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#436178 Within 10 Years, We’ll Travel by ...

What’s faster than autonomous vehicles and flying cars?

Try Hyperloop, rocket travel, and robotic avatars. Hyperloop is currently working towards 670 mph (1080 kph) passenger pods, capable of zipping us from Los Angeles to downtown Las Vegas in under 30 minutes. Rocket Travel (think SpaceX’s Starship) promises to deliver you almost anywhere on the planet in under an hour. Think New York to Shanghai in 39 minutes.

But wait, it gets even better…

As 5G connectivity, hyper-realistic virtual reality, and next-gen robotics continue their exponential progress, the emergence of “robotic avatars” will all but nullify the concept of distance, replacing human travel with immediate remote telepresence.

Let’s dive in.

Hyperloop One: LA to SF in 35 Minutes
Did you know that Hyperloop was the brainchild of Elon Musk? Just one in a series of transportation innovations from a man determined to leave his mark on the industry.

In 2013, in an attempt to shorten the long commute between Los Angeles and San Francisco, the California state legislature proposed a $68 billion budget allocation for what appeared to be the slowest and most expensive bullet train in history.

Musk was outraged. The cost was too high, the train too sluggish. Teaming up with a group of engineers from Tesla and SpaceX, he published a 58-page concept paper for “The Hyperloop,” a high-speed transportation network that used magnetic levitation to propel passenger pods down vacuum tubes at speeds of up to 670 mph. If successful, it would zip you across California in 35 minutes—just enough time to watch your favorite sitcom.

In January 2013, venture capitalist Shervin Pishevar, with Musk’s blessing, started Hyperloop One with myself, Jim Messina (former White House Deputy Chief of Staff for President Obama), and tech entrepreneurs Joe Lonsdale and David Sacks as founding board members. A couple of years after that, the Virgin Group invested in this idea, Richard Branson was elected chairman, and Virgin Hyperloop One was born.

“The Hyperloop exists,” says Josh Giegel, co-founder and chief technology officer of Hyperloop One, “because of the rapid acceleration of power electronics, computational modeling, material sciences, and 3D printing.”

Thanks to these convergences, there are now ten major Hyperloop One projects—in various stages of development—spread across the globe. Chicago to DC in 35 minutes. Pune to Mumbai in 25 minutes. According to Giegel, “Hyperloop is targeting certification in 2023. By 2025, the company plans to have multiple projects under construction and running initial passenger testing.”

So think about this timetable: Autonomous car rollouts by 2020. Hyperloop certification and aerial ridesharing by 2023. By 2025—going on vacation might have a totally different meaning. Going to work most definitely will.

But what’s faster than Hyperloop?

Rocket Travel
As if autonomous vehicles, flying cars, and Hyperloop weren’t enough, in September of 2017, speaking at the International Astronautical Congress in Adelaide, Australia, Musk promised that for the price of an economy airline ticket, his rockets will fly you “anywhere on Earth in under an hour.”

Musk wants to use SpaceX’s megarocket, Starship, which was designed to take humans to Mars, for terrestrial passenger delivery. The Starship travels at 17,500 mph. It’s an order of magnitude faster than the supersonic jet Concorde.

Think about what this actually means: New York to Shanghai in 39 minutes. London to Dubai in 29 minutes. Hong Kong to Singapore in 22 minutes.

So how real is the Starship?

“We could probably demonstrate this [technology] in three years,” Musk explained, “but it’s going to take a while to get the safety right. It’s a high bar. Aviation is incredibly safe. You’re safer on an airplane than you are at home.”

That demonstration is proceeding as planned. In September 2017, Musk announced his intentions to retire his current rocket fleet, both the Falcon 9 and Falcon Heavy, and replace them with the Starships in the 2020s.

Less than a year later, LA mayor Eric Garcetti tweeted that SpaceX was planning to break ground on an 18-acre rocket production facility near the port of Los Angeles. And April of this year marked an even bigger milestone: the very first test flights of the rocket.

Thus, sometime in the next decade or so, “off to Europe for lunch” may become a standard part of our lexicon.

Avatars
Wait, wait, there’s one more thing.

While the technologies we’ve discussed will decimate the traditional transportation industry, there’s something on the horizon that will disrupt travel itself. What if, to get from A to B, you didn’t have to move your body? What if you could quote Captain Kirk and just say “Beam me up, Scotty”?

Well, shy of the Star Trek transporter, there’s the world of avatars.

An avatar is a second self, typically in one of two forms. The digital version has been around for a couple of decades. It emerged from the video game industry and was popularized by virtual world sites like Second Life and books-turned-blockbusters like Ready Player One.

A VR headset teleports your eyes and ears to another location, while a set of haptic sensors shifts your sense of touch. Suddenly, you’re inside an avatar inside a virtual world. As you move in the real world, your avatar moves in the virtual.

Use this technology to give a lecture and you can do it from the comfort of your living room, skipping the trip to the airport, the cross-country flight, and the ride to the conference center.

Robots are the second form of avatars. Imagine a humanoid robot that you can occupy at will. Maybe, in a city far from home, you’ve rented the bot by the minute—via a different kind of ridesharing company—or maybe you have spare robot avatars located around the country.

Either way, put on VR goggles and a haptic suit, and you can teleport your senses into that robot. This allows you to walk around, shake hands, and take action—all without leaving your home.

And like the rest of the tech we’ve been talking about, even this future isn’t far away.

In 2018, entrepreneur Dr. Harry Kloor recommended to All Nippon Airways (ANA), Japan’s largest airline, the design of an Avatar XPRIZE. ANA then funded this vision to the tune of $10 million to speed the development of robotic avatars. Why? Because ANA knows this is one of the technologies likely to disrupt their own airline industry, and they want to be ready.

ANA recently announced its “newme” robot that humans can use to virtually explore new places. The colorful robots have Roomba-like wheeled bases and cameras mounted around eye-level, which capture surroundings viewable through VR headsets.

If the robot was stationed in your parents’ home, you could cruise around the rooms and chat with your family at any time of day. After revealing the technology at Tokyo’s Combined Exhibition of Advanced Technologies in October, ANA plans to deploy 1,000 newme robots by 2020.

With virtual avatars like newme, geography, distance, and cost will no longer limit our travel choices. From attractions like the Eiffel Tower or the pyramids of Egypt to unreachable destinations like the moon or deep sea, we will be able to transcend our own physical limits, explore the world and outer space, and access nearly any experience imaginable.

Final Thoughts
Individual car ownership has enjoyed over a century of ascendancy and dominance.

The first real threat it faced—today’s ride-sharing model—only showed up in the last decade. But that ridesharing model won’t even get ten years to dominate. Already, it’s on the brink of autonomous car displacement, which is on the brink of flying car disruption, which is on the brink of Hyperloop and rockets-to-anywhere decimation. Plus, avatars.

The most important part: All of this change will happen over the next ten years. Welcome to a future of human presence where the only constant is rapid change.

Note: This article—an excerpt from my next book The Future Is Faster Than You Think, co-authored with Steven Kotler, to be released January 28th, 2020—originally appeared on my tech blog at diamandis.com. Read the original article here.

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Image Credit: Virgin Hyperloop One Continue reading

Posted in Human Robots

#436176 We’re Making Progress in Explainable ...

Machine learning algorithms are starting to exceed human performance in many narrow and specific domains, such as image recognition and certain types of medical diagnoses. They’re also rapidly improving in more complex domains such as generating eerily human-like text. We increasingly rely on machine learning algorithms to make decisions on a wide range of topics, from what we collectively spend billions of hours watching to who gets the job.

But machine learning algorithms cannot explain the decisions they make.
How can we justify putting these systems in charge of decisions that affect people’s lives if we don’t understand how they’re arriving at those decisions?

This desire to get more than raw numbers from machine learning algorithms has led to a renewed focus on explainable AI: algorithms that can make a decision or take an action, and tell you the reasons behind it.

What Makes You Say That?
In some circumstances, you can see a road to explainable AI already. Take OpenAI’s GTP-2 model, or IBM’s Project Debater. Both of these generate text based on a large corpus of training data, and try to make it as relevant as possible to the prompt that’s given. If these models were also able to provide a quick run-down of the top few sources in that corpus of training data they were drawing information from, it may be easier to understand where the “argument” (or poetic essay about unicorns) was coming from.

This is similar to the approach Google is now looking at for its image classifiers. Many algorithms are more sensitive to textures and the relationship between adjacent pixels in an image, rather than recognizing objects by their outlines as humans do. This leads to strange results: some algorithms can happily identify a totally scrambled image of a polar bear, but not a polar bear silhouette.

Previous attempts to make image classifiers explainable relied on significance mapping. In this method, the algorithm would highlight the areas of the image that contributed the most statistical weight to making the decision. This is usually determined by changing groups of pixels in the image and seeing which contribute to the biggest change in the algorithm’s impression of what the image is. For example, if the algorithm is trying to recognize a stop sign, changing the background is unlikely to be as important as changing the sign.

Google’s new approach changes the way that its algorithm recognizes objects, by examining them at several different resolutions and searching for matches to different “sub-objects” within the main object. You or I might recognize an ambulance from its flashing lights, its tires, and its logo; we might zoom in on the basketball held by an NBA player to deduce their occupation, and so on. By linking the overall categorization of an image to these “concepts,” the algorithm can explain its decision: I categorized this as a cat because of its tail and whiskers.

Even in this experiment, though, the “psychology” of the algorithm in decision-making is counter-intuitive. For example, in the basketball case, the most important factor in making the decision was actually the player’s jerseys rather than the basketball.

Can You Explain What You Don’t Understand?
While it may seem trivial, the conflict here is a fundamental one in approaches to artificial intelligence. Namely, how far can you get with mere statistical associations between huge sets of data, and how much do you need to introduce abstract concepts for real intelligence to arise?

At one end of the spectrum, Good Old-Fashioned AI or GOFAI dreamed up machines that would be entirely based on symbolic logic. The machine would be hard-coded with the concept of a dog, a flower, cars, and so forth, alongside all of the symbolic “rules” which we internalize, allowing us to distinguish between dogs, flowers, and cars. (You can imagine a similar approach to a conversational AI would teach it words and strict grammatical structures from the top down, rather than “learning” languages from statistical associations between letters and words in training data, as GPT-2 broadly does.)

Such a system would be able to explain itself, because it would deal in high-level, human-understandable concepts. The equation is closer to: “ball” + “stitches” + “white” = “baseball”, rather than a set of millions of numbers linking various pathways together. There are elements of GOFAI in Google’s new approach to explaining its image recognition: the new algorithm can recognize objects based on the sub-objects they contain. To do this, it requires at least a rudimentary understanding of what those sub-objects look like, and the rules that link objects to sub-objects, such as “cats have whiskers.”

The issue, of course, is the—maybe impossible—labor-intensive task of defining all these symbolic concepts and every conceivable rule that could possibly link them together by hand. The difficulty of creating systems like this, which could handle the “combinatorial explosion” present in reality, helped to lead to the first AI winter.

Meanwhile, neural networks rely on training themselves on vast sets of data. Without the “labeling” of supervised learning, this process might bear no relation to any concepts a human could understand (and therefore be utterly inexplicable).

Somewhere between these two, hope explainable AI enthusiasts, is a happy medium that can crunch colossal amounts of data, giving us all of the benefits that recent, neural-network AI has bestowed, while showing its working in terms that humans can understand.

Image Credit: Image by Seanbatty from Pixabay Continue reading

Posted in Human Robots

#436155 This MIT Robot Wants to Use Your ...

MIT researchers have demonstrated a new kind of teleoperation system that allows a two-legged robot to “borrow” a human operator’s physical skills to move with greater agility. The system works a bit like those haptic suits from the Spielberg movie “Ready Player One.” But while the suits in the film were used to connect humans to their VR avatars, the MIT suit connects the operator to a real robot.

The robot is called Little HERMES, and it’s currently just a pair of little legs, about a third the size of an average adult. It can step and jump in place or walk a short distance while supported by a gantry. While that in itself is not very impressive, the researchers say their approach could help bring capable disaster robots closer to reality. They explain that, despite recent advances, building fully autonomous robots with motor and decision-making skills comparable to those of humans remains a challenge. That’s where a more advanced teleoperation system could help.

The researchers, João Ramos, now an assistant professor at the University of Illinois at Urbana-Champaign, and Sangbae Kim, director of MIT’s Biomimetic Robotics Lab, describe the project in this week’s issue of Science Robotics. In the paper, they argue that existing teleoperation systems often can’t effectively match the operator’s motions to that of a robot. In addition, conventional systems provide no physical feedback to the human teleoperator about what the robot is doing. Their new approach addresses these two limitations, and to see how it would work in practice, they built Little HERMES.

Image: Science Robotics

The main components of MIT’s bipedal robot Little HERMES: (A) Custom actuators designed to withstand impact and capable of producing high torque. (B) Lightweight limbs with low inertia and fast leg swing. (C) Impact-robust and lightweight foot sensors with three-axis contact force sensor. (D) Ruggedized IMU to estimates the robot’s torso posture, angular rate, and linear acceleration. (E) Real-time computer sbRIO 9606 from National Instruments for robot control. (F) Two three-cell lithium-polymer batteries in series. (G) Rigid and lightweight frame to minimize the robot mass.

Early this year, the MIT researchers wrote an in-depth article for IEEE Spectrum about the project, which includes Little HERMES and also its big brother, HERMES (for Highly Efficient Robotic Mechanisms and Electromechanical System). In that article, they describe the two main components of the system:

[…] We are building a telerobotic system that has two parts: a humanoid capable of nimble, dynamic behaviors, and a new kind of two-way human-machine interface that sends your motions to the robot and the robot’s motions to you. So if the robot steps on debris and starts to lose its balance, the operator feels the same instability and instinctively reacts to avoid falling. We then capture that physical response and send it back to the robot, which helps it avoid falling, too. Through this human-robot link, the robot can harness the operator’s innate motor skills and split-second reflexes to keep its footing.

You could say we’re putting a human brain inside the machine.

Image: Science Robotics

The human-machine interface built by the MIT researchers for controlling Little HERMES is different from conventional ones in that it relies on the operator’s reflexes to improve the robot’s stability. The researchers call it the balance-feedback interface, or BFI. The main modules of the BFI include: (A) Custom interface attachments for torso and feet designed to capture human motion data at high speed (1 kHz). (B) Two underactuated modules to track the position and orientation of the torso and apply forces to the operator. (C) Each actuation module has three DoFs, one of which is a push/pull rod actuated by a DC brushless motor. (D) A series of linkages with passive joints connected to the operator’s feet and track their spatial translation. (E) Real-time controller cRIO 9082 from National Instruments to close the BFI control loop. (F) Force plate to estimated the operator’s center of pressure position and measure the shear and normal components of the operator’s net contact force.

Here’s more footage of the experiments, showing Little HERMES stepping and jumping in place, walking a few steps forward and backward, and balancing. Watch until the end to see a compilation of unsuccessful stepping experiments. Poor Little HERMES!

In the new Science Robotics paper, the MIT researchers explain how they solved one of the key challenges in making their teleoperation system effective:

The challenge of this strategy lies in properly mapping human body motion to the machine while simultaneously informing the operator how closely the robot is reproducing the movement. Therefore, we propose a solution for this bilateral feedback policy to control a bipedal robot to take steps, jump, and walk in synchrony with a human operator. Such dynamic synchronization was achieved by (i) scaling the core components of human locomotion data to robot proportions in real time and (ii) applying feedback forces to the operator that are proportional to the relative velocity between human and robot.

Little HERMES is now taking its first steps, quite literally, but the researchers say they hope to use robotic legs with similar design as part of a more advanced humanoid. One possibility they’ve envisioned is a fast-moving quadruped robot that could run through various kinds of terrain and then transform into a bipedal robot that would use its hands to perform dexterous manipulations. This could involve merging some of the robots the MIT researchers have built in their lab, possibly creating hybrids between Cheetah and HERMES, or Mini Cheetah and Little HERMES. We can’t wait to see what the resulting robots will look like.

[ Science Robotics ] Continue reading

Posted in Human Robots

#436149 Blue Frog Robotics Answers (Some of) Our ...

In September of 2015, Buddy the social home robot closed its Indiegogo crowdfunding campaign more than 600 percent over its funding goal. A thousand people pledged for a robot originally scheduled to be delivered in December of 2016. But nearly three years later, the future of Buddy is still unclear. Last May, Blue Frog Robotics asked for forgiveness from its backers and announced the launch of an “equity crowdfunding campaign” to try to raise the additional funding necessary to deliver the robot in April of 2020.

By the time the crowdfunding campaign launched in August, the delivery date had slipped again, to September 2020, even as Blue Frog attempted to draw investors by estimating that sales of Buddy would “increase from 2000 robots in 2020 to 20,000 in 2023.” Blue Frog’s most recent communication with backers, in September, mentions a new CTO and a North American office, but does little to reassure backers of Buddy that they’ll ever be receiving their robot.

Backers of the robot are understandably concerned about the future of Buddy, so we sent a series of questions to the founder and CEO of Blue Frog Robotics, Rodolphe Hasselvander.

We’ve edited this interview slightly for clarity, but we should also note that Hasselvander was unable to provide answers to every question. In particular, we asked for some basic information about Blue Frog’s near-term financial plans, on which the entire future of Buddy seems to depend. We’ve left those questions in the interview anyway, along with Hasselvander’s response.

1. At this point, how much additional funding is necessary to deliver Buddy to backers?
2. Assuming funding is successful, when can backers expect to receive Buddy?
3. What happens if the fundraising goal is not met?
4. You estimate that sales of Buddy will increase 10x over three years. What is this estimate based on?

Rodolphe Hasselvander: Regarding the questions 1-4, unfortunately, as we are fundraising in a Regulation D, we do not comment on prospect, customer data, sales forecasts, or figures. Please refer to our press release here to have information about the fundraising.

5. Do you feel that you are currently being transparent enough about this process to satisfy backers?
6. Buddy’s launch date has moved from April 2020 to September 2020 over the last four months. Why should backers remain confident about Buddy’s schedule?

Since the last newsletter, we haven’t changed our communication, the backers will be the first to receive their Buddy, and we plan an official launch in September 2020.

7. What is the goal of My Buddy World?

At Blue Frog, we think that matching a great product with a big market can only happen through continual experimentation, iteration and incorporation of customer feedback. That’s why we created the forum My Buddy World. It has been designed for our Buddy Community to join us, discuss the world’s first emotional robot, and create with us. The objective is to deepen our conversation with Buddy’s fans and users, stay agile in testing our hypothesis and validate our product-market fit. We trust the value of collaboration. Behind Buddy, there is a team of roboticists, engineers, and programmers that are eager to know more about our consumers’ needs and are excited to work with them to create the perfect human/robot experience.

8. How is the current version of Buddy different from the 2015 version that backers pledged for during the successful crowdfunding campaign, in both hardware and software?

We have completely revised some parts of Buddy as well as replaced and/or added more accurate and reliable components to ensure we fully satisfy our customers’ requirements for a mature and high-quality robot from day one. We sourced more innovative components to make sure that Buddy has the most up-to-date technologies such as adding four microphones, a high def thermal matrix, a 3D camera, an 8-megapixel RGB camera, time-of-flight sensors, and touch sensors.
If you want more info, we just posted an article about what is Buddy here.

9. Will the version of Buddy that ships to backers in 2020 do everything that that was shown in the original crowdfunding video?

Concerning the capabilities of Buddy regarding the video published on YouTube, I confirm that Buddy will be able to do everything you can see, like patrol autonomously and secure your home, telepresence, mathematics applications, interactive stories for children, IoT/smart home management, face recognition, alarm clock, reminder, message/photo sharing, music, hands free call, people following, games like hide and seek (and more). In addition, everyone will be able to create their own apps thanks to the “BuddyLab” application.

10. What makes you confident that Buddy will be successful when Jibo, Kuri, and other social robots have not?

Consumer robotics is a new market. Some people think it is a tough one. But we, at Blue Frog Robotics, believe it is a path of learning, understanding, and finding new ways to serve consumers. Here are the five key factors that will make Buddy successful.

1) A market-fit robot

Blue Frog Robotics is a consumer-centric company. We know that a successful business model and a compelling fit to market Buddy must come up from solving consumers’ frustrations and problems in a way that’s new and exciting. We started from there.

By leveraged existing research and syndicated consumer data sets to understand our customers’ needs and aspirations, we get that creating a robot is not about the best tech innovation and features, but always about how well technology becomes a service to one’s basic human needs and assets: convenience, connection, security, fun, self-improvement, and time. To answer to these consumers’ needs and wants, we designed an all-in-one robot with four vital capabilities: intelligence, emotionality, mobility, and customization.

With his multi-purpose brain, he addresses a broad range of needs in modern-day life, from securing homes to carrying out his owners’ daily activities, from helping people with disabilities to educating children, from entertaining to just becoming a robot friend.

Buddy is a disruptive innovative robot that is about to transform the way we live, learn, utilize information, play, and even care about our health.
2) Endless possibilities

One of the major advantages of Buddy is his adaptability. Beyond to be adorable, playful, talkative, and to accompany anyone in their daily life at home whether you are comfortable with technology or not, he offers via his platform applications to engage his owners in a wide range of activities. From fitness to cooking, from health monitoring to education, from games to meditation, the combination of intelligence, sensors, mobility, multi-touch panel opens endless possibilities for consumers and organizations to adapt their Buddy to their own needs.
3) An affordable price

Buddy will be the first robot combining smart, social, and mobile capabilities and a developed platform with a personality to enter the U.S. market at affordable price.

Our competitors are social or assistant robots but rarely both. Competitors differentiate themselves by features: mobile, non-mobile; by shapes: humanoid or not; by skills: social versus smart; targeting a specific domain like entertainment, retail assistant, eldercare, or education for children; and by price. Regarding our six competitors: Moorebot, Elli-Q, and Olly are not mobile; Lynx and Nao are in toy category; Pepper is above $10k targeting B2B market; and finally, Temi can’t be considered an emotional robot.
Buddy remains highly differentiated as an all-in-one, best of his class experience, covering the needs for social interactions and assistance of his owners at each stage of their life at an affordable price.

The price range of Buddy will be between US $1700 and $2000.

4) A winning business model

Buddy’s great business model combines hardware, software, and services, and provides game-changing convenience for consumers, organizations, and developers.

Buddy offers a multi-sided value proposition focused on three vertical markets: direct consumers, corporations (healthcare, education, hospitality), and developers. The model creates engagement and sustained usage and produces stable and diverse cash flow.
5) A Passion for people and technology

From day one, we have always believed in the power of our dream: To bring the services and the fun of an emotional robot in every house, every hospital, in every care house. Each day, we refuse to think that we are stuck or limited; we work hard to make Buddy a reality that will help people all over the world and make them smile.

While we certainly appreciate Hasselvander’s consistent optimism and obvious enthusiasm, we’re obligated to point out that some of our most important questions were not directly answered. We haven’t learned anything that makes us all that much more confident that Blue Frog will be able to successfully deliver Buddy this time. Hasselvander also didn’t address our specific question about whether he feels like Blue Frog’s communication strategy with backers has been adequate, which is particularly relevant considering that over the four months between the last two newsletters, Buddy’s launch date slipped by six months.

At this point, all we can do is hope that the strategy Blue Frog has chosen will be successful. We’ll let you know if as soon as we learn more.

[ Buddy ] Continue reading

Posted in Human Robots

#436146 Video Friday: Kuka’s Robutt Is a ...

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!):

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.

Kuka’s “robutt” can, according to the company, simulate “thousands of butts in the pursuit of durability and comfort.” Two of the robots are used at a Ford development center in Germany to evaluate new car seats. The tests are quite exhaustive, consisting of around 25,000 simulated sitting motions for each new seat design.” Or as Kuka puts it, “Pleasing all the butts on the planet is serious business.”

[ Kuka ]

Here’s a clever idea: 3D printing manipulators, and then using the 3D printer head to move those manipulators around and do stuff with them:

[ Paper ]

Two former soldiers performed a series of tests to see if the ONYX Exoskeleton gave them extra strength and endurance in difficult environments.

So when can I rent one of these to help me move furniture?

[ Lockheed ]

One of the defining characteristics of legged robots in general (and humanoid robots in particular) is the ability of walking on various types of terrain. In this video, we show our humanoid robot TORO walking dynamically over uneven (on grass outside the lab), rough (large gravel), and compliant terrain (a soft gym mattress). The robot can maintain its balance, even when the ground shifts rapidly under foot, such as when walking over gravel. This behaviour showcases the torque-control capability of quickly adapting the contact forces compared to position control methods.

An in-depth discussion of the current implementation is presented in the paper “Dynamic Walking on Compliant and Uneven Terrain using DCM and Passivity-based Whole-body Control”.

[ DLR RMC ]

Tsuki is a ROS-enabled quadruped designed and built by Lingkang Zhang. It’s completely position controlled, with no contact sensors on the feet, or even an IMU.

It can even do flips!

[ Tsuki ]

Thanks Lingkang!

TRI CEO Dr. Gill Pratt presents TRI’s contributions to Toyota’s New “LQ” Concept Vehicle, which includes onboard artificial intelligence agent “Yui” and LQ’s automated driving technology.

[ TRI ]

Hooman Hedayati wrote in to share some work (presented at HRI this year) on using augmented reality to make drone teleoperation more intuitive. Get a virtual drone to do what you want first, and then the real drone will follow.

[ Paper ]

Thanks Hooman!

You can now order a Sphero RVR for $250. It’s very much not spherical, but it does other stuff, so we’ll give it a pass.

[ Sphero ]

The AI Gamer Q56 robot is an expert at whatever this game is, using AI plus actual physical control manipulation. Watch until the end!

[ Bandai Namco ]

We present a swarm of autonomous flying robots for the exploration of unknown environments. The tiny robots do not make maps of their environment, but deal with obstacles on the fly. In robotics, the algorithms for navigating like this are called “bug algorithms”. The navigation of the robots involves them first flying away from the base station and later finding their way back with the help of a wireless beacon.

[ MAVLab ]

Okay Soft Robotics you successfully and disgustingly convinced us that vacuum grippers should never be used for food handling. Yuck!

[ Soft Robotics ]

Beyond the asteroid belt are “fossils of planet formation” known as the Trojan asteroids. These primitive bodies share Jupiter’s orbit in two vast swarms, and may hold clues to the formation and evolution of our solar system. Now, NASA is preparing to explore the Trojan asteroids for the first time. A mission called Lucy will launch in 2021 and visit seven asteroids over the course of twelve years – one in the main belt and six in Jupiter’s Trojan swarms.

[ NASA ]

I’m not all that impressed by this concept car from Lexus except that it includes some kind of super-thin autonomous luggage-carrying drone.

The LF-30 Electrified also carries the ‘Lexus Airporter’ drone-technology support vehicle. Using autonomous control, the Lexus Airporter is capable of such tasks as independently transporting baggage from a household doorstep to the vehicle’s luggage area.

[ Lexus ]

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 ]

Tech United Eindhoven is looking good for RoboCup@Home 2020.

[ Tech United ]

Penn engineers participated in the Subterranean (SubT) Challenge hosted by DARPA, the Defense Advanced Research Projects Agency. The goal of this Challenge is for teams to develop automated systems that can work in underground environments so they could be deployed after natural disasters or on dangerous search-and-rescue missions.

[ Team PLUTO ]

It’s BeetleCam vs White Rhinos in Kenya, and the White Rhinos don’t seem to mind at all.

[ Will Burrard-Lucas ] Continue reading

Posted in Human Robots