﻿Weekly Robot News Hello viewers! Welcome back to your one-stop-shop
for all news Robotics! We’re back once more with the latest, sometimes shocking, happenings of the
Robotic Tech world. From iCub all grown up, robots getting inspired by Moai statues, and aid for
field robots, all the way to a cute desktop robot, and an E-Nose to sniff out the best whiskey,
we have it all and more! So without further adieu, let’s jump right into our weekly updates!
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Highlights of the Week * iCub Is Growing Up
It’s a little weird to think that iCub, the first version of which was released in 2008,
is now a full-on teenager—after all, the robot was originally designed after a three year old child,
and it hasn’t grown all that much. But as it turns out, iCub has grown, at least a little bit,
with the brand new iCub3, a bigger, heavier, stronger upgrade that can also be used as a
sophisticated immersive telepresence platform. You might not notice the difference between the old
and new iCub unless they’re standing side-by-side, but iCub3 is 25 cm taller and weighs 19 kg more,
featuring more powerful legs and rearranged actuators in the legs, torso, and shoulders. The
head is the same, but the neck is a bit longer to make the robot more proportional overall.
In total, iCub3 is 1.25 m tall and weighs 52 kg, with 54 degrees of freedom.
Part of the reason for these upgrades is to turn iCub3 into an avatar platform—that
is, a humanoid robot that can embody a remote humanoid of the more biological type.
This is something that researchers at the Italian Institute of Technology
(IIT) led by Daniele Pucci have been working on for quite a while. Now, a couple of the
shots right at the beginning of the video they released look more like drone videos than an
actual representation of the user experience, or at least, it won’t be accurate until iCub can fly,
which they’re working on, of course. It’s also, honestly, kind of hard to tell what the user
experience actually is just based on this very very fancy video, and very very fancy videos
rarely inspire confidence about the capabilities of a robotic system. Fortunately, the researchers
have published a paper on using iCub3 as an avatar which fortunately includes plenty of detail.
* Robots Get Inspiration From the Moai Statues of Easter Island
People around the world have long been captivated by the moai, a collection of statues that stand
sentry along the coast of Easter Island. The statues are well known not just for their immense
size and distinct facial features (for example, very broad noses and chins), but also for the
mystery that shrouds their geographic location. The question that piques everyone’s curiosity is:
How did ancient Rapa Nui people move these ginormous rocks—some weighing as much as 80
tonnes—across distances of up to 18 kilometers? In 2011, a group of archaeologists made some progress
in potentially unraveling this mystery. They conducted an experiment whereby
three hemp ropes were tied to the head of a moai replica. Using two of the ropes angled
at the sides to rock the statue back and forth, and the third rope for guidance,
they were able to “rock and walk” the replica forward, demonstrating at least one possible way
that the Rapa Nui people may have moved the real moai so many centuries ago. In the experiment,
18 people were able to move a 4.35-tonne replica 100 meters in just 40 minutes.
More recently, a group of researchers sought to use robots to employ this “rock-and-walk”
technique further. Jungwon Seo, an assistant professor at Hong Kong University of Science
and Technology, has previously used robots to study how to precisely move and place Go stones.
“Objects heavier than a Go stone, like the moai statue, may pose additional fresh challenges.
But we were motivated by the difficulty,” he says. His team devised a “rock-and-walk” technique and
implemented it four different ways using single or dual robotic arms, or single or dual custom-made
quadrotor aircrafts. They describe their work in their study published on 21st January
in IEEE Transactions on Robotics. * WayFAST For Field Robots
A new method of Traversability Predictive Navigation for Field Robots has been developed.
The team presents a self-supervised approach for learning to predict traversable paths for
wheeled mobile robots that require good traction to navigate. Their algorithm,
termed WayFAST (Waypoint Free Autonomous Systems for Traversability), uses RGB and depth data,
along with navigation experience, to autonomously generate traversable paths in outdoor unstructured
environments. Their key inspiration is that traction can be estimated for rolling robots
using kinodynamic models. Using traction estimates provided by an online receding horizon estimator,
they are able to train a traversability prediction neural network in a self-supervised manner,
without requiring heuristics utilized by previous methods. They demonstrate the effectiveness of
WayFAST through extensive field testing in varying environments, ranging from sandy dry beaches to
forest canopies and snow covered grass fields. Their results clearly demonstrate that WayFAST
can learn to avoid geometric obstacles as well as untraversable terrain, such as snow, which would
be difficult to avoid with sensors that provide only geometric data, such as LiDAR. Furthermore,
they also show that their training pipeline based on online traction estimates is more data
efficient than other heuristic-based methods. * ElectronBot: A Sweet Mini Desktop Robot
That Ticks All The Boxes Peng Zhihui seems to have
found some spare time and energy to crack out another sweet robot build, this time it’s a
much smaller, and cuter emoji-bot with the usual production-ready levels of attention to detail.
With a lot of fine details in the 3D printed models, this is one for SLS printing in nylon,
but that can be done for a reasonable outlay, in China at least. The electronics package consists
of a few full custom, and tiny, PCBs designed with Altium Designer, with off-the-shelf modules
for the circular LCD and camera. The main board hosts an STM32F405 and deals with the display
and SD card, The reason for this choice of STM32 was due to the requirement for connecting to an
external USB3300 high-speed USB PHY. There is a sensor PCB which handles the gesture sensor,
a USB hub, MPU6050 9-axis sensor, and also the USB camera module. This board attaches to the
USB-C connector in the base, via a FFC cable, allowing the robot to rotate on its base.
Peng clearly has exacting standards as to how things should work, and we guess wanted to have
the arms back-driveable in a way that enabled the host computer to track and record the motor
positions for replaying later on. The connection back to the controller is via I2C, allowing all
five servos to hang on the same bus, saving previous resources. Smart! Getting a processor
and motor driver in such a tiny space was a bit of challenge, but a walk in the park for Peng
as he demonstrated in his video which you might require English subtitles for. The arm mechanism
is particularly interesting, and rather elegantly executed, and he does seem rather proud of this
part of the design, and so he should! Like with Peng’s other projects, there is a lot to see, and
plenty of scope for feature explosion. It was nice to see the ‘bot being used as an input device,
not only with gesture sensing via the dedicated sensor, but also using the camera with OpenCV
to track user posture and act accordingly. This thing could act as genuinely useful AI device,
as was a being darn cute at the same time! * E-Nose Sniffs Out the Good Whiskey
A whiskey connoisseur can take a whiff of a dram and know exactly the brand, region,
and style of whiskey in hand. But how do our human noses compare to electronic noses in
distinguishing the qualities of a whiskey? A study published 1st February in IEEE Sensors Journal
describes a new e-nose that is surprisingly accurate at analyzing whiskies—and can identify
the brand of whiskey with more than 95 percent accuracy after just one “whiff.” E-noses have
been gaining in popularity over recent years thanks to their range of valuable applications,
from sensing when crops are ready for harvest to identifying food products on the cusp of expiring.
It is perhaps unsurprising that many e-noses have also been developed to analyze alcoholic
beverages, including whiskey, which had an estimated international market worth
US $58 billion in 2018 alone. “This lucrative industry has the potential to be a target of
fraudulent activities such as mislabeling and adulteration,” explains Steven Su, an associate
professor at the Faculty of Engineering and IT, University of Technology Sydney. “Trained experts
and experienced aficionados can easily tell the difference between whiskies from their scents.
But it is quite difficult for most consumers, especially amateurs.”
Therefore, Su and his colleagues sought to adapt one of their e-noses so that it could analyze some
key qualities of whiskey. Their original e-nose was designed to detect illegal animal parts sold
on the black market, such as rhino horns, and they have since also adapted their e-nose for breath
analysis and assessing food quality. With that, we come to the end of this
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