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RoboCup 2019 took place earlier this month down in Sydney, Australia. While there are many different events including RoboCup@Home, RoboCup Rescue, and a bunch of different soccer leagues, one of the most compelling events is middle-size league (MSL), where mobile robots each about the size of a fire hydrant play soccer using a regular size FIFA soccer ball. The robots are fully autonomous, making their own decisions in real time about when to dribble, pass, and shoot.
The long-term goal of RoboCup is this:
By the middle of the 21st century, a team of fully autonomous humanoid robot soccer players shall win a soccer game, complying with the official rules of FIFA, against the winner of the most recent World Cup.
While the robots are certainly not there yet, they're definitely getting closer.
Even if you’re not a particular fan of soccer, it’s impressive to watch the robots coordinate with each other, setting up multiple passes and changing tactics on the fly in response to the movements of the other team. And the ability of these robots to shoot accurately is world-class (like, human world-class), as they’re seemingly able to put the ball in whatever corner of the goal they choose with split-second timing.
The final match was between Tech United from Eindhoven University of Technology in the Netherlands (whose robots are called TURTLE), and Team Water from Beijing Information Science & Technology University. Without spoiling it, I can tell you that the game was tied within just the last few seconds, meaning that it had to go to overtime. You can watch the entire match on YouTube, or a 5-minute commentated highlight video here:
It’s become a bit of a tradition to have the winning MSL robots play a team of what looks to be inexperienced adult humans wearing long pants and dress shoes.
The fact that the robots managed to score even once is pretty awesome, and it also looks like the robots are playing very conservatively (more so than the humans) so as not to accidentally injure any of us fragile meatbags with our spindly little legs. I get that RoboCup wants its first team of robots that can beat a human World Cup winning team to be humanoids, but at the moment, the MSL robots are where all the skill is.
To get calibrated on the state of the art for humanoid soccer robots, here’s the adult size final, Team Nimbro from the University of Bonn in Germany versus Team Sweaty from Offenburg University in Germany:
Yup, still a lot of falling over.
There’s lots more RoboCup on YouTube: Some channels to find more matches include the official RoboCup 2019 channel, and Tech United Eindhoven’s channel, which has both live English commentary and some highlight videos.
[ RoboCup 2019 ] Continue reading
The Tunnel Circuit of the DARPA Subterranean Challenge starts later this week at the NIOSH research mine just outside of Pittsburgh, Pennsylvania. From 15-22 August, 11 teams will send robots into a mine that they've never seen before, with the goal of making maps and locating items. All DARPA SubT events involve tunnels of one sort or another, but in this case, the “Tunnel Circuit” refers to mines as opposed to urban underground areas or natural caves. This month’s challenge is the first of three discrete events leading up to a huge final event in August of 2021.
While the Tunnel Circuit competition will be closed to the public, and media are only allowed access for a single day (which we'll be at, of course), DARPA has provided a substantial amount of information about what teams will be able to expect. We also have details from the SubT Integration Exercise, called STIX, which was a completely closed event that took place back in April. STIX was aimed at giving some teams (and DARPA) a chance to practice in a real tunnel environment.
For more general background on SubT, here are some articles to get you all caught up:
SubT: The Next DARPA Challenge for Robotics
Q&A with DARPA Program Manager Tim Chung
Meet The First Nine Teams
It makes sense to take a closer look at what happened at April's STIX exercise, because it is (probably) very similar to what teams will experience in the upcoming Tunnel Circuit. STIX took place at Edgar Experimental Mine in Colorado, and while no two mines are the same (and many are very, very different), there are enough similarities for STIX to have been a valuable experience for teams. Here's an overview video of the exercise from DARPA:
DARPA has also put together a much more detailed walkthrough of the STIX mine exercise, which gives you a sense of just how vast, complicated, and (frankly) challenging for robots the mine environment is:
So, that's the kind of thing that teams had to deal with back in April. Since the event was an exercise, rather than a competition, DARPA didn't really keep score, and wouldn't comment on the performance of individual teams. We've been trolling YouTube for STIX footage, though, to get a sense of how things went, and we found a few interesting videos.
Here's a nice overview from Team CERBERUS, which used drones plus an ANYmal quadruped:
Team CTU-CRAS also used drones, along with a tracked robot:
Team Robotika was brave enough to post video of a “fatal failure” experienced by its wheeled robot; the poor little bot gets rescued at about 7:00 in case you get worried:
So that was STIX. But what about the Tunnel Circuit competition this week? Here's a course preview video from DARPA:
It sort of looks like the NIOSH mine might be a bit less dusty than the Edgar mine was, but it could also be wetter and muddier. It’s hard to tell, because we’re just getting a few snapshots of what’s probably an enormous area with kilometers of tunnels that the robots will have to explore. But DARPA has promised “constrained passages, sharp turns, large drops/climbs, inclines, steps, ladders, and mud, sand, and/or water.” Combine that with the serious challenge to communications imposed by the mine itself, and robots will have to be both physically capable, and almost entirely autonomous. Which is, of course, exactly what DARPA is looking to test with this challenge.
Lastly, we had a chance to catch up with Tim Chung, Program Manager for the Subterranean Challenge at DARPA, and ask him a few brief questions about STIX and what we have to look forward to this week.
IEEE Spectrum: How did STIX go?
Tim Chung: It was a lot of fun! I think it gave a lot of the teams a great opportunity to really get a taste of what these types of real world environments look like, and also what DARPA has in store for them in the SubT Challenge. STIX I saw as an experiment—a learning experience for all the teams involved (as well as the DARPA team) so that we can continue our calibration.
What do you think teams took away from STIX, and what do you think DARPA took away from STIX?
I think the thing that teams took away was that, when DARPA hosts a challenge, we have very audacious visions for what the art of the possible is. And that's what we want—in my mind, the purpose of a DARPA Grand Challenge is to provide that inspiration of, ‘Holy cow, someone thinks we can do this!’ So I do think the teams walked away with a better understanding of what DARPA's vision is for the capabilities we're seeking in the SubT Challenge, and hopefully walked away with a better understanding of the technical, physical, even maybe mental challenges of doing this in the wild— which will all roll back into how they think about the problem, and how they develop their systems.
This was a collaborative exercise, so the DARPA field team was out there interacting with the other engineers, figuring out what their strengths and weaknesses and needs might be, and even understanding how to handle the robots themselves. That will help [strengthen] connections between these university teams and DARPA going forward. Across the board, I think that collaborative spirit is something we really wish to encourage, and something that the DARPA folks were able to take away.
What do we have to look forward to during the Tunnel Circuit?
The vision here is that the Tunnel Circuit is representative of one of the three subterranean subdomains, along with urban and cave. Characteristics of all of these three subdomains will be mashed together in an epic final course, so that teams will have to face hints of tunnel once again in that final event.
Without giving too much away, the NIOSH mine will be similar to the Edgar mine in that it's a human-made environment that supports mining operations and research. But of course, every site is different, and these differences, I think, will provide good opportunities for the teams to shine.
Again, we'll be visiting the NIOSH mine in Pennsylvania during the Tunnel Circuit and will post as much as we can from there. But if you’re an actual participant in the Subterranean Challenge, please tweet me @BotJunkie so that I can follow and help share live updates.
[ DARPA Subterranean Challenge ] Continue reading
The first competitive event in the DARPA Subterranean Challenge concluded last week—hopefully you were able to follow along on the livestream, on Twitter, or with some of the articles that we’ve posted about the event. We’ll have plenty more to say about how things went for the SubT teams, but while they take a bit of a (well earned) rest, we can take a look at the winning teams as well as who won DARPA’s special superlative awards for the competition.
First Place: Team Explorer (25/40 artifacts found)
With their rugged, reliable robots featuring giant wheels and the ability to drop communications nodes, Team Explorer was in the lead from day 1, scoring in double digits on every single run.
Second Place: Team CoSTAR (11/40 artifacts found)
Team CoSTAR had one of the more diverse lineups of robots, and they switched up which robots they decided to send into the mine as they learned more about the course.
Third Place: Team CTU-CRAS (10/40 artifacts found)
While many teams came to SubT with DARPA funding, Team CTU-CRAS was self-funded, making them eligible for a special $200,000 Tunnel Circuit prize.
DARPA also awarded a bunch of “superlative awards” after SubT:
Most Accurate Artifact: Team Explorer
To score a point, teams had to submit the location of an artifact that was correct to within 5 meters of the artifact itself. However, DARPA was tracking the artifact locations with much higher precision—for example, the “zero” point on the backpack artifact was the center of the label on the front, which DARPA tracked to the millimeter. Team Explorer managed to return the location of a backpack with an error of just 0.18 meter, which is kind of amazing.
Down to the Wire: Team CSIRO Data61
With just an hour to find as many artifacts as possible, teams had to find the right balance between sending robots off to explore and bringing them back into communication range to download artifact locations. Team CSIRO Data61 cut their last point pretty close, sliding their final point in with a mere 22 seconds to spare.
Most Distinctive Robots: Team Robotika
Team Robotika had some of the quirkiest and most recognizable robots, which DARPA recognized with the “Most Distinctive” award. Robotika told us that part of the reason for that distinctiveness was practical—having a robot that was effectively in two parts meant that they could disassemble it so that it would fit in the baggage compartment of an airplane, very important for a team based in the Czech Republic.
Most Robots Per Person: Team Coordinated Robotics
Kevin Knoedler, who won NASA’s Space Robotics Challenge entirely by himself, brought his own personal swarm of drones to SubT. With a ratio of seven robots to one human, Kevin was almost certainly the hardest working single human at the challenge.
Fan Favorite: Team NCTU
Photo: Evan Ackerman/IEEE Spectrum
The Fan Favorite award went to the team that was most popular on Twitter (with the #SubTChallenge hashtag), and it may or may not be the case that I personally tweeted enough about Team NCTU’s blimp to win them this award. It’s also true that whenever we asked anyone on other teams what their favorite robot was (besides their own, of course), the blimp was overwhelmingly popular. So either way, the award is well deserved.
DARPA shared this little behind-the-scenes clip of the blimp in action (sort of), showing what happened to the poor thing when the mine ventilation system was turned on between runs and DARPA staff had to chase it down and rescue it:
The thing to keep in mind about the results of the Tunnel Circuit is that unlike past DARPA robotics challenges (like the DRC), they don’t necessarily indicate how things are going to go for the Urban or Cave circuits because of how different things are going to be. Explorer did a great job with a team of rugged wheeled vehicles, which turned out to be ideal for navigating through mines, but they’re likely going to need to change things up substantially for the rest of the challenges, where the terrain will be much more complex.
DARPA hasn’t provided any details on the location of the Urban Circuit yet; all we know is that it’ll be sometime in February 2020. This gives teams just six months to take all the lessons that they learned from the Tunnel Circuit and update their hardware, software, and strategies. What were those lessons, and what do teams plan to do differently next year? Check back next week, and we’ll tell you.
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Artificially intelligent systems are slowly taking over tasks previously done by humans, and many processes involving repetitive, simple movements have already been fully automated. In the meantime, humans continue to be superior when it comes to abstract and creative tasks.
However, it seems like even when it comes to creativity, we’re now being challenged by our own creations.
In the last few years, we’ve seen the emergence of hundreds of “AI artists.” These complex algorithms are creating unique (and sometimes eerie) works of art. They’re generating stunning visuals, profound poetry, transcendent music, and even realistic movie scripts. The works of these AI artists are raising questions about the nature of art and the role of human creativity in future societies.
Here are a few works of art created by non-human entities.
Ai-Da Robot with Painting. Image Credit: Ai-Da portraits by Nicky Johnston. Published with permission from Midas Public Relations.
Earlier this month we saw the announcement of Ai.Da, considered the first ultra-realistic drawing robot artist. Her mechanical abilities, combined with AI-based algorithms, allow her to draw, paint, and even sculpt. She is able to draw people using her artificial eye and a pencil in her hand. Ai.Da’s artwork and first solo exhibition, Unsecured Futures, will be showcased at Oxford University in July.
Ai-Da Cartesian Painting. Image Credit: Ai-Da Artworks. Published with permission from Midas Public Relations.
Obviously Ai.Da has no true consciousness, thoughts, or feelings. Despite that, the (human) organizers of the exhibition believe that Ai.Da serves as a basis for crucial conversations about the ethics of emerging technologies. The exhibition will serve as a stimulant for engaging with critical questions about what kind of future we ought to create via such technologies.
The exhibition’s creators wrote, “Humans are confident in their position as the most powerful species on the planet, but how far do we actually want to take this power? To a Brave New World (Nightmare)? And if we use new technologies to enhance the power of the few, we had better start safeguarding the future of the many.”
Our transcendence adorns,
That society of the stars seem to be the secret.
The two lines of poetry above aren’t like any poetry you’ve come across before. They are generated by an algorithm that was trained via deep learning neural networks trained on 20 million words of 19th-century poetry.
Google’s latest art project, named PoemPortraits, takes a word of your suggestion and generates a unique poem (once again, a collaboration of man and machine). You can even add a selfie in the final “PoemPortrait.” Artist Es Devlin, the project’s creator, explains that the AI “doesn’t copy or rework existing phrases, but uses its training material to build a complex statistical model. As a result, the algorithm generates original phrases emulating the style of what it’s been trained on.”
The generated poetry can sometimes be profound, and sometimes completely meaningless.But what makes the PoemPortraits project even more interesting is that it’s a collaborative project. All of the generated lines of poetry are combined to form a consistently growing collective poem, which you can view after your lines are generated. In many ways, the final collective poem is a collaboration of people from around the world working with algorithms.
Faceless Portraits Transcending Time
AICAN + Ahmed Elgammal
Image Credit: AICAN + Ahmed Elgammal | Faceless Portrait #2 (2019) | Artsy.
In March of this year, an AI artist called AICAN and its creator Ahmed Elgammal took over a New York gallery. The exhibition at HG Commentary showed two series of canvas works portraying harrowing, dream-like faceless portraits.
The exhibition was not simply credited to a machine, but rather attributed to the collaboration between a human and machine. Ahmed Elgammal is the founder and director of the Art and Artificial Intelligence Laboratory at Rutgers University. He considers AICAN to not only be an autonomous AI artist, but also a collaborator for artistic endeavors.
How did AICAN create these eerie faceless portraits? The system was presented with 100,000 photos of Western art from over five centuries, allowing it to learn the aesthetics of art via machine learning. It then drew from this historical knowledge and the mandate to create something new to create an artwork without human intervention.
by AIVA Technologies
Listen to the score above. While you do, reflect on the fact that it was generated by an AI.
AIVA is an AI that composes soundtrack music for movies, commercials, games, and trailers. Its creative works span a wide range of emotions and moods. The scores it generates are indistinguishable from those created by the most talented human composers.
The AIVA music engine allows users to generate original scores in multiple ways. One is to upload an existing human-generated score and select the temp track to base the composition process on. Another method involves using preset algorithms to compose music in pre-defined styles, including everything from classical to Middle Eastern.
Currently, the platform is promoted as an opportunity for filmmakers and producers. But in the future, perhaps every individual will have personalized music generated for them based on their interests, tastes, and evolving moods. We already have algorithms on streaming websites recommending novel music to us based on our interests and history. Soon, algorithms may be used to generate music and other works of art that are tailored to impact our unique psyches.
The Future of Art: Pushing Our Creative Limitations
These works of art are just a glimpse into the breadth of the creative works being generated by algorithms and machines. Many of us will rightly fear these developments. We have to ask ourselves what our role will be in an era where machines are able to perform what we consider complex, abstract, creative tasks. The implications on the future of work, education, and human societies are profound.
At the same time, some of these works demonstrate that AI artists may not necessarily represent a threat to human artists, but rather an opportunity for us to push our creative boundaries. The most exciting artistic creations involve collaborations between humans and machines.
We have always used our technological scaffolding to push ourselves beyond our biological limitations. We use the telescope to extend our line of sight, planes to fly, and smartphones to connect with others. Our machines are not always working against us, but rather working as an extension of our minds. Similarly, we could use our machines to expand on our creativity and push the boundaries of art.
Image Credit: Ai-Da portraits by Nicky Johnston. Published with permission from Midas Public Relations. Continue reading