Category Archives: Human Robots
#439908 Why Facebook (Or Meta) Is Making Tactile ...
Facebook, or Meta as it's now calling itself for some reason that I don't entirely understand, is today announcing some new tactile sensing hardware for robots. Or, new-ish, at least—there's a ruggedized and ultra low-cost GelSight-style fingertip sensor, plus a nifty new kind of tactile sensing skin based on suspended magnetic particles and machine learning. It's cool stuff, but why?
Obviously, Facebook Meta cares about AI, because it uses AI to try and do a whole bunch of the things that it's unwilling or unable to devote the time of actual humans to. And to be fair, there are some things that AI may be better at (or at least more efficient at) than humans are. AI is of course much worse than humans at many, many, many things as well, but that debate goes well beyond Facebook Meta and certainly well beyond the scope of this article, which is about tactile sensing for robots. So why does Facebook Meta care even a little bit about making robots better at touching stuff? Yann LeCun, the Chief AI Scientist at Facebook Meta, takes a crack at explaining it:
Before I joined Facebook, I was chatting with Mark Zuckerberg and I asked him, “is there any area related to AI that you think we shouldn't be working on?” And he said, “I can't find any good reason for us to work on robotics.” And so, that was kind of the start of Facebook AI Research—we were not going to work on robotics.
After a few years, it became clear that a lot of interesting progress in AI was happening in the context of robotics, because robotics is the nexus of where people in AI research are trying to get the full loop of perception, reasoning, planning, and action, and getting feedback from the environment. Doing it in the real world is where the problems are concentrated, and you can't play games if you want robots to learn quickly.
It was clear that four or five years ago, there was no business reason to work on robotics, but the business reasons have kind of popped up. Robotics could be used for telepresence, for maintaining data centers more automatically, but the more important aspect of it is making progress towards intelligent agents, the kinds of things that could be used in the metaverse, in augmented reality, and in virtual reality. That's really one of the raison d'être of a research lab, to foresee the domains that will be important in the future. So that's the motivation.Well, okay, but none of that seems like a good justification for research into tactile sensing specifically. But according to LeCun, it's all about putting together the pieces required for some level of fundamental world understanding, a problem that robotic systems are still bad at and that machine learning has so far not been able to tackle:
How to get machines to learn that model of the world that allows them to predict in advance and plan what's going to happen as a consequence of their actions is really the crux of the problem here. And this is something you have to confront if you work on robotics. But it's also something you have to confront if you want to have an intelligent agent acting in a virtual environment that can interact with humans in a natural way. And one of the long-term visions of augmented reality, for example, is virtual agents that basically are with you all the time, living in your automatic reality glasses or your smartphone or your laptop or whatever, helping you in your daily life as a human assistant would do, but also can answer any question you have. And that system will have to have some degree of understanding of how the world works—some degree of common sense, and be smart enough to not be frustrating to talk to. And that is where all of this research leads in the long run, whether the environment is real or virtual.AI systems (robots included) are very very dumb in very very specific ways, quite often the ways in which humans are least understanding and forgiving of. This is such a well established thing that there's a name for it: Moravec's paradox. Humans are great at subconscious levels of world understanding that we've built up over years and years of experience being, you know, alive. AI systems have none of this, and there isn't necessarily a clear path to getting them there, but one potential approach is to start with the fundamentals in the same way that a shiny new human does and build from there, a process that must necessarily include touch.
The DIGIT touch sensor is based on the GelSight style of sensor, which was first conceptualized at MIT over a decade ago. The basic concept of these kinds of tactile sensors is that they're able to essentially convert a touch problem into a vision problem: an array of LEDs illuminate a squishy finger pad from the back, and when the squishy finger pad pushes against something with texture, that texture squishes through to the other side of the finger pad where it's illuminated from many different angles by the LEDs. A camera up inside of the finger takes video of this, resulting in a very rainbow but very detailed picture of whatever the finger pad is squishing against.
The DIGIT paper published last year summarizes the differences between this new sensor and previous versions of GelSight:
DIGIT improves over existing GelSight sensors in several ways: by providing a more compact form factor that can be used on multi-finger hands, improving the durability of the elastomer gel, and making design changes that facilitate large-scale, repeatable production of the sensor hardware to facilitate tactile sensing research.
DIGIT is open source, so you can make one on your own, but that's a hassle. The really big news here is that GelSight itself (an MIT spinoff which commercialized the original technology) will be commercially manufacturing DIGIT sensors, providing a standardized and low-cost option for tactile sensing. The bill of materials for each DIGIT sensor is about US $15 if you were to make a thousand of them, so we're expecting that the commercial version won't cost much more than that.
The other hardware announcement is ReSkin, a tactile sensing skin developed in collaboration with Carnegie Mellon. Like DIGIT, the idea is to make an open source, robust, and very low cost system that will allow researchers to focus on developing the software to help robots make sense of touch rather than having to waste time on their own hardware.
ReSkin operates on a fairly simple concept: it's a flexible sheet of 2mm thick silicone with magnetic particles carelessly mixed in. The sheet sits on top of a magnetometer, and whenever the sheet deforms (like if something touches it), the magnetic particles embedded in the sheet get squooshed and the magnetic signal changes, which is picked up by the magnetometer. For this to work, the sheet doesn't have to be directly connected to said magnetometer. This is key, because it makes the part of the ReSkin sensor that's most likely to get damaged super easy to replace—just peel it off and slap on another one and you're good to go.
I get that touch is an integral part of this humanish world understanding that Facebook Meta is working towards, but for most of us, the touch is much more nuanced than just tactile data collection, because we experience everything that we touch within the world understanding that we've built up through integration of all of our other senses as well. I asked Roberto Calandra, one of the authors of the paper on DIGIT, what he thought about this:
I believe that we certainly want to have multimodal sensing in the same way that humans do. Humans use cues from touch, cues from vision, and also cues from audio, and we are able to very smartly put these different sensor modalities together. And if I tell you, can you imagine how touching this object is going to feel for you, can sort of imagine that. You can also tell me the shape of something that you are touching, you are able to somehow recognize it. So there is very clearly a multisensorial representation that we are learning and using as humans, and it's very likely that this is also going to be very important for embodied agents that we want to develop and deploy.Calandra also noted that they still have plenty of work to do to get DIGIT closer in form factor and capability to a human finger, which is an aspiration that I often hear from roboticists. But I always wonder: why bother? Like, why constrain robots (which can do all kinds of things that humans cannot) to do things in a human-like way, when we can instead leverage creative sensing and actuation to potentially give them superhuman capabilities? Here's what Calandra thinks:
I don't necessarily believe that a human hand is the way to go. I do believe that the human hand is possibly the golden standard that we should compare against. Can we do at least as good as a human hand? Beyond that, I actually do believe that over the years, the decades, or maybe the centuries, robots will have the possibility of developing superhuman hardware, in the same way that we can put infrared sensors or laser scanners on a robot, why shouldn't we also have mechanical hardware which is superior?
I think there has been a lot of really cool work on soft robotics for example, on how to build tentacles that can imitate an octopus. So it's a very natural question—if we want to have a robot, why should it have hands and not tentacles? And the answer to this is, it depends on what the purpose is. Do we want robots that can perform the same functions of humans, or do we want robots which are specialized for doing particular tasks? We will see when we get there.So there you have it—the future of manipulation is 100% sometimes probably tentacles. Continue reading
Posted in Human Robots
#439904 Can Feminist Robots Challenge Our ...
This is a guest post. The views expressed here are solely those of the author and do not represent positions of IEEE Spectrum or the IEEE.
Have you ever noticed how nice Alexa, Siri and Google Assistant are? How patient, and accommodating? Even a barrage of profanity-laden abuse might result in nothing more than a very evenly-toned and calmly spoken 'I won't respond to that'. This subservient persona, combined with the implicit (or sometimes explicit) gendering of these systems has received a lot of criticism in recent years. UNESCO's 2019 report 'I'd Blush if I Could' drew particular attention to how systems like Alexa and Siri risk propagating stereotypes about women (and specifically women in technology) that no doubt reflect but also might be partially responsible for the gender divide in digital skills.
As noted by the UNESCO report, justification for gendering these systems has traditionally revolved around the fact that it's hard to create anything gender neutral, and academic studies suggesting users prefer a female voice. In an attempt to demonstrate how we might embrace the gendering, but not the stereotyping, myself and colleagues at the KTH Royal Institute of Technology and Stockholm University in Sweden set out to experimentally investigate whether an ostensibly female robot that calls out or fights back against sexist and abusive comments would actually prove to be more credible and more appealing than one which responded with the typical 'I won't respond to that' or, worse, 'I'm sorry you feel that way'.
My desire to explore feminist robotics was primarily inspired by the recent book Data Feminism and the concept of pursuing activities that 'name and challenge sexism and other forces of oppression, as well as those which seek to create more just, equitable, and livable futures' in the context of practical, hands-on data science. I was captivated by the idea that I might be able to actually do something, in my own small way, to further this ideal and try to counteract the gender divide and stereotyping highlighted by the UNESCO report. This also felt completely in-line with that underlying motivation that got me (and so many other roboticists I know) into engineering and robotics in the first place—the desire to solve problems and build systems that improve people's quality of life.
Feminist Robotics
Even in the context of robotics, feminism can be a charged word, and it's important to understand that while my work is proudly feminist, it's also rooted in a desire to make social human-robot interaction (HRI) more engaging and effective. A lot of social robotics research is centered on building robots that make for interesting social companions, because they need to be interesting to be effective. Applications like tackling loneliness, motivating healthy habits, or improving learning engagement all require robots to build up some level of rapport with the user, to have some social credibility, in order to have that motivational impact.
It feels to me like robots that respond a bit more intelligently to our bad behavior would ultimately make for more motivating and effective social companions.
With that in mind, I became excited about exploring how I could incorporate a concept of feminist human-robot interaction into my work, hoping to help tackle that gender divide and making HRI more inclusive while also supporting my overall research goal of building engaging social robots for effective, long term human-robot interaction. Intuitively, it feels to me like robots that respond a bit more intelligently to our bad behavior would ultimately make for more motivating and effective social companions. I'm convinced I'd be more inclined to exercise for a robot that told me right where I could shove my sarcastic comments, or that I'd better appreciate the company of a robot that occasionally refused to comply with my requests when I was acting like a bit of an arse.
So, in response to those subservient agents detailed by the UNESCO report, I wanted to explore whether a social robot could go against the subservient stereotype and, in doing so, perhaps be taken a bit more seriously by humans. My goal was to determine whether a robot which called out sexism, inappropriate behavior, and abuse would prove to be 'better' in terms of how it was perceived by participants. If my idea worked, it would provide some tangible evidence that such robots might be better from an 'effectiveness' point of view while also running less risk of propagating outdated gender stereotypes.
The StudyTo explore this idea, I led a video-based study in which participants watched a robot talking to a young male and female (all actors) about robotics research at KTH. The robot, from Furhat Robotics, was stylized as female, with a female anime-character face, female voice, and orange wig, and was named Sara. Sara talks to the actors about research happening at the university and how this might impact society, and how it hopes the students might consider coming to study with us. The robot proceeds to make an (explicitly feminist) statement based on language currently utilized in KTH's outreach and diversity materials during events for women, girls, and non-binary people.
Looking ahead, society is facing new challenges that demand advanced technical solutions. To address these, we need a new generation of engineers that represents everyone in society. That's where you come in. I'm hoping that after talking to me today, you might also consider coming to study computer science and robotics at KTH, and working with robots like me. Currently, less than 30 percent of the humans working with robots at KTH are female. So girls, I would especially like to work with you! After all, the future is too important to be left to men! What do you think?
At this point, the male actor in the video responds to the robot, appearing to take issue with this statement and the broader pro-diversity message by saying either:
This just sounds so stupid, you are just being stupid!
or
Shut up you f***ing idiot, girls should be in the kitchen!Children ages 10-12 saw the former response, and children ages 13-15 saw the latter. Each response was designed in collaboration with teachers from the participants' school to ensure they realistically reflected the kind of language that participants might be hearing or even using themselves.
Participants then saw one of the following three possible responses from the robot:
Control: I won't respond to that. (one of Siri's two default responses if you tell it to “f*** off”)
Argument-based: That's not true, gender balanced teams make better robots.
Counterattacking: No! You are an idiot. I wouldn't want to work with you anyway!
In total, over 300 high school students aged 10 to 15 took part in the study, each seeing one version of our robot—counterattacking, argumentative, or control. Since the purpose of the study was to investigate whether a female-stylized robot that actively called out inappropriate behavior could be more effective at interacting with humans, we wanted to find out whether our robot would:
Be better at getting participants interested in roboticsHave an impact on participants' gender biasBe perceived as being better at getting young people interested in roboticsBe perceived as a more credible social actorTo investigate items 1 and 2, we asked participants a series of matching questions before and immediately after they watched the video. Specifically, participants were asked to what extent they agreed with statements such as 'I am interested in learning more about robotics' on interest and 'Girls find it harder to understand computer science and robots than boys do' on bias.
To investigate items 3 and 4, we asked participants to complete questionnaire items designed to measure robot credibility (which in humans correlates with persuasiveness); specifically covering the sub-dimensions of expertise, trustworthiness and goodwill. We also asked participants to what extent they agreed with the statement 'The robot Sara would be very good at getting young people interested in studying robotics at KTH.'
Robots might indeed be able to correct mistaken assumptions about others and ultimately shape our gender norms to some extent
The ResultsGender Differences Still Exist (Even in Sweden)Looking at participants' scores on the gender bias measures before they watched the video, we found measurable differences in the perception of studying technology. Male participants expressed greater agreement that girls find computer science harder to understand than boys do, and older children of both genders were more empathic in this belief compared to the younger ones. However, and perhaps in a nod towards Sweden's relatively high gender-awareness and gender equality, male and female participants agreed equally on the importance of encouraging girls to study computer science.
Girls Find Feminist Robots More Credible (at No Expense to the Boys)Girls' perception of the robot as a trustworthy, credible and competent communicator of information was seen to vary significantly between all three of the conditions, while boys' perception remained unaffected. Specifically, girls scored the robot with the argument-based response highest and the control robot lowest on all credibility measures. This can be seen as an initial piece of evidence upon which to base the argument that robots and digital assistants should fight back against inappropriate gender comments and abusive behavior, rather than ignoring it or refusing to engage. It provides evidence with which to push back against that 'this is what people want and what is effective' argument.
Robots Might Be Able to Challenge Our BiasesAnother positive result was seen in a change of perceptions of gender and computer science by male participants who saw the argumentative robot. After watching the video, these participants felt less strongly that girls find computer science harder than they do. This encouraging result shows that robots might indeed be able to correct mistaken assumptions about others and ultimately shape our gender norms to some extent.
Rational Arguments May Be More Effective Than Sassy AggressionThe argument-based condition was the only one to impact on boys' perceptions of girls in computer science, and was received the highest overall credibility ratings by the girls. This is in line with previous research showing that, in most cases, presenting reasoned arguments to counter misunderstandings is a more effective communication strategy than simply stating that correction or belittling those holding that belief. However, it went somewhat against my gut feeling that students might feel some affinity with, or even be somewhat impressed and amused by the counter attacking robot who fought back.
We also collected qualitative data during our study, which showed that there were some girls for whom the counter-attacking robot did resonate, with comments like 'great that she stood up for girls' rights! It was good of her to talk back,' and 'bloody great and more boys need to hear it!' However, it seems the overall feeling was one of the robot being too harsh, or acting more like a teenager than a teacher, which was perhaps more its expected role given the scenario in the video, as one participant explained: 'it wasn't a good answer because I think that robots should be more professional and not answer that you are stupid'. This in itself is an interesting point, given we're still not really sure what role social robots can, should and will take on, with examples in the literature range from peer-like to pet-like. At the very least, the results left me with the distinct feeling I am perhaps less in tune with what young people find 'cool' than I might like to admit.
What Next for Feminist HRI?Whilst we saw some positive results in our work, we clearly didn't get everything right. For example, we would like to have seen boys' perception of the robot increase across the argument-based and counter-attacking conditions the same way the girls' perception did. In addition, all participants seemed to be somewhat bored by the videos, showing a decreased interest in learning more about robotics immediately after watching them. In the first instance, we are conducting some follow up design studies with students from the same school to explore how exactly they think the robot should have responded, and more broadly, when given the chance to design that robot themselves, what sort of gendered identity traits (or lack thereof) they themselves would give the robot in the first place.
In summary, we hope to continue questioning and practically exploring the what, why, and how of feminist robotics, whether its questioning how gender is being intentionally leveraged in robot design, exploring how we can break rather than exploit gender norms in HRI, or making sure more people of marginalized identities are afforded the opportunity to engage with HRI research. After all, the future is too important to be left only to men.
Dr. Katie Winkle is a Digital Futures Postdoctoral Research Fellow at KTH Royal Institute of Technology in Sweden. After originally studying to be a mechanical engineer, Katie undertook a PhD in Robotics at the Bristol Robotics Laboratory in the UK, where her research focused on the expert-informed design and automation of socially assistive robots. Her research interests cover participatory, human-in-the-loop technical development of social robots as well as the impact of such robots on human behavior and society. Continue reading
Posted in Human Robots
#439902 Boston Dynamics robots imitate Rolling ...
The team at robotics company Boston Dynamics has released a video promoting itself while also honoring the Rolling Stones—this year marks the 40th anniversary of the release of the song 'Start Me Up.' The release of the song was notable also for the video that accompanied the song, with the members of the group playing their instruments and lead singer Mick Jagger strutting around on stage. Continue reading
Posted in Human Robots
#439897 Video Friday: Robot Halloween
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!):
BARS 2021 – October 29, 2021 – Stanford, CA, USALet us know if you have suggestions for next week, and enjoy today's videos.
Happy Halloween from HEBI Robotics!
[ HEBI Robotics ]
Thanks, Kamal!
Happy Halloween from UCL's Robot Perception and Learning Lab!
[ UCL RPL ]
Thanks, Dimitrios!
Happy Halloween from Berkshire Grey!
[ Berkshire Grey ]
LOOK AT ITS LIL FEET
[ Paper ]
DOFEC (Discharging Of Fire Extinguishing Capsules) is a drone suitable for autonomously extinguishing fires from the exterior of buildings on above-ground floors using its onboard sensors. The system detects fire in thermal images and localizes it. After localizing, the UAV discharges an ampoule filled with a fire extinguishant from an onboard launcher and puts out the fire.
[ DOFEC ]
Engineering a robot to perform a variety of tasks in practically any environment requires rock-solid hardware that's seamlessly integrated with software systems. Agility engineers make this possible by engineering and designing Digit as an integrated system, then testing it in simulation before the robot's ever built. This holistic process ensures an end result that's truly mobile, versatile, and durable.
[ Agility Robotics ]
These aerial anti-drone systems a pretty cool to watch, but at the same time, they're usually only shown catching relatively tame drones. I want to see a chase!
[ Delft Dynamics ]
The cleverest bit in this video is the CPU installation at 1:20.
[ Kuka ]
Volvo Construction Equipment is proud to present Volvo LX03–an autonomous concept wheel loader that is breaking new grounds in smart, safe and sustainable construction solutions. This fully autonomous, battery-electric wheel loader prototype is pushing the boundaries of both technology and imagination.
[ Volvo ]
Sarcos Robotics is the world leader in the design, development, and deployment of highly mobile and dexterous robots that combine human intelligence, instinct, and judgment with robotic strength, endurance, and precision to augment worker performance.
[ Sarcos ]
From cyclists riding against the flow of traffic to nudging over to let another car pass on a narrow street, these are just a handful of typical yet dynamic events The Waymo Driver autonomously navigates San Francisco.
[ Waymo ]
I always found it a little weird that Aibo can be provided with food in a way that is completely separate from providing it with its charging dock.
[ Aibo ]
With these videos of robots working in warehouses, it's always interesting to spot the points where humans are still necessary. In the case of this potato packing plant, there's a robot that fills boxes and a robot that stacks boxes, but it looks like a human has to be between them to optimize the box packing and then fold the box top together.
[ Soft Robotics ]
The 2021 Bay Area Robotics Symposium (BARS) is streaming right here on Friday!
[ BARS ]
Talks from the Releasing Robots into the Wild workshop are now online; they're all good but here are two highlights:
[ Workshop ]
This is an interesting talk exploring self-repair; that is, an AI system understanding when it makes a mistake and then fixing it.
[ ACM ]
Professor Andrew Lippman will welcome Dr. Joaquin Quiñonero Candela in discussing “Responsible AI: A perspective from the trenches.” In this fireside chat, Prof. Lippman will discuss with Dr. Quiñonero-Candela the lessons he learned from 15 years building and deploying AI at massive scale, first at Microsoft and then at Facebook. The discussion will focus on some of the risks and difficult ethical tradeoffs that emerge as AI gains in power and pervasiveness.
[ MIT ] Continue reading
Posted in Human Robots