Video Friday: Check out this robot made from 3D printing as it makes its escape.

This robot can walk, without electronics, and only with the addition of a cartridge of compressed gas, right off the 3D-printer. It can also be printed in one go, from one material. Researchers from the University of California San Diego and BASF, describe how they developed the robot in an advanced online publication in the journal Advanced Intelligent Systems. They used the simplest technology available: a desktop 3D-printer and an off-the-shelf printing material. This design approach is not only robust, it is also cheap—each robot costs about $20 to manufacture.

And details!

[ Paper ] via [ University of California San Diego ]

Why do you want a humanoid robot to walk like a human? So that it doesn’t look weird, I guess, but it’s hard to imagine that a system that doesn’t have the same arrangement of joints and muscles that we do will move optimally by just trying to mimic us.

[ Figure ]

I don’t know how it manages it, but this little soft robotic worm somehow moves with an incredible amount of personality.

Soft actuators are critical for enabling soft robots, medical devices, and haptic systems. Many soft actuators, however, require power to hold a configuration and rely on hard circuitry for control, limiting their potential applications. In this work, the first soft electromagnetic system is demonstrated for externally-controlled bistable actuation or self-regulated astable oscillation.

[ Paper ] via [ Georgia Tech ]

Thanks, Ellen!

A 180-degree pelvis rotation would put the “break” in “breakdancing” if this were a human doing it.

[ Boston Dynamics ]

My colleagues were impressed by this cooking robot, but that may be because journalists are always impressed by free food.

[ Posha ]

This is our latest work about a hybrid aerial-terrestrial quadruped robot called SPIDAR, which shows unique and complex locomotion styles in both aerial and terrestrial domains including thrust-assisted crawling motion. This work has been presented in the International Symposium of Robotics Research (ISRR) 2024.

[ Paper ] via [ Dragon Lab ]

Thanks, Moju!

This fresh, newly captured video from Unitree’s testing grounds showcases the breakneck speed of humanoid intelligence advancement. Every day brings something thrilling!

[ Unitree ]

There should be more robots that you can ride around on.

[ AgileX Robotics ]

There should be more robots that wear hats at work.

[ Ugo ]

iRobot, who pioneered giant docks for robot vacuums, is now moving away from giant docks for robot vacuums.

[ iRobot ]

There’s a famous experiment where if you put a dead fish in current, it starts swimming, just because of its biomechanical design. Somehow, you can do the same thing with an unactuated quadruped robot on a treadmill.

[ Delft University of Technology ]

Mush! Narrowly!

[ Hybrid Robotics ]

It’s freaking me out a little bit that this couple is apparently wandering around a huge mall that is populated only by robots and zero other humans.

[ MagicLab ]

I’m trying, I really am, but the yellow is just not working for me.

[ Kepler ]

By having Stretch take on the physically demanding task of unloading trailers stacked floor to ceiling with boxes, Gap Inc has reduced injuries, lowered turnover, and watched employees get excited about automation intended to keep them safe.

[ Boston Dynamics ]

Since arriving at Mars in 2012, NASA’s Curiosity rover has been ingesting samples of Martian rock, soil, and air to better understand the past and present habitability of the Red Planet. Of particular interest to its search are organic molecules: the building blocks of life. Now, Curiosity’s onboard chemistry lab has detected long-chain hydrocarbons in a mudstone called “Cumberland,” the largest organics yet discovered on Mars.

[ NASA ]

This University of Toronto Robotics Institute Seminar is from Sergey Levine at UC Berkeley, on Robotics Foundation Models.

General-purpose pretrained models have transformed natural language processing, computer vision, and other fields. In principle, such approaches should be ideal in robotics: since gathering large amounts of data for any given robotic platform and application is likely to be difficult, general pretrained models that provide broad capabilities present an ideal recipe to enable robotic learning at scale for real-world applications.
From the perspective of general AI research, such approaches also offer a promising and intriguing approach to some of the grandest AI challenges: if large-scale training on embodied experience can provide diverse physical capabilities, this would shed light not only on the practical questions around designing broadly capable robots, but the foundations of situated problem-solving, physical understanding, and decision making. However, realizing this potential requires handling a number of challenging obstacles. What data shall we use to train robotic foundation models? What will be the training objective? How should alignment or post-training be done? In this talk, I will discuss how we can approach some of these challenges.

[ University of Toronto ]