"The whole program of the robots is basically loaded into my brain."

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.