Tag Archives: knowledge

#436042 Video Friday: Caltech’s Drone With ...

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!):

ISRR 2019 – October 6-10, 2019 – Hanoi, Vietnam
Ro-Man 2019 – October 14-18, 2019 – New Delhi, India
Humanoids 2019 – October 15-17, 2019 – Toronto, Canada
ARSO 2019 – October 31-1, 2019 – Beijing, China
ROSCon 2019 – October 31-1, 2019 – Macau
IROS 2019 – November 4-8, 2019 – Macau
Let us know if you have suggestions for next week, and enjoy today’s videos.

Caltech has been making progress on LEONARDO (LEg ON Aerial Robotic DrOne), their leggy thruster powered humanoid-thing. It can now balance and walk, which is quite impressive to see.

We’ll circle back again when they’ve got it jumping and floating around.

[ Caltech ]

Turn the subtitles on to learn how robots became experts at slicing bubbly, melty, delicious cheese.

These robots learned how to do the traditional Swiss raclette from demonstration. The Robot Learning & Interaction group at the Idiap Research Institute has developed an imitation learning technique allowing the robot to acquire new skills by considering position and force information, with an automatic adaptation to new situations. The range of applications is wide, including industrial robots, service robots, and assistive robots.

[ Idiap ]

Thanks Sylvain!

Some amazing news this week from Skydio, with the announcement of their better in every single way Skydio 2 autonomous drone. Read our full article for details, but here’s a getting started video that gives you an overview of what the drone can do.

The first batch sold out in 36 hours, but you can put down a $100 deposit to reserve the $999 drone for 2020 delivery.

[ Skydio ]

UBTECH is introducing a couple new robot kits for the holidays: ChampBot and FireBot.

$130 each, available on October 20.

[ Ubtech ]

NASA’s InSight lander on Mars is trying to use its robotic arm to get the mission’s heat flow probe, or mole, digging again. InSight team engineer Ashitey Trebbi-Ollennu, based at NASA’s Jet Propulsion Laboratory in Pasadena, California, explains what has been attempted and the game plan for the coming weeks. The next tactic they’ll try will be “pinning” the mole against the hole it’s in.

[ NASA ]

We introduce shape-changing swarm robots. A swarm of self-transformable robots can both individually and collectively change their configuration to display information, actuate objects, act as tangible controllers, visualize data, and provide physical affordances. ShapeBots is a concept prototype of shape-changing swarm robots. Each robot can change its shape by leveraging small linear actuators that are thin (2.5 cm) and highly extendable (up to 20cm) in both horizontal and vertical directions.

[ Ryo Suzuki ]

Robot abuse!

Vision 60 legged robot managing unstructured terrain without vision or force sensors in its legs. Using only high-transparency actuators and 2kHz algorithmic stability control… 4-limbs and 12-motors with only a velocity command.

[ Ghost Robotics ]

We asked real people to bring in real products they needed picked for their application. In MINUTES, we assembled the right tool.

This is a cool idea, but for a real challenge they should try it outside a supermarket. Or a pet store.

[ Soft Robotics ]

Good water quality is important to humans and to nature. In a country with as much water as the Netherlands has, ensuring water quality is a very labour-intensive undertaking. To address this issue, researchers from TU Delft have developed a ‘pelican drone’: a drone capable of taking water samples quickly, in combination with a measuring instrument that immediately analyses the water quality. The drone was tested this week at the new Marker Wadden nature area ‘Living Lab’.

[ MAVLab ]

In an international collaboration led by scientists in Switzerland, three amputees merge with their bionic prosthetic legs as they climb over various obstacles without having to look. The amputees report using and feeling their bionic leg as part of their own body, thanks to sensory feedback from the prosthetic leg that is delivered to nerves in the leg’s stump.

[ EPFL ]

It’s a little hard to see, but this is one way of testing out asteroid imaging spacecraft without actually going into space: a fake asteroid and a 2D microgravity simulator.

[ Caltech ]

Drones can help filmmakers do the kinds of shots that would be otherwise impossible.

[ DJI ]

Two long interviews this week from Lex Fridman’s AI Podcast, and both of them are worth watching: Gary Marcus, and Peter Norvig.

[ AI Podcast ]

This week’s CMU RI Seminar comes from Tucker Hermans at the University of Utah, on “Improving Multi-fingered Robot Manipulation by Unifying Learning and Planning.”

Multi-fingered hands offer autonomous robots increased dexterity, versatility, and stability over simple two-fingered grippers. Naturally, this increased ability comes with increased complexity in planning and executing manipulation actions. As such, I propose combining model-based planning with learned components to improve over purely data-driven or purely-model based approaches to manipulation. This talk examines multi-fingered autonomous manipulation when the robot has only partial knowledge of the object of interest. I will first present results on planning multi-fingered grasps for novel objects using a learned neural network. I will then present our approach to planning in-hand manipulation tasks when dynamic properties of objects are not known. I will conclude with a discussion of our ongoing and future research to further unify these two approaches.

[ CMU RI ] Continue reading

Posted in Human Robots

#436021 AI Faces Speed Bumps and Potholes on Its ...

Implementing machine learning in the real world isn’t easy. The tools are available and the road is well-marked—but the speed bumps are many.

That was the conclusion of panelists wrapping up a day of discussions at the IEEE AI Symposium 2019, held at Cisco’s San Jose, Calif., campus last week.

The toughest problem, says Ben Irving, senior manager of Cisco’s strategy innovations group, is people.

It’s tough to find data scientist expertise, he indicated, so companies are looking into non-traditional sources of personnel, like political science. “There are some untapped areas with a lot of untapped data science expertise,” Irving says.

Lazard’s artificial intelligence manager Trevor Mottl agreed that would-be data scientists don’t need formal training or experience to break into the field. “This field is changing really rapidly,” he says. “There are new language models coming out every month, and new tools, so [anyone should] expect to not know everything. Experiment, try out new tools and techniques, read, study, spend time; there aren’t any true experts at this point because the foundational elements are shifting so rapidly.”

“It is a wonderful time to get into a field,” he reasons, noting that it doesn’t take long to catch up because there aren’t 20 years of history.”

Confusion about what different kinds of machine learning specialists do doesn’t help the personnel situation. An audience member asked panelists to explain the difference between data scientist, data analyst, and data engineer. Darrin Johnson, Nvidia global director of technical marketing for enterprise, admitted it’s hard to sort out, and any two companies could define the positions differently. “Sometimes,” he says, particularly at smaller companies, “a data scientist plays all three roles. But as companies grow, there are different groups that ingest data, clean data, and use data. At some companies, training and inference are separate. It really depends, which is a challenge when you are trying to hire someone.”

Mitigating the risks of a hot job market

The competition to hire data scientists, analysts, engineers, or whatever companies call them requires that managers make sure any work being done is structured and comprehensible at all times, the panelists cautioned.

“We need to remember that our data scientists go home every day and sometimes they don’t come back because they go home and then go to a different company,” says Lazard’s Mottl. “That’s a fact of life. If you give people choice on [how they do development], and have a successful person who gets poached by competitor, you have to either hire a team to unwrap what that person built or jettison their work and rebuild it.”

By contrast, he says, “places that have structured coding and structured commits and organized constructions of software have done very well.”

But keeping all of a company’s engineers working with the same languages and on the same development paths is not easy to do in a field that moves as fast as machine learning. Zongjie Diao, Cisco director of product management for machine learning, quipped: “I have a data scientist friend who says the speed at which he changes girlfriends is less than speed at which he changes languages.”

The data scientist/IT manager clash

Once a company finds the data engineers and scientists they need and get them started on the task of applying machine learning to that company’s operations, one of the first obstacles they face just might be the company’s IT department, the panelists suggested.

“IT is process oriented,” Mottl says. The IT team “knows how to keep data secure, to set up servers. But when you bring in a data science team, they want sandboxes, they want freedom, they want to explore and play.”

Also, Nvidia’s Johnson pointed out, “There is a language barrier.” The AI world, he says, is very different from networking or storage, and data scientists find it hard to articulate their requirements to IT.

On the ground or in the cloud?

And then there is the decision of where exactly machine learning should happen—on site, or in the cloud? At Lazard, Mottl says, the deep learning engineers do their experimentation on premises; that’s their sandbox. “But when we deploy, we deploy in the cloud,” he says.

Nvidia, Johnson says, thinks the opposite approach is better. We see the cloud as “the sandbox,” he says. “So you can run as many experiments as possible, fail fast, and learn faster.”

For Cisco’s Irving, the “where” of machine learning depends on the confidentiality of the data.

Mottl, who says rolling machine learning technology into operation can hit resistance from all across the company, had one last word of caution for those aiming to implement AI:

Data scientists are building things that might change the ways other people in the organization work, like sales and even knowledge workers. [You need to] think about the internal stakeholders and prepare them, because the last thing you want to do is to create a valuable new thing that nobody likes and people take potshots against.

The AI Symposium was organized by the Silicon Valley chapters of the IEEE Young Professionals, the IEEE Consultants’ Network, and IEEE Women in Engineering and supported by Cisco. Continue reading

Posted in Human Robots

#435822 The Internet Is Coming to the Rest of ...

People surf it. Spiders crawl it. Gophers navigate it.

Now, a leading group of cognitive biologists and computer scientists want to make the tools of the Internet accessible to the rest of the animal kingdom.

Dubbed the Interspecies Internet, the project aims to provide intelligent animals such as elephants, dolphins, magpies, and great apes with a means to communicate among each other and with people online.

And through artificial intelligence, virtual reality, and other digital technologies, researchers hope to crack the code of all the chirps, yips, growls, and whistles that underpin animal communication.

Oh, and musician Peter Gabriel is involved.

“We can use data analysis and technology tools to give non-humans a lot more choice and control,” the former Genesis frontman, dressed in his signature Nehru-style collar shirt and loose, open waistcoat, told IEEE Spectrum at the inaugural Interspecies Internet Workshop, held Monday in Cambridge, Mass. “This will be integral to changing our relationship with the natural world.”

The workshop was a long time in the making.

Eighteen years ago, Gabriel visited a primate research center in Atlanta, Georgia, where he jammed with two bonobos, a male named Kanzi and his half-sister Panbanisha. It was the first time either bonobo had sat at a piano before, and both displayed an exquisite sense of musical timing and melody.

Gabriel seemed to be speaking to the great apes through his synthesizer. It was a shock to the man who once sang “Shock the Monkey.”

“It blew me away,” he says.

Add in the bonobos’ ability to communicate by pointing to abstract symbols, Gabriel notes, and “you’d have to be deaf, dumb, and very blind not to notice language being used.”

Gabriel eventually teamed up with Internet protocol co-inventor Vint Cerf, cognitive psychologist Diana Reiss, and IoT pioneer Neil Gershenfeld to propose building an Interspecies Internet. Presented in a 2013 TED Talk as an “idea in progress,” the concept proved to be ahead of the technology.

“It wasn’t ready,” says Gershenfeld, director of MIT’s Center for Bits and Atoms. “It needed to incubate.”

So, for the past six years, the architects of the Dolittlesque initiative embarked on two small pilot projects, one for dolphins and one for chimpanzees.

At her Hunter College lab in New York City, Reiss developed what she calls the D-Pad—a touchpad for dolphins.

Reiss had been trying for years to create an underwater touchscreen with which to probe the cognition and communication skills of bottlenose dolphins. But “it was a nightmare coming up with something that was dolphin-safe and would work,” she says.

Her first attempt emitted too much heat. A Wii-like system of gesture recognition proved too difficult to install in the dolphin tanks.

Eventually, she joined forces with Rockefeller University biophysicist Marcelo Magnasco and invented an optical detection system in which images and infrared sensors are projected through an underwater viewing window onto a glass panel, allowing the dolphins to play specially designed apps, including one dubbed Whack-a-Fish.

Meanwhile, in the United Kingdom, Gabriel worked with Alison Cronin, director of the ape rescue center Monkey World, to test the feasibility of using FaceTime with chimpanzees.

The chimps engaged with the technology, Cronin reported at this week’s workshop. However, our hominid cousins proved as adept at videotelephonic discourse as my three-year-old son is at video chatting with his grandparents—which is to say, there was a lot of pass-the-banana-through-the-screen and other silly games, and not much meaningful conversation.

“We can use data analysis and technology tools to give non-humans a lot more choice and control.”
—Peter Gabriel

The buggy, rudimentary attempt at interspecies online communication—what Cronin calls her “Max Headroom experiment”—shows that building the Interspecies Internet will not be as simple as giving out Skype-enabled tablets to smart animals.

“There are all sorts of problems with creating a human-centered experience for another animal,” says Gabriel Miller, director of research and development at the San Diego Zoo.

Miller has been working on animal-focused sensory tools such as an “Elephone” (for elephants) and a “Joybranch” (for birds), but it’s not easy to design efficient interactive systems for other creatures—and for the Interspecies Internet to be successful, Miller points out, “that will be super-foundational.”

Researchers are making progress on natural language processing of animal tongues. Through a non-profit organization called the Earth Species Project, former Firefox designer Aza Raskin and early Twitter engineer Britt Selvitelle are applying deep learning algorithms developed for unsupervised machine translation of human languages to fashion a Rosetta Stone–like tool capable of interpreting the vocalizations of whales, primates, and other animals.

Inspired by the scientists who first documented the complex sonic arrangements of humpback whales in the 1960s—a discovery that ushered in the modern marine conservation movement—Selvitelle hopes that an AI-powered animal translator can have a similar effect on environmentalism today.

“A lot of shifts happen when someone who doesn’t have a voice gains a voice,” he says.

A challenge with this sort of AI software remains verification and validation. Normally, machine-learning algorithms are benchmarked against a human expert, but who is to say if a cybernetic translation of a sperm whale’s clicks is accurate or not?

One could back-translate an English expression into sperm whale-ese and then into English again. But with the great apes, there might be a better option.

According to primatologist Sue Savage-Rumbaugh, expertly trained bonobos could serve as bilingual interpreters, translating the argot of apes into the parlance of people, and vice versa.

Not just any trained ape will do, though. They have to grow up in a mixed Pan/Homo environment, as Kanzi and Panbanisha were.

“If I can have a chat with a cow, maybe I can have more compassion for it.”
—Jeremy Coller

Those bonobos were raised effectively from birth both by Savage-Rumbaugh, who taught the animals to understand spoken English and to communicate via hundreds of different pictographic “lexigrams,” and a bonobo mother named Matata that had lived for six years in the Congolese rainforests before her capture.

Unlike all other research primates—which are brought into captivity as infants, reared by human caretakers, and have limited exposure to their natural cultures or languages—those apes thus grew up fluent in both bonobo and human.

Panbanisha died in 2012, but Kanzi, aged 38, is still going strong, living at an ape sanctuary in Des Moines, Iowa. Researchers continue to study his cognitive abilities—Francine Dolins, a primatologist at the University of Michigan-Dearborn, is running one study in which Kanzi and other apes hunt rabbits and forage for fruit through avatars on a touchscreen. Kanzi could, in theory, be recruited to check the accuracy of any Google Translate–like app for bonobo hoots, barks, grunts, and cries.

Alternatively, Kanzi could simply provide Internet-based interpreting services for our two species. He’s already proficient at video chatting with humans, notes Emily Walco, a PhD student at Harvard University who has personally Skyped with Kanzi. “He was super into it,” Walco says.

And if wild bonobos in Central Africa can be coaxed to gather around a computer screen, Savage-Rumbaugh is confident Kanzi could communicate with them that way. “It can all be put together,” she says. “We can have an Interspecies Internet.”

“Both the technology and the knowledge had to advance,” Savage-Rumbaugh notes. However, now, “the techniques that we learned could really be extended to a cow or a pig.”

That’s music to the ears of Jeremy Coller, a private equity specialist whose foundation partially funded the Interspecies Internet Workshop. Coller is passionate about animal welfare and has devoted much of his philanthropic efforts toward the goal of ending factory farming.

At the workshop, his foundation announced the creation of the Coller Doolittle Prize, a US $100,000 award to help fund further research related to the Interspecies Internet. (A working group also formed to synthesize plans for the emerging field, to facilitate future event planning, and to guide testing of shared technology platforms.)

Why would a multi-millionaire with no background in digital communication systems or cognitive psychology research want to back the initiative? For Coller, the motivation boils to interspecies empathy.

“If I can have a chat with a cow,” he says, “maybe I can have more compassion for it.”

An abridged version of this post appears in the September 2019 print issue as “Elephants, Dolphins, and Chimps Need the Internet, Too.” Continue reading

Posted in Human Robots

#435738 Boing Goes the Trampoline Robot

There are a handful of quadrupedal robots out there that are highly dynamic, with the ability to run and jump, but those robots tend to be rather expensive and complicated, requiring powerful actuators and legs with elasticity. Boxing Wang, a Ph.D. student in the College of Control Science and Engineering at Zhejiang University in China, contacted us to share a project he’s been working to investigate quadruped jumping with simple, affordable hardware.

“The motivation for this project is quite simple,” Boxing says. “I wanted to study quadrupedal jumping control, but I didn’t have custom-made powerful actuators, and I didn’t want to have to design elastic legs. So I decided to use a trampoline to make a normal servo-driven quadruped robot to jump.”

Boxing and his colleagues had wanted to study quadrupedal running and jumping, so they built this robot with the most powerful servos they had access to: Kondo KRS6003RHV actuators, which have a maximum torque of 6 Nm. After some simple testing, it became clear that the servos were simply not fast or powerful enough to get the robot to jump, and that an elastic element was necessary to store energy to help the robot get off the ground.

“Normally, people would choose elastic legs,” says Boxing. “But nobody in my lab knew for sure how to design them. If we tried making elastic legs and we failed to make the robot jump, we couldn’t be sure whether the problem was the legs or the control algorithms. For hardware, we decided that it’s better to start with something reliable, something that definitely won’t be the source of the problem.”

As it turns out, all you need is a trampoline, an inertial measurement unit (IMU), and little tactile switches on the end of each foot to detect touch-down and lift-off events, and you can do some useful jumping research without a jumping robot. And the trampoline has other benefits as well—because it’s stiffer at the edges than at the center, for example, the robot will tend to center itself on the trampoline, and you get some warning before things go wrong.

“I can’t say that it’s a breakthrough to make a quadruped robot jump on a trampoline,” Boxing tells us. “But I believe this is useful for prototype testing, especially for people who are interested in quadrupedal jumping control but without a suitable robot at hand.”

To learn more about the project, we emailed him some additional questions.

IEEE Spectrum: Where did this idea come from?

Boxing Wang: The idea of the trampoline came while we were drinking milk tea. I don’t know why it came up, maybe someone saw a trampoline in a gym recently. And I don’t remember who proposed it exactly. It was just like someone said it unintentionally. But I realized that a trampoline would be a perfect choice. It’s reliable, easy to buy, and should have a similar dynamic model with the one of jumping with springy legs (we have briefly analyzed this in a paper). So I decided to try the trampoline.

How much do you think you can learn using a quadruped on a trampoline, instead of using a jumping quadruped?

Generally speaking, no contact surfaces are strictly rigid. They all have elasticity. So there are no essential differences between jumping on a trampoline and jumping on a rigid surface. However, using a quadruped on a trampoline can give you more information on how to make use of elasticity to make jumping easier and more efficient. You can use quadruped robots with springy legs to address the same problem, but that usually requires much more time on hardware design.

We prefer to treat the trampoline experiment as a kind of early test for further real jumping quadruped design. Unless you’re interested in designing an acrobatic robot on a trampoline, a real jumping quadruped is probably a more useful application, and that is our ultimate goal. The point of the trampoline tests is to develop the control algorithms first, and to examine the stability of the general hardware structure. Due to the similarity between jumping on a trampoline with rigid legs and jumping on hard surfaces with springy legs, the control algorithms you develop could be transferred to hard-surface jumping robots.

“Unless you’re interested in designing an acrobatic robot on a trampoline, a real jumping quadruped is probably a more useful application, and that is our ultimate goal. The point of the trampoline tests is to develop the control algorithms first, and to examine the stability of the general hardware structure”

Do you think that this idea can be beneficial for other kinds of robotics research?

Yes. For jumping quadrupeds with springy legs, the control algorithms could be first designed through trampoline tests using simple rigid legs. And the hardware design for elastic legs could be accelerated with the help of the control algorithms you design. In addition, we believe our work could be a good example of using a position-control robot to realize dynamic motions such as jumping, or even running.

Unlike other dynamic robots, every active joint in our robot is controlled through commercial position-control servos and not custom torque control motors. Most people don’t think that a position-control robot could perform highly dynamic motions such as jumping, because position-control motors usually mean high a gear ratio and slow response. However, our work indicates that, with the help of elasticity, stable jumping could be realized through position-control servos. So for those who already have a position-control robot at hand, they could explore the potential of their robot through trampoline tests.

Why is teaching a robot to jump important?

There are many scenarios where a jumping robot is needed. For example, a real jumping quadruped could be used to design a running quadruped. Both experience moments when all four legs are in the air, and it is easier to start from jumping and then move to running. Specifically, hopping or pronking can easily transform to bounding if the pitch angle is not strictly controlled. A bounding quadruped is similar to a running rabbit, so for now it can already be called a running quadruped.

To the best of our knowledge, a practical use of jumping quadrupeds could be planet exploration, just like what SpaceBok was designed for. In a low-gravity environment, jumping is more efficient than walking, and it’s easier to jump over obstacles. But if I had a jumping quadruped on Earth, I would teach it to catch a ball that I throw at it by jumping. It would be fantastic!

That would be fantastic.

Since the whole point of the trampoline was to get jumping software up and running with a minimum of hardware, the next step is to add some springy legs to the robot so that the control system the researchers developed can be tested on hard surfaces. They have a journal paper currently under revision, and Boxing Wang is joined as first author by his adviser Chunlin Zhou, undergrads Ziheng Duan and Qichao Zhu, and researchers Jun Wu and Rong Xiong. Continue reading

Posted in Human Robots

#435731 Video Friday: NASA Is Sending This ...

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!):

MARSS 2019 – July 1-5, 2019 – Helsinki, Finland
ICRES 2019 – July 29-30, 2019 – London, UK
DARPA SubT Tunnel Circuit – August 15-22, 2019 – Pittsburgh, PA, USA
Let us know if you have suggestions for next week, and enjoy today’s videos.

The big news today is that NASA is sending a robot to Saturn’s moon Titan. A flying robot. The Dragonfly mission will launch in 2026 and arrive in 2034, but you knew that already, because last January, we posted a detailed article about the concept from the Applied Physics Lab at Johns Hopkins University. And now it’s not a concept anymore, yay!

Again, read all the details plus an interview in 2018 article.

[ NASA ]

A robotic gripping arm that uses engineered bacteria to “taste” for a specific chemical has been developed by engineers at the University of California, Davis, and Carnegie Mellon University. The gripper is a proof-of-concept for biologically-based soft robotics.

The new device uses a biosensing module based on E. coli bacteria engineered to respond to the chemical IPTG by producing a fluorescent protein. The bacterial cells reside in wells with a flexible, porous membrane that allows chemicals to enter but keeps the cells inside. This biosensing module is built into the surface of a flexible gripper on a robotic arm, so the gripper can “taste” the environment through its fingers.

When IPTG crosses the membrane into the chamber, the cells fluoresce and electronic circuits inside the module detect the light. The electrical signal travels to the gripper’s control unit, which can decide whether to pick something up or release it.

[ UC Davis ]

The Toyota Research Institute (TRI) is taking on the hard problems in manipulation research toward making human-assist robots reliable and robust. Dr. Russ Tedrake, TRI Vice President of Robotics Research, explains how we are exploring the challenges and addressing the reliability gap by using a robot loading dishes in a dishwasher as an example task.

[ TRI ]

The Tactile Telerobot is the world’s first haptic telerobotic system that transmits realistic touch feedback to an operator located anywhere in the world. It is the product of joint collaboration between Shadow Robot Company, HaptX, and SynTouch. All Nippon Airways funded the project’s initial research and development.

What’s really unique about this is the HaptX tactile feedback system, which is something we’ve been following for several years now. It’s one of the most magical tech experiences I’ve ever had, and you can read about it here and here.

[ HaptX ]

Thanks Andrew!

I love how snake robots can emulate some of the fanciest moves of real snakes, and then also do bonkers things that real snakes never do.

[ Matsuno Lab ]

Here are a couple interesting videos from the Human-Robot Interaction Lab at Tufts.

A robot is instructed to perform an action and cannot do it due to lack of sensors. But when another robot is placed nearby, it can execute the instruction by tacitly tapping into the other robot’s mind and using that robot’s sensors for its own actions. Yes, it’s automatic, and yes, it’s the BORG!

Two Nao robots are instructed to perform a dance and are able to do it right after instruction. Moreover, they can switch roles immediately, and even a third different PR2 robot can perform the dance right away, demonstrating the ability of our DIARC architecture to learn quickly and share the knowledge with any type of robot running the architecture.

Compared to Nao, PR2 just sounds… depressed.

[ HRI Lab ]

This work explores the problem of robot tool construction – creating tools from parts available in the environment. We advance the state-of-the-art in robotic tool construction by introducing an approach that enables the robot to construct a wider range of tools with greater computational efficiency. Specifically, given an action that the robot wishes to accomplish and a set of building parts available to the robot, our approach reasons about the shape of the parts and potential ways of attaching them, generating a ranking of part combinations that the robot then uses to construct and test the target tool. We validate our approach on the construction of five tools using a physical 7-DOF robot arm.

[ RAIL Lab ] via [ RSS ]

We like Magazino’s approach to warehouse picking- constrain the problem to something you can reliably solve, like shoeboxes.

Magazino has announced a new pricing model for their robots. You pay 55k euros for the robot itself, and then after that, all you pay to keep the robot working is 6 cents per pick, so the robot is only costing you money for the work that it actually does.

[ Magazino ]

Thanks Florin!

Human-Robot Collaborations are happening across factories worldwide, yet very few are using it for smaller businesses, due to high costs or the difficulty of customization. Elephant Robotics, a new player from Shenzhen, the Silicon Valley of Asia, has set its sight on helping smaller businesses gain access to smart robotics. They created a Catbot (a collaborative robotic arm) that will offer high efficiency and flexibility to various industries.

The Catbot is set to help from education projects, photography, massaging, to being a personal barista or co-playing a table game. The customizations are endless. To increase the flexibility of usage, the Catbot is extremely easy to program from a high precision task up to covering hefty ground projects.

[ Elephant Robotics ]

Thanks Johnson!

Dronistics, an EPFL spin-off, has been testing out their enclosed delivery drone in the Dominican Republic through a partnership with WeRobotics.

[ WeRobotics ]

QTrobot is an expressive humanoid robot designed to help children with autism spectrum disorder and children with special educational needs in learning new skills. QTrobot uses simple and exaggerated facial expressions combined by interactive games and stories, to help children improve their emotional skills. QTrobot helps children to learn about and better understand the emotions and teach them strategies to handle their emotions more effectively.

[ LuxAI ]

Here’s a typical day in the life of a Tertill solar-powered autonomous weed-destroying robot.

$300, now shipping from Franklin Robotics.

[ Tertill ]

PAL Robotics is excited to announce a new TIAGo with two arms, TIAGo++! After carefully listening to the robotics community needs, we used TIAGo’s modularity to integrate two 7-DoF arms to our mobile manipulator. TIAGo++ can help you swiftly accomplish your research goals, opening endless possibilities in mobile manipulation.

[ PAL Robotics ]

Thanks Jack!

You’ve definitely already met the Cobalt security robot, but Toyota AI Ventures just threw a pile of money at them and would therefore like you to experience this re-introduction:

[ Cobalt Robotics ] via [ Toyota AI ]

ROSIE is a mobile manipulator kit from HEBI Robotics. And if you don’t like ROSIE, the modular nature of HEBI’s hardware means that you can take her apart and make something more interesting.

[ HEBI Robotics ]

Learn about Kawasaki Robotics’ second addition to their line of duAro dual-arm collaborative robots, duAro2. This model offers an extended vertical reach (550 mm) and an increased payload capacity (3 kg/arm).

[ Kawasaki Robotics ]

Drone Delivery Canada has partnered with Peel Region Paramedics to pilot its proprietary drone delivery platform to enable rapid first responder technology via drone with the goal to reduce response time and potentially save lives.

[ Drone Delivery Canada ]

In this week’s episode of Robots in Depth, Per speaks with Harri Ketamo, from Headai.

Harri Ketamo talks about AI and how he aims to mimic human decision making with algorithms. Harri has done a lot of AI for computer games to create opponents that are entertaining to play against. It is easy to develop a very bad or a very good opponent, but designing an opponent that behaves like a human, is entertaining to play against and that you can beat is quite hard. He talks about how AI in computer games is a very important story telling tool and an important part of making a game entertaining to play.

This work led him into other parts of the AI field. Harri thinks that we sometimes have a problem separating what is real from what is the type of story telling he knows from gaming AI. He calls for critical analysis of AI and says that data has to be used to verify AI decisions and results.

[ Robots in Depth ]

Thanks Per! Continue reading

Posted in Human Robots