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He just can’t help it.

Don’t worry, you’ll still be able to watch Jury Duty for freevee.

Simone Giertz came to fame in the 2010s by becoming the self-proclaimed “queen of shitty robots.” On YouTube she demonstrated a hilarious series of self-built mechanized devices that worked perfectly for ridiculous applications, such as a headboard-mounted alarm clock with a rubber hand to slap the user awake.

But Giertz has parlayed her Internet renown into Yetch, a design company that makes commercial consumer products. (The company name comes from how Giertz’s Swedish name is properly pronounced.) Her first release, a daily habit-tracking calendar, was picked up by prestigious outlets such as the Museum of Modern Art design store in New York City. She has continued to make commercial products since, as well as one-off strange inventions for her online audience.

Where did the motivation for your useless robots come from?

Simone Giertz: I just thought that robots that failed were really funny. It was also a way for me to get out of creating from a place of performance anxiety and perfection. Because if you set out to do something that fails, that gives you a lot of creative freedom.

You built up a big online following. A lot of people would be happy with that level of success. But you moved into inventing commercial products. Why?

Giertz: I like torturing myself, I guess! I’d been creating things for YouTube and for social media for a long time. I wanted to try something new and also find longevity in my career. I’m not super motivated to constantly try to get people to give me attention. That doesn’t feel like a very good value to strive for. So I was like, “Okay, what do I want to do for the rest of my career?” And developing products is something that I’ve always been really, really interested in. And yeah, it is tough, but I’m so happy to be doing it. I’m enjoying it thoroughly, as much as there’s a lot of face-palm moments.

Giertz’s every day goal calendar was picked up by the Museum of Modern Art’s design store. Yetch

What role does failure play in your invention process?

Giertz: I think it’s inevitable. Before, obviously, I wanted something that failed in the most unexpected or fun way possible. And now when I’m developing products, it’s still a part of it. You make so many different versions of something and each one fails because of something. But then, hopefully, what happens is that you get smaller and smaller failures. Product development feels like you’re going in circles, but you’re actually going in a spiral because the circles are taking you somewhere.

What advice do you have for aspiring inventors?

Giertz: Make things that you want. A lot of people make things that they think that other people want, but the main target audience, at least for myself, is me. I trust that if I find something interesting, there are probably other people who do too. And then just find good people to work with and collaborate with. There is no such thing as the lonely genius, I think. I’ve worked with a lot of different people and some people made me really nervous and anxious. And some people, it just went easy and we had a great time. You’re just like, “Oh, what if we do this? What if we do this?” Find those people.

This article appears in the November 2024 print issue as “The Queen of Useless Robots.”

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Boston Dynamics is the master of dropping amazing robot videos with no warning, and last week, we got a surprise look at the new electric Atlas going “hands on” with a practical factory task.

This video is notable because it’s the first real look we’ve had at the new Atlas doing something useful—or doing anything at all, really, as the introductory video from back in April (the first time we saw the robot) was less than a minute long. And the amount of progress that Boston Dynamics has made is immediately obvious, with the video showing a blend of autonomous perception, full body motion, and manipulation in a practical task.

We sent over some quick questions as soon as we saw the video, and we’ve got some extra detail from Scott Kuindersma, senior director of Robotics Research at Boston Dynamics.

If you haven’t seen this video yet, what kind of robotics person are you, and also here you go:

Atlas is autonomously moving engine covers between supplier containers and a mobile sequencing dolly. The robot receives as input a list of bin locations to move parts between.

Atlas uses a machine learning (ML) vision model to detect and localize the environment fixtures and individual bins [0:36]. The robot uses a specialized grasping policy and continuously estimates the state of manipulated objects to achieve the task.

There are no prescribed or teleoperated movements; all motions are generated autonomously online. The robot is able to detect and react to changes in the environment (e.g., moving fixtures) and action failures (e.g., failure to insert the cover, tripping, environment collisions [1:24]) using a combination of vision, force, and proprioceptive sensors.

Eagle-eyed viewers will have noticed that this task is very similar to what we saw hydraulic Atlas (Atlas classic?) working on just before it retired. We probably don’t need to read too much into the differences between how each robot performs that task, but it’s an interesting comparison to make.

For more details, here’s our Q&A with Kuindersma:

How many takes did this take?

Kuindersma: We ran this sequence a couple times that day, but typically we’re always filming as we continue developing and testing Atlas. Today we’re able to run that engine cover demo with high reliability, and we’re working to expand the scope and duration of tasks like these.

Is this a task that humans currently do?

Kuindersma: Yes.

What kind of world knowledge does Atlas have while doing this task?

Kuindersma: The robot has access to a CAD model of the engine cover that is used for object pose prediction from RGB images. Fixtures are represented more abstractly using a learned keypoint prediction model. The robot builds a map of the workcell at startup which is updated on the fly when changes are detected (e.g., moving fixture).

Does Atlas’s torso have a front or back in a meaningful way when it comes to how it operates?

Kuindersma: Its head/torso/pelvis/legs do have “forward” and “backward” directions, but the robot is able to rotate all of these relative to one another. The robot always knows which way is which, but sometimes the humans watching lose track.

Are the head and torso capable of unlimited rotation?

Kuindersma: Yes, many of Atlas’s joints are continuous.

How long did it take you folks to get used to the way Atlas moves?

Kuindersma: Atlas’s motions still surprise and delight the team.

OSHA recommends against squatting because it can lead to workplace injuries. How does Atlas feel about that?

Kuindersma: As might be evident by some of Atlas’s other motions, the kinds of behaviors that might be injurious for humans might be perfectly fine for robots.

Can you describe exactly what process Atlas goes through at 1:22?

Kuindersma: The engine cover gets caught on the fabric bins and triggers a learned failure detector on the robot. Right now this transitions into a general-purpose recovery controller, which results in a somewhat jarring motion (we will improve this). After recovery, the robot retries the insertion using visual feedback to estimate the state of both the part and fixture.

Were there other costume options you considered before going with the hot dog?

Kuindersma: Yes, but marketing wants to save them for next year.

How many important sensors does the hot dog costume occlude?

Kuindersma: None. The robot is using cameras in the head, proprioceptive sensors, IMU, and force sensors in the wrists and feet. We did have to cut the costume at the top so the head could still spin around.

Why are pickles always causing problems?

Kuindersma: Because pickles are pesky, polarizing pests.

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