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Video Friday: Dusty at Work

Your weekly selection of awesome robot videos

3 min read
A small rectangular robot with large orange cartoon eyes on a construction site

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We'll also be posting a weekly calendar of upcoming robotics events for the next few months; here's what we have so far (send us your events!):

ROSCon 2021 – October 20-21, 2021 – [Online Event]
Silicon Valley Robot Block Party – October 23, 2021 – Oakland, CA, USA

Let us know if you have suggestions for next week, and enjoy today's videos.


I love watching Dusty Robotics' field printer at work. I don't know whether it's intentional or not, but it's go so much personality somehow.

[ Dusty Robotics ]

A busy commuter is ready to walk out the door, only to realize they've misplaced their keys and must search through piles of stuff to find them. Rapidly sifting through clutter, they wish they could figure out which pile was hiding the keys. Researchers at MIT have created a robotic system that can do just that. The system, RFusion, is a robotic arm with a camera and radio frequency (RF) antenna attached to its gripper. It fuses signals from the antenna with visual input from the camera to locate and retrieve an item, even if the item is buried under a pile and completely out of view.

While finding lost keys is helpful, RFusion could have many broader applications in the future, like sorting through piles to fulfill orders in a warehouse, identifying and installing components in an auto manufacturing plant, or helping an elderly individual perform daily tasks in the home, though the current prototype isn't quite fast enough yet for these uses.

[ MIT ]

CSIRO Data61 had, I'm pretty sure, the most massive robots in the entire SubT competition. And this is how you solve doors with a massive robot.

[ CSIRO ]

You know how robots are supposed to be doing things that are too dangerous for humans? I think sailing through a hurricane qualifies..

This second video, also captured by this poor Saildrone, is if anything even worse:

[ Saildrone ] via [ NOAA ]

Soft Robotics can handle my taquitos anytime.

[ Soft Robotics ]

This is brilliant, if likely unaffordable for most people.

[ Eric Paulos ]

I do not understand this robot at all, nor can I tell whether it's friendly or potentially dangerous or both.

[ Keunwook Kim ]

This sort of thing really shouldn't have to exist for social home robots, but I'm glad it does, I guess?

It costs $100, though.

[ Digital Dream Labs ]

If you watch this video closely, you'll see that whenever a simulated ANYmal falls over, it vanishes from existence. This is a new technique for teaching robots to walk by threatening them with extinction if they fail.

But seriously how do I get this as a screensaver?

[ RSL ]

Zimbabwe Flying Labs' Tawanda Chihambakwe shares how Zimbabwe Flying Labs got their start, using drones for STEM programs, and how drones impact conservation and agriculture.

[ Zimbabwe Flying Labs ]

DARPA thoughtfully provides a video tour of the location of every artifact on the SubT Final prize course. Some of them are hidden extraordinarily well.

Also posted by DARPA this week are full prize round run videos for every team; here are the top three: MARBLE, CSIRO Data61, and CERBERUS.

[ DARPA SubT ]

An ICRA 2021 plenary talk from Fumihito Arai at the University of Tokyo, on "Robotics and Automation in Micro & Nano-Scales."

[ ICRA 2021 ]

This week's UPenn GRASP Lab Seminar comes from Rahul Mangharam, on "What can we learn from Autonomous Racing?"

[ UPenn ]

The Conversation (3)
E_Z Points 09 Oct, 2021

The headline on the RFusion robot video is misleading.

The robot does not find and retrieve missing objects, it finds and retrieves RFID tags.

E_Z Points 09 Oct, 2021

I would think it a very good idea, to keep the Post-plant3 away from children.

E_Z Points 09 Oct, 2021

"Soft Robotics can handle my taquitos anytime."

You're starting to sound like Howard Wolowitz.

Letting Robocars See Around Corners

Using several bands of radar at once can give cars a kind of second sight

10 min read
Horizontal
Illustration of the modeling of a autonomous vehicle within a urban city intersection.

Seeing around the corner is simulated by modeling an autonomous vehicle approaching an urban intersection with four high-rise concrete buildings at the corners. A second vehicle is approaching the center via a crossing road, out of the AV’s line of sight, but it can be detected nonetheless through the processing of signals that return either by reflecting along multiple paths or by passing directly through the buildings.

Chris Philpot

An autonomous car needs to do many things to make the grade, but without a doubt, sensing and understanding its environment are the most critical. A self-driving vehicle must track and identify many objects and targets, whether they’re in clear view or hidden, whether the weather is fair or foul.

Today’s radar alone is nowhere near good enough to handle the entire job—cameras and lidars are also needed. But if we could make the most of radar’s particular strengths, we might dispense with at least some of those supplementary sensors.

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