michael Schreiber, whose prolific engineering keeps up with Marcell's appetite for experimentation. Michael isn't here this year, so Marcell is working with a couple new teammates, showing them the code and teaching them the ropes. Most of his time is on the field with the robots, coaxing them to motion.

Now Marcell is teaching Copedo how to kick. It’s much stronger than its walk, and the mid-size soccer ball rolls forward several feet. I congratulate Marcell, but he returns to his computer unimpressed. "What would you expect from a kick? It has to be able to score a goal from any position," he grumbles.

Marcell likens teaching a robot to walk and kick to sculpture. It's sculpture with variables. Copedo has 35 tweakable numbers that define its kick alone, with hundreds of hard-coded parameters that cascade from those. In simulation, 35 variables are a challenge, but in real life, those 35 interact with the infinite variables of real life. A dozen or so motors are held to an imperfect, flexing frame by screws at different tensions, all stumbling over a nearly flat soccer field, covered in felt.

Copedo falls, and Marcell keeps sculpting.

RoboCup 2012 was my first RoboCup — my knowledge of last year’s competition in Istanbul and prior matches has all come from YouTube and second-hand accounts. I picked up my credentials at an improvised "Press Registration" table in the multi-floor building dubbed the “Pepsi Center” behind Mexico City’s World Trade Center, and wandered in. It had the usual bland mix of grays and blues required in convention halls worldwide. An unrelenting mix of Switchfoot songs played on the loudspeakers to lift the spirits of the competitors -- a thousand or so respectable computer scientists and mechanical engineers, whose robots were about to make a butchery of "the beautiful game."

In front of me stretched a sea of folding tables draped in blue tablecloths, each assigned to a different team. Most tables were drenched in disassembled robots and spare parts. Every year someone at RoboCup starts a fire with one of its battery charging stations, and this year looked like it would be no exception.

RoboCup’s multiple soccer “leagues” are broken down by size and mechanics: from tiny wheeled robots up to full-size humanoids. The Humanoid League, where I spent most of my time, was all custom-built robots, and therefore required the most maintenance, the most tables, and the most battery fires.

All of the games (and most testing) take place on small soccer fields of green felt, which change in size depending on the type of robot competing. Roboticists sleep at their tables, fighting jetlag. The games wouldn't start until Wednesday, and so Monday and Tuesday were spent in earnest calibration, with cables, robots, laptops, and sock-clad roboticists sprawled across the fields.

After assembly, the robots are taught very carefully what a ball looks like, based only on its color. Every flicker, burned out bulb, and hue variation confused the robots, and the roboticists would curse at the yellow-gray ceiling like a rain cloud threatening a baseball game. Then they'd take another bite of Domino's pizza, pull up some code, and start another round of calibration.

RoboCup’s competitors vie for the Louis Vuitton Best Humanoid Award, filled with a Baccarat crystal globe and encased in the iconic monogrammed LV lettering, but they wear t-shirts emblazoned with university names and nylon cargo pants that convert into capris.

RoboCup started twelve years ago, with an absurd goal to field a team of soccer robots against the human World Cup champions in 2050... and win. Right now the robots couldn't beat a team of toddlers.

A bit like a regular soccer match, robot soccer has two teams, two goals, a field, a ball, players and a referee. On each team's sideline is a long table that acts as a makeshift robot hospital. Across from the teams are metal bleachers, filled with a rotating cast of fans.

Each team has a robot handler, which picks up “malfunctioning specimens” off the field and hands them to the robo-hospital, or just places them in time out until their penalty time is over. The handlers stay busy. Both of them, along with the referee, wear black pants and black socks on the field, so not to confuse the robots.

The robots see the game as a "state machine," a flow chart of best-case scenarios. A state machine asks "what is my status?" and then executes a routine based on that status.

Do I see a ball?
If yes, then go to it.
Am I near a ball?
If yes, then kick it at the opponent's goal.

If the robot is confused about its status, all of its actions will be incorrect — and even the right status doesn't guarantee a useful action.

The whistle blows, all robots run at the ball simultaneously, blocking each other — including their own teammates — from reaching it. They fall. A robot gets up and kicks the ball towards the goal, but doesn't register the mayhem at its feet blocking the shot.

One robot decides the orange notebook I'm holding on the sidelines is a ball and goes after it. Another thinks the concrete pillars in the convention hall are goal posts.

The goalie's state machine determines it should make a dive to stop the ball rolling toward it. But it dives two seconds too late... in the wrong direction. And now it can't get up. The confused robot is pulled from the field, leaving the goal completely open.

Teams play with two, one, or no robots on the field. There are countless open shots, open goals, and missed shots on open goals. For some teams, success at RoboCup would be scoring a single goal in a game. For other teams, a single kick without falling over would be a triumph.

DARPA's big step

Marcell's trademark piece of apparel is an ugly, oversized sweater jacket that acts as simultaneous lab coat, painter's smock, and security blanket. It billows as he jogs between his work table and the soccer field, alternating between sitting and laying as he pours over his code — which is from 7AM to 11PM every day this week. He dreams in code, too: "The whole program of the robots is basically loaded into my brain."

He likens his walking algorithms to recipes: when you find a good one, with the measurements just right, you want to be sure to save a copy. He's built Copedo's walk recipe from scratch "100s of times," and it's "quite a pain in the butt."

There's all sorts of science required to build a robot, but when you're on the field, you just have your eyes. There's "nothing to calculate," explains Marcell, "you have to look at the robot." The skill, of course, is knowing what to look for. Marcell admitted he could spot problems in robots other than his own: "sometimes I have the impression 'this should have a little lower of a frequency,' or 'that one has the legs spread apart too far.'" But he keeps his suggestions to himself because he doesn't want to seem rude. Whether politeness or competitiveness was holding him back, Marcell's robots walked literal circles around the competition all week.

Marcell claims that his lab-built recipe didn't work at all when he first arrived, but midway through the first day, Copedo had the best walk in the building. Each step was stable and strong, and reminded me of an adult wearing a heavy backpack. But as Marcell kept pushing its speed, Copedo started to fall.

"Anything I do makes it worse," he said.

We hunkered down on Marcell's corner of the test field and observed. He tried another kick, and the robot shifted its weight to one side to counterbalance the motion. It looked precarious, and when it returned to two feet, Copedo took a second or two to stabilize laterally, swaying like an upside-down swing.

Marcell startled, eyes wide, and then dove into his computer.

He'd forgotten to turn on "damping," he explained. In Copedo's case, damping is a routine that causes the legs to actively resist the swaying motion, and the robot had been doing without that algorithm. Marcell pulled up the source code, tweaked, and recompiled. When Copedo tried another kick, it stabilized almost instantly after its kick.

Marcell's interest isn't in just creating the perfect, optimal walking algorithm. His PhD research is in teaching a robot how to stagger. How to right itself when the conditions stray from optimal. The real world is non-optimal, and RoboCup is a brutal, week-long reminder of that fact.

The next table over, Steven McGill, from U. Penn, runs the dominant Darwin-OP KidSize team, a joint effort between Virginia Tech and U. Penn. But he also brought a new robot this year: Darwin XOS, which is Team Darwin's first TeenSize entry. The robot was as fresh as they come: Virginia Tech had machined the final parts only a week before, and when I first spotted the robot, Steven was still teaching it which way gravity was pointed.

When they finally got XOS "walking," it looked like it was staggering through death throes after taking a bullet to the chest, or possibly in need of a bathroom. Steven works with his brothers, who he operates like a command line interface. He was tweaking "velocity limits" in OS X's Terminal, while they babysat XOS in case it fell.

"Dude, the velocity, I can get it up to .06 now." Fingers flew, more tweaks were made. "Forward bias, definitely a forward bias." Steven sounded like a spaceship engineer, stretching a photon drive to its limits. XOS started to fall forward. "I was pushing it, I was pushing it!"

"What was that up to?" asked a brother.

".08, putting it back to .06," said Steven, adrenaline still pulsing. "Save save save..."

On .06, XOS started really walking. Not Marcell / Copedo-good, but still pretty good. I cheered, Steven checked again that he'd saved, and then he looked around to see if anybody had seen. There were few witnesses. Steven and I scrambled for cameras but by the time we were ready to shoot, XOS wasn't able repeat its performance.

The team blamed overheating motors and rested XOS, but I never saw it take another good step. As the week wore on, it seemed XOS's inefficient walk and weak power-to-weight ratio was burning out its actuators.

Saturday, I watched in agony as the Darmstadt Dribblers, Darwin-OP's primary rival in the KidSize league, lost their semifinal match with most of their robots on the sideline. The game had been a tight back-and-forth until the end. "The intense is killing me," said a Korean woman next to me, as the score tied up for the third time. The intense was killing me, too. But then the opponent, CIT Brains, scored a couple uncontested goals. Darmstadt students frantically pumped compressed air into the joints to try and cool off their robot's motors, rushing to get a working Dribbler back on the field before the clock ran out, but ultimately the aging design just couldn't handle the strain.

A house of cards indeed.

RoboCup's simultaneous strength and weakness is that to win, you have to leave your bleeding edge experiments at home and bring something that just works. Darmstadt has been bringing the same KidSize soccer robot to RoboCup for the past five years, and there's no replacement on the way. In the AdultSize competition, Virginia Tech coasted through to a win with Charlie-2, which won the Louis Vuitton award last year and underwent few changes for this year's competition. Why risk knocking down the house of cards if you're winning?

"AI is not about doing the optimal thing," Dr. Daniel Lee told me, who heads the robotics program at U. Penn and helps advise the Virginia Tech guys as well, just "never do the stupid things."

Now that TeenSize robots like Marcell's can survive falls, and even get themselves up off the ground at times, TeenSize seems like a natural evolution from KidSize — like the move from caninoid to humanoid was last decade. But just four TeenSize teams came this year, and only Marcell's Nimbro bots and the slick, minimal CIT Brains humanoids were competitive.

Many participants agreed that TeenSize is the "optimal" move for RoboCup, but the robots are exponentially more expensive than KidSize robots, and they don't get as much press as AdultSize robots. Now with DARPA looming, next-gen AdultSize robots -- like the promising ones in the works at Virginia Tech and Darmstadt -- will be even more important.

Marcell is building a TeenSize Open Platform robot, which he hopes to get built and sold by Robotis, like it currently sells the KidSize Darwin-OP. Maybe it will help. But the fact also remains that these humanoids are desperately dumb. It seems silly to spend $20,000 or $30,000 on a robot goalie that dives in the wrong direction.

At RoboCup, the real brains are in the @home competition. The robots compete at domestic chores like recognizing humans, handing them objects, avoiding collisions with furniture, and cleaning up carefully placed messes. They're aided by laser rangefinders, high-powered laptops, and Kinect sensors for heads.

But even the best brain is at the mercy of its state machine. Most of the @home robots failed on the starting line of their very first test: an open door. The whistle would blow, the clock would start, and $20,000 or so of machinery would stand still, asking itself "is the door open?" and answering itself with a false-negative.

In a later @home competition, a robot stood still for three minutes in front of a judge it was supposed to be recognizing. "Please look at me," it intoned synthetically, wanting a better look at the judge's face. "Please look at my eyes." I squirmed in the audience. Human and robot stood face-to-Kinect sensor until the clock ran out, the request on loop. "Please look at me. Please look at my eyes."

Thankfully, I also saw some amazing things in @home. Robots managed to take verbal drink orders, pick the correct beverage among a lineup of choices, and then bring it to the human that requested it. Robots watered plants, picked up trash, and, on occasion, went through open doors.

In my favorite performance, Marcell’s colleague Jörg Stückler’s Cosero followed a judge through a crowd and entered an elevator. I sprinted with a few dozen other observers to an escalator and downstairs, where we craned our necks, cameras poised, to see if Cosero would manage to make it out of the elevator. It did, but the changes in lighting downstairs stopped it in its tracks.

The elevator challenge had originally been slated for a freight elevator, but the elevator would stop a couple inches lower than the floor — making it too dangerous for the wheeled robots to navigate. And so the robots used the handicap elevator instead.