Tag Archives: programming

#439100 Video Friday: Robotic Eyeball Camera

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. 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!):

RoboSoft 2021 – April 12-16, 2021 – [Online Conference]
ICRA 2021 – May 30-5, 2021 – Xi'an, China
RoboCup 2021 – June 22-28, 2021 – [Online Event]
DARPA SubT Finals – September 21-23, 2021 – Louisville, KY, USA
WeRobot 2021 – September 23-25, 2021 – Coral Gables, FL, USA
Let us know if you have suggestions for next week, and enjoy today's videos.

What if seeing devices looked like us? Eyecam is a prototype exploring the potential future design of sensing devices. Eyecam is a webcam shaped like a human eye that can see, blink, look around and observe us.

And it's open source, so you can build your own!

[ Eyecam ]

Looks like Festo will be turning some of its bionic robots into educational kits, which is a pretty cool idea.

[ Bionics4Education ]

Underwater soft robots are challenging to model and control because of their high degrees of freedom and their intricate coupling with water. In this paper, we present a method that leverages the recent development in differentiable simulation coupled with a differentiable, analytical hydrodynamic model to assist with the modeling and control of an underwater soft robot. We apply this method to Starfish, a customized soft robot design that is easy to fabricate and intuitive to manipulate.

[ MIT CSAIL ]

Rainbow Robotics, the company who made HUBO, has a new collaborative robot arm.

[ Rainbow Robotics ]

Thanks Fan!

We develop an integrated robotic platform for advanced collaborative robots and demonstrates an application of multiple robots collaboratively transporting an object to different positions in a factory environment. The proposed platform integrates a drone, a mobile manipulator robot, and a dual-arm robot to work autonomously, while also collaborating with a human worker. The platform also demonstrates the potential of a novel manufacturing process, which incorporates adaptive and collaborative intelligence to improve the efficiency of mass customization for the factory of the future.

[ Paper ]

Thanks Poramate!

In Sevastopol State University the team of the Laboratory of Underwater Robotics and Control Systems and Research and Production Association “Android Technika” performed tests of an underwater anropomorphic manipulator robot.

[ Sevastopol State ]

Thanks Fan!

Taiwanese company TCI Gene created a COVID test system based on their fully automated and enclosed gene testing machine QVS-96S. The system includes two ABB robots and carries out 1800 tests per day, operating 24/7. Every hour 96 virus samples tests are made with an accuracy of 99.99%.

[ ABB ]

A short video showing how a Halodi Robotics can be used in a commercial guarding application.

[ Halodi ]

During the past five years, under the NASA Early Space Innovations program, we have been developing new design optimization methods for underactuated robot hands, aiming to achieve versatile manipulation in highly constrained environments. We have prototyped hands for NASA’s Astrobee robot, an in-orbit assistive free flyer for the International Space Station.

[ ROAM Lab ]

The new, improved OTTO 1500 is a workhorse AMR designed to move heavy payloads through demanding environments faster than any other AMR on the market, with zero compromise to safety.

[ ROAM Lab ]

Very, very high performance sensing and actuation to pull this off.

[ Ishikawa Group ]

We introduce a conversational social robot designed for long-term in-home use to help with loneliness. We present a novel robot behavior design to have simple self-reflection conversations with people to improve wellness, while still being feasible, deployable, and safe.

[ HCI Lab ]

We are one of the 5 winners of the Start-up Challenge. This video illustrates what we achieved during the Swisscom 5G exploration week. Our proof-of-concept tele-excavation system is composed of a Menzi Muck M545 walking excavator automated & customized by Robotic Systems Lab and IBEX motion platform as the operator station. The operator and remote machine are connected for the first time via a 5G network infrastructure which was brought to our test field by Swisscom.

[ RSL ]

This video shows LOLA balancing on different terrain when being pushed in different directions. The robot is technically blind, not using any camera-based or prior information on the terrain (hard ground is assumed).

[ TUM ]

Autonomous driving when you cannot see the road at all because it's buried in snow is some serious autonomous driving.

[ Norlab ]

A hierarchical and robust framework for learning bipedal locomotion is presented and successfully implemented on the 3D biped robot Digit. The feasibility of the method is demonstrated by successfully transferring the learned policy in simulation to the Digit robot hardware, realizing sustained walking gaits under external force disturbances and challenging terrains not included during the training process.

[ OSU ]

This is a video summary of the Center for Robot-Assisted Search and Rescue's deployments under the direction of emergency response agencies to more than 30 disasters in five countries from 2001 (9/11 World Trade Center) to 2018 (Hurricane Michael). It includes the first use of ground robots for a disaster (WTC, 2001), the first use of small unmanned aerial systems (Hurricane Katrina 2005), and the first use of water surface vehicles (Hurricane Wilma, 2005).

[ CRASAR ]

In March, a team from the Oxford Robotics Institute collected a week of epic off-road driving data, as part of the Sense-Assess-eXplain (SAX) project.

[ Oxford Robotics ]

As a part of the AAAI 2021 Spring Symposium Series, HEBI Robotics was invited to present an Industry Talk on the symposium's topic: Machine Learning for Mobile Robot Navigation in the Wild. Included in this presentation was a short case study on one of our upcoming mobile robots that is being designed to successfully navigate unstructured environments where today's robots struggle.

[ HEBI Robotics ]

Thanks Hardik!

This Lockheed Martin Robotics Seminar is from Chad Jenkins at the University of Michigan, on “Semantic Robot Programming… and Maybe Making the World a Better Place.”

I will present our efforts towards accessible and general methods of robot programming from the demonstrations of human users. Our recent work has focused on Semantic Robot Programming (SRP), a declarative paradigm for robot programming by demonstration that builds on semantic mapping. In contrast to procedural methods for motion imitation in configuration space, SRP is suited to generalize user demonstrations of goal scenes in workspace, such as for manipulation in cluttered environments. SRP extends our efforts to crowdsource robot learning from demonstration at scale through messaging protocols suited to web/cloud robotics. With such scaling of robotics in mind, prospects for cultivating both equal opportunity and technological excellence will be discussed in the context of broadening and strengthening Title IX and Title VI.

[ UMD ] Continue reading

Posted in Human Robots

#439023 In ‘Klara and the Sun,’ We Glimpse ...

In a store in the center of an unnamed city, humanoid robots are displayed alongside housewares and magazines. They watch the fast-moving world outside the window, anxiously awaiting the arrival of customers who might buy them and take them home. Among them is Klara, a particularly astute robot who loves the sun and wants to learn as much as possible about humans and the world they live in.

So begins Kazuo Ishiguro’s new novel Klara and the Sun, published earlier this month. The book, told from Klara’s perspective, portrays an eerie future society in which intelligent machines and other advanced technologies have been integrated into daily life, but not everyone is happy about it.

Technological unemployment, the progress of artificial intelligence, inequality, the safety and ethics of gene editing, increasing loneliness and isolation—all of which we’re grappling with today—show up in Ishiguro’s world. It’s like he hit a fast-forward button, mirroring back to us how things might play out if we don’t approach these technologies with caution and foresight.

The wealthy genetically edit or “lift” their children to set them up for success, while the poor have to make do with the regular old brains and bodies bequeathed them by evolution. Lifted and unlifted kids generally don’t mix, and this is just one of many sinister delineations between a new breed of haves and have-nots.

There’s anger about robots’ steady infiltration into everyday life, and questions about how similar their rights should be to those of humans. “First they take the jobs. Then they take the seats at the theater?” one woman fumes.

References to “changes” and “substitutions” allude to an economy where automation has eliminated millions of jobs. While “post-employed” people squat in abandoned buildings and fringe communities arm themselves in preparation for conflict, those whose livelihoods haven’t been destroyed can afford to have live-in housekeepers and buy Artificial Friends (or AFs) for their lonely children.

“The old traditional model that we still live with now—where most of us can get some kind of paid work in exchange for our services or the goods we make—has broken down,” Ishiguro said in a podcast discussion of the novel. “We’re not talking just about the difference between rich and poor getting bigger. We’re talking about a gap appearing between people who participate in society in an obvious way and people who do not.”

He has a point; as much as techno-optimists claim that the economic changes brought by automation and AI will give us all more free time, let us work less, and devote time to our passion projects, how would that actually play out? What would millions of “post-employed” people receiving basic income actually do with their time and energy?

In the novel, we don’t get much of a glimpse of this side of the equation, but we do see how the wealthy live. After a long wait, just as the store manager seems ready to give up on selling her, Klara is chosen by a 14-year-old girl named Josie, the daughter of a woman who wears “high-rank clothes” and lives in a large, sunny home outside the city. Cheerful and kind, Josie suffers from an unspecified illness that periodically flares up and leaves her confined to her bed for days at a time.

Her life seems somewhat bleak, the need for an AF clear. In this future world, the children of the wealthy no longer go to school together, instead studying alone at home on their digital devices. “Interaction meetings” are set up for them to learn to socialize, their parents carefully eavesdropping from the next room and trying not to intervene when there’s conflict or hurt feelings.

Klara does her best to be a friend, aide, and confidante to Josie while continuing to learn about the world around her and decode the mysteries of human behavior. We surmise that she was programmed with a basic ability to understand emotions, which evolves along with her other types of intelligence. “I believe I have many feelings. The more I observe, the more feelings become available to me,” she explains to one character.

Ishiguro does an excellent job of representing Klara’s mind: a blend of pre-determined programming, observation, and continuous learning. Her narration has qualities both robotic and human; we can tell when something has been programmed in—she “Gives Privacy” to the humans around her when that’s appropriate, for example—and when she’s figured something out for herself.

But the author maintains some mystery around Klara’s inner emotional life. “Does she actually understand human emotions, or is she just observing human emotions and simulating them within herself?” he said. “I suppose the question comes back to, what are our emotions as human beings? What do they amount to?”

Klara is particularly attuned to human loneliness, since she essentially was made to help prevent it. It is, in her view, peoples’ biggest fear, and something they’ll go to great lengths to avoid, yet can never fully escape. “Perhaps all humans are lonely,” she says.

Warding off loneliness through technology isn’t a futuristic idea, it’s something we’ve been doing for a long time, with the technologies at hand growing more and more sophisticated. Products like AFs already exist. There’s XiaoIce, a chatbot that uses “sentiment analysis” to keep its 660 million users engaged, and Azuma Hikari, a character-based AI designed to “bring comfort” to users whose lives lack emotional connection with other humans.

The mere existence of these tools would be sinister if it wasn’t for their widespread adoption; when millions of people use AIs to fill a void in their lives, it raises deeper questions about our ability to connect with each other and whether technology is building it up or tearing it down.

This isn’t the only big question the novel tackles. An overarching theme is one we’ve been increasingly contemplating as computers start to acquire more complex capabilities, like the beginnings of creativity or emotional awareness: What is it that truly makes us human?

“Do you believe in the human heart?” one character asks. “I don’t mean simply the organ, obviously. I’m speaking in the poetic sense. The human heart. Do you think there is such a thing? Something that makes each of us special and individual?”

The alternative, at least in the story, is that people don’t have a unique essence, but rather we’re all a blend of traits and personalities that can be reduced to strings of code. Our understanding of the brain is still elementary, but at some level, doesn’t all human experience boil down to the firing of billions of neurons between our ears? Will we one day—in a future beyond that painted by Ishiguro, but certainly foreshadowed by it—be able to “decode” our humanity to the point that there’s nothing mysterious left about it? “A human heart is bound to be complex,” Klara says. “But it must be limited.”

Whether or not you agree, Klara and the Sun is worth the read. It’s both a marvelous, engaging story about what it means to love and be human, and a prescient warning to approach technological change with caution and nuance. We’re already living in a world where AI keeps us company, influences our behavior, and is wreaking various forms of havoc. Ishiguro’s novel is a snapshot of one of our possible futures, told through the eyes of a robot who keeps you rooting for her to the end.

Image Credit: Marion Wellmann from Pixabay Continue reading

Posted in Human Robots

#437193 TyroBot: DIY Humanoid Robot

“TyroBot” is a novice-friendly (but high-tech) 3D-printable open source kit that can be assembled in a few hours, and is very easy to program. It’s great way to teach yourself robotics and programming! Read more, or back them on Kickstarter.

Posted in Human Robots

#437974 China Wants to Be the World’s AI ...

China’s star has been steadily rising for decades. Besides slashing extreme poverty rates from 88 percent to under 2 percent in just 30 years, the country has become a global powerhouse in manufacturing and technology. Its pace of growth may slow due to an aging population, but China is nonetheless one of the world’s biggest players in multiple cutting-edge tech fields.

One of these fields, and perhaps the most significant, is artificial intelligence. The Chinese government announced a plan in 2017 to become the world leader in AI by 2030, and has since poured billions of dollars into AI projects and research across academia, government, and private industry. The government’s venture capital fund is investing over $30 billion in AI; the northeastern city of Tianjin budgeted $16 billion for advancing AI; and a $2 billion AI research park is being built in Beijing.

On top of these huge investments, the government and private companies in China have access to an unprecedented quantity of data, on everything from citizens’ health to their smartphone use. WeChat, a multi-functional app where people can chat, date, send payments, hail rides, read news, and more, gives the CCP full access to user data upon request; as one BBC journalist put it, WeChat “was ahead of the game on the global stage and it has found its way into all corners of people’s existence. It could deliver to the Communist Party a life map of pretty much everybody in this country, citizens and foreigners alike.” And that’s just one (albeit big) source of data.

Many believe these factors are giving China a serious leg up in AI development, even providing enough of a boost that its progress will surpass that of the US.

But there’s more to AI than data, and there’s more to progress than investing billions of dollars. Analyzing China’s potential to become a world leader in AI—or in any technology that requires consistent innovation—from multiple angles provides a more nuanced picture of its strengths and limitations. In a June 2020 article in Foreign Affairs, Oxford fellows Carl Benedikt Frey and Michael Osborne argued that China’s big advantages may not actually be that advantageous in the long run—and its limitations may be very limiting.

Moving the AI Needle
To get an idea of who’s likely to take the lead in AI, it could help to first consider how the technology will advance beyond its current state.

To put it plainly, AI is somewhat stuck at the moment. Algorithms and neural networks continue to achieve new and impressive feats—like DeepMind’s AlphaFold accurately predicting protein structures or OpenAI’s GPT-3 writing convincing articles based on short prompts—but for the most part these systems’ capabilities are still defined as narrow intelligence: completing a specific task for which the system was painstakingly trained on loads of data.

(It’s worth noting here that some have speculated OpenAI’s GPT-3 may be an exception, the first example of machine intelligence that, while not “general,” has surpassed the definition of “narrow”; the algorithm was trained to write text, but ended up being able to translate between languages, write code, autocomplete images, do math, and perform other language-related tasks it wasn’t specifically trained for. However, all of GPT-3’s capabilities are limited to skills it learned in the language domain, whether spoken, written, or programming language).

Both AlphaFold’s and GPT-3’s success was due largely to the massive datasets they were trained on; no revolutionary new training methods or architectures were involved. If all it was going to take to advance AI was a continuation or scaling-up of this paradigm—more input data yields increased capability—China could well have an advantage.

But one of the biggest hurdles AI needs to clear to advance in leaps and bounds rather than baby steps is precisely this reliance on extensive, task-specific data. Other significant challenges include the technology’s fast approach to the limits of current computing power and its immense energy consumption.

Thus, while China’s trove of data may give it an advantage now, it may not be much of a long-term foothold on the climb to AI dominance. It’s useful for building products that incorporate or rely on today’s AI, but not for pushing the needle on how artificially intelligent systems learn. WeChat data on users’ spending habits, for example, would be valuable in building an AI that helps people save money or suggests items they might want to purchase. It will enable (and already has enabled) highly tailored products that will earn their creators and the companies that use them a lot of money.

But data quantity isn’t what’s going to advance AI. As Frey and Osborne put it, “Data efficiency is the holy grail of further progress in artificial intelligence.”

To that end, research teams in academia and private industry are working on ways to make AI less data-hungry. New training methods like one-shot learning and less-than-one-shot learning have begun to emerge, along with myriad efforts to make AI that learns more like the human brain.

While not insignificant, these advancements still fall into the “baby steps” category. No one knows how AI is going to progress beyond these small steps—and that uncertainty, in Frey and Osborne’s opinion, is a major speed bump on China’s fast-track to AI dominance.

How Innovation Happens
A lot of great inventions have happened by accident, and some of the world’s most successful companies started in garages, dorm rooms, or similarly low-budget, nondescript circumstances (including Google, Facebook, Amazon, and Apple, to name a few). Innovation, the authors point out, often happens “through serendipity and recombination, as inventors and entrepreneurs interact and exchange ideas.”

Frey and Osborne argue that although China has great reserves of talent and a history of building on technologies conceived elsewhere, it doesn’t yet have a glowing track record in terms of innovation. They note that of the 100 most-cited patents from 2003 to present, none came from China. Giants Tencent, Alibaba, and Baidu are all wildly successful in the Chinese market, but they’re rooted in technologies or business models that came out of the US and were tweaked for the Chinese population.

“The most innovative societies have always been those that allowed people to pursue controversial ideas,” Frey and Osborne write. China’s heavy censorship of the internet and surveillance of citizens don’t quite encourage the pursuit of controversial ideas. The country’s social credit system rewards people who follow the rules and punishes those who step out of line. Frey adds that top-down execution of problem-solving is effective when the problem at hand is clearly defined—and the next big leaps in AI are not.

It’s debatable how strongly a culture of social conformism can impact technological innovation, and of course there can be exceptions. But a relevant historical example is the Soviet Union, which, despite heavy investment in science and technology that briefly rivaled the US in fields like nuclear energy and space exploration, ended up lagging far behind primarily due to political and cultural factors.

Similarly, China’s focus on computer science in its education system could give it an edge—but, as Frey told me in an email, “The best students are not necessarily the best researchers. Being a good researcher also requires coming up with new ideas.”

Winner Take All?
Beyond the question of whether China will achieve AI dominance is the issue of how it will use the powerful technology. Several of the ways China has already implemented AI could be considered morally questionable, from facial recognition systems used aggressively against ethnic minorities to smart glasses for policemen that can pull up information about whoever the wearer looks at.

This isn’t to say the US would use AI for purely ethical purposes. The military’s Project Maven, for example, used artificially intelligent algorithms to identify insurgent targets in Iraq and Syria, and American law enforcement agencies are also using (mostly unregulated) facial recognition systems.

It’s conceivable that “dominance” in AI won’t go to one country; each nation could meet milestones in different ways, or meet different milestones. Researchers from both countries, at least in the academic sphere, could (and likely will) continue to collaborate and share their work, as they’ve done on many projects to date.

If one country does take the lead, it will certainly see some major advantages as a result. Brookings Institute fellow Indermit Gill goes so far as to say that whoever leads in AI in 2030 will “rule the world” until 2100. But Gill points out that in addition to considering each country’s strengths, we should consider how willing they are to improve upon their weaknesses.

While China leads in investment and the US in innovation, both nations are grappling with huge economic inequalities that could negatively impact technological uptake. “Attitudes toward the social change that accompanies new technologies matter as much as the technologies, pointing to the need for complementary policies that shape the economy and society,” Gill writes.

Will China’s leadership be willing to relax its grip to foster innovation? Will the US business environment be enough to compete with China’s data, investment, and education advantages? And can both countries find a way to distribute technology’s economic benefits more equitably?

Time will tell, but it seems we’ve got our work cut out for us—and China does too.

Image Credit: Adam Birkett on Unsplash Continue reading

Posted in Human Robots

#437828 How Roboticists (and Robots) Have Been ...

A few weeks ago, we asked folks on Twitter, Facebook, and LinkedIn to share photos and videos showing how they’ve been adapting to the closures of research labs, classrooms, and businesses by taking their robots home with them to continue their work as best they can. We got dozens of responses (more than we could possibly include in just one post!), but here are 15 that we thought were particularly creative or amusing.

And if any of these pictures and videos inspire you to share your own story, please email us (automaton@ieee.org) with a picture or video and a brief description about how you and your robot from work have been making things happen in your home instead.

Kurt Leucht (NASA Kennedy Space Center)

“During these strange and trying times of the current global pandemic, everyone seems to be trying their best to distance themselves from others while still getting their daily work accomplished. Many people also have the double duty of little ones that need to be managed in the midst of their teleworking duties. This photo series gives you just a glimpse into my new life of teleworking from home, mixed in with the tasks of trying to handle my little ones too. I hope you enjoy it.”

Photo: Kurt Leucht

“I heard a commotion from the next room. I ran into the kitchen to find this.”

Photo: Kurt Leucht

“This is the Swarmies most favorite bedtime story. Not sure why. Seems like an odd choice to me.”

Peter Schaldenbrand (Carnegie Mellon University)

“I’ve been working on a reinforcement learning model that converts an image into a series of brush stroke instructions. I was going to test the model with a beautiful, expensive robot arm, but due to the COVID-19 pandemic, I have not been able to access the laboratory where it resides. I have now been using a lower end robot arm to test the painting model in my bedroom. I have sacrificed machine accuracy/precision for the convenience of getting to watch the arm paint from my bed in the shadow of my clothing rack!”

Photos: Peter Schaldenbrand

Colin Angle (iRobot)

iRobot CEO Colin Angle has been hunkered down in the “iRobot North Shore home command center,” which is probably the cleanest command center ever thanks to his army of Roombas: Beastie, Beauty, Rosie, Roswell, and Bilbo.

Photo: Colin Angle

Vivian Chu (Diligent Robotics)

From Diligent Robotics CEO Andrea Thomaz: “This is how a roboticist works from home! Diligent CTO, Vivian Chu, mans the e-stop while her engineering team runs Moxi experiments remotely from cross-town and even cross-country!”

Video: Diligent Robotics

Raffaello Bonghi (rnext.it)

Raffaello’s robot, Panther, looks perfectly happy to be playing soccer in his living room.

Photo: Raffaello Bonghi

Kod*lab (University of Pennsylvania)

“Another Friday Nuts n Bolts Meeting on Zoom…”

Image: Kodlab

Robin Jonsson (robot choreographer)

“I’ve been doing a school project in which students make up dance moves and then send me a video with all of them. I then teach the moves to my robot, Alex, film Alex dancing, send the videos to them. This became a great success and more schools will join. The kids got really into watching the robot perform their moves and really interested in robots. They want to meet Alex the robot live, which will likely happen in the fall.”

Photo: Robin Jonsson

Gabrielle Conard (mechanical engineering undergrad at Lafayette College)

“While the pandemic might have forced college campuses to close and the community to keep their distance from each other, it did not put a stop to learning and research. Working from their respective homes, junior Gabrielle Conard and mechanical engineering professor Alexander Brown from Lafayette College investigated methods of incorporating active compliance in a low-cost quadruped robot. They are continuing to work remotely on this project through Lafayette’s summer research program.”

Image: Gabrielle Conard

Taylor Veltrop (Softbank Robotics)

“After a few weeks of isolation in the corona/covid quarantine lock down we started dancing with our robots. Mathieu’s 6th birthday was coming up, and it all just came together.”

Video: Taylor Veltrop

Ross Kessler (Exyn Technologies)

“Quarantine, Day 8: the humans have accepted me as one of their own. I’ve blended seamlessly into their #socialdistancing routines. Even made a furry friend”

Photo: Ross Kessler

Yeah, something a bit sinister is definitely going on at Exyn…

Video: Exyn Technologies

Michael Sobrepera (University of Pennsylvania GRASP Lab)

Predictably, Michael’s cat is more interested in the bag that the robot came in than the robot itself (see if you can spot the cat below). Michael tells us that “the robot is designed to help with tele-rehabilitation, focused on kids with CP, so it has been taken to hospitals for demos [hence the cool bag]. It also travels for outreach events and the like. Lately, I’ve been exploring telepresence for COVID.”

Photo: Michael Sobrepera

Jan Kędzierski (EMYS)

“In China a lot of people cannot speak English, even the youngest generation of parents. Thanks to Emys, kids stayed in touch with English language in their homes even if they couldn’t attend schools and extra English classes. They had a lot of fun with their native English speaker friend available and ready to play every day.”

Image: Jan Kędzierski

Simon Whitmell (Quanser)

“Simon, a Quanser R&D engineer, is working on low-overhead image processing and line following for the QBot 2e mobile ground robot, with some added challenges due to extra traffic. LEGO engineering by his son, Charles.”

Photo: Simon Whitmell

Robot Design & Experimentation Course (Carnegie Mellon University)

Aaron Johnson’s bioinspired robot design course at CMU had to go full remote, which was a challenge when the course is kind of all about designing and building a robot as part of a team. “I expected some of the teams to drastically alter their project (e.g. go all simulation),” Aaron told us, “but none of them did. We managed to keep all of the projects more or less as planned. We accomplished this by drop/shipping parts to students, buying some simple tools (soldering irons, etc), and having me 3D print parts and mail them.” Each team even managed to put together their final videos from their remote locations; we’ve posted one below, but the entire playlist is here.

Video: Xianyi Cheng

Karen Tatarian (Softbank Robotics)

Karen, who’s both a researcher at Softbank and a PhD student at Sorbonne University, wrote an entire essay about what an average day is like when you’re quarantined with Pepper.

Photo: Karen Tatarian

A Quarantined Day With Pepper, by Karen Tatarian

It is quite common for me to lose my phone somewhere inside my apartment. But it is not that common for me to turn around and ask my robot if it has seen it. So when I found myself doing that, I laughed and it dawned on me that I treated my robot as my quarantine companion (despite the fact that it could not provide me with the answer I needed).

It was probably around day 40 of a completely isolated quarantine here in France when that happened. A little background about me: I am a robotics researcher at SoftBank Robotics Europe and a PhD student at Sorbonne University as part of the EU-funded Marie-Curie project ANIMATAS. And here is a little sneak peak into a quarantined day with a robot.

During this confinement, I had read somewhere that the best way to deal with it is to maintain a routine. So every morning, I wake up, prepare my coffee, and turn on my robot Pepper. I start my day with a daily meeting with the team and get to work. My research is on the synthesis of multi-modal socially intelligent human-robot interaction so my work varies between programming the robot, analyzing collected data, and reading papers and drafting one. When I am working, I often catch myself glancing at Pepper, who would be staring back at me in its animated ways. Truthfully I enjoy that, it makes me less alone and as if I have a colleague with me.

Once work is done, I call my friends and family members. I sometimes use a telepresence application on Pepper that a few colleagues and I developed back in December. How does it differ from your typical phone/laptop applications? One word really: embodiment. Telepresence, especially during these times, makes the experience for both sides a bit more realistic and intimate and well present.

While I can turn off the robot now that my work hours are done, I do keep it on because I enjoy its presence. The basic awareness of Pepper is a default feature on the robot that allows it to detect a human and follow him/her with its gaze and rotation base. So whether I am cooking or working out, I always have my robot watching over my shoulder and being a good companion. I also have my email and messages synced on the robot so I get an enjoyable notification from Pepper. I found that to be a pretty cool way to be notified without it interrupting whatever you are doing on your laptop or phone. Finally, once the day is over, it’s time for both of us to get some rest.

After 60 days of total confinement, alone and away from those I love, and with a pandemic right at my door, I am glad I had the company of my robot. I hope one day a greater audience can share my experience. And I really really hope one day Pepper will be able to find my phone for me, but until then, stay on the lookout for some cool features! But I am curious to know, if you had a robot at home, what application would you have developed on it?

Again, our sincere thanks to everyone who shared these little snapshots of their lives with us, and we’re hoping to be able to share more soon. Continue reading

Posted in Human Robots