Рубрика: Robotics

Since Saudi Arabia gave citizenship to a robot known as Sophia in 2017 and she became the world’s first robot citizen, the robotic industry has advanced in other fields as well where artificial humans can be used in productive ways. Even in the world of human-machine intimacy, certain quantum leaps have taken the industry by a boom. In fact, Harmony by RealDoll is among the most evolved sexbots which can blink, move its head, have conversations and comes with self-learning software that remembers earlier encounters and conversations to offer better companionships.

Such bots are customizable and offer a choice of 10 personality types including sexy, funny, angry and certain others. With the advancements pacing at this rate we can expect them to become more evolved, sophisticated and human-like.

More about SexTech Market

Sextech is any technology that has been curated to enhance the human sexual experience and disrupts the way sex is viewed, accessed and enjoyed like never before. However, the industry is still marginalized yet the market is growing at a significant rate. Reportedly, the sextech industry has been valued at US$30 billion and is predicted to grow at an annual rate of 30 percent. The industry has seen growth in such companies that are keeping their prejudices aside to embrace sextech in order to offer some innovation in sexbots and other lines of products. Also, this market is expected to continue to grow and reach the worth of US$122 billion by 2026.

The industry is also viewed as a recession-proof market as regardless of the economic situations, people will always experience sexual desire and innovate their sexuality on a personal level.

Technology and Intimacy

The industry is buzzing with the rising voice of IoB technology. IoB stands for the Internet of Bodies which is basically the Internet of Things (IoT) implanted in the human body. While telepresence is bridging physical distances in a virtual ecosystem, remote intimacy technologies or teledildonics or sexbots are emerging companion to partners separated by distance. Moreover, the industry experts are exploring the new arena of immersive sex content and virtual reality pornography.

Even the prostitution which is considered as the world’s oldest profession is being disrupted by new-age technologies. In several parts of the world including the UK and Canada, brothels are offering sex dolls to customers.
At a digital level, more digitized versions of cyber love and cyber-sex lives (digisexuals) are expected to become an important classification. People can also expect the emergence of a whole new line of products, services, and middlemen such as sexbots counselors.

The innovative and distinguishing features of AI-in-built sex dolls or sexbots will potentially increase intimate connectivity. The ability of sexbots is expected to become more thought-provoking, intellectually stimulating and physically interactive in the future. Also, the mysterious element between the human-machine intimacy through AI and robotics could become more exciting.

However, the orgasmic growth in this industry has raised concerned over change in human nature and how he will nurture emotional alliances with e-individuals. The negative issue could also flourish when people will get used to made-to-order, ever-consenting sex robots which are fears of misogynistic objectification.

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Robotics is one of the most advanced and emerging technologies in the age of digitization. It deals with the design, construction, operation and the use of robots. Looking at its history, the starting point of robotics dated back to 400 BC, when Mathematician Archytas created the first steam-powered mechanical bird. But the research and development in robotics took place in the mid-20th century, majorly within an industrial environment where repetitive movements and lifting heavy objects used machines.

Today, robots have come to play a prevalent and crucial role in a wide array of industrial operations. There are different type of robots including quadruped, cobots, humanoids, and more. And these kinds of robots are being used from manufacturing, heavy-duty industries, agriculture, aviation, and hospitals, to retail, restaurants, entertainment and even in homes.

Investment in Robotics

The field of robotics is still in its growing phase as every day some new innovations and developments befall out there. With this pace of breakthroughs, the field is enticing a series of funding and financial investments. During the first half of 2019, companies in this space raised over US$15.6 billion. And technology for autonomous vehicles and robots, and intelligent systems in healthcare proved as the winners.

So, here we have accumulated the list of top robotics investments.

Agro AI

Amount Funded: $2.6 Billion

Transaction Type: Venture

Lead Investor: Volkswagen Group

Agro AI, a self-driving technology platform, which works with leading automakers to deliver a fully integrated autonomous driving system, clinched a staggering amount of $2.6 billion from Volkswagen AG. Agro AI self-driving system that can be manufactured for safe and reliable deployment in ride-sharing and goods delivery services. With the support of its first customers and partners, Volkswagen and Ford, Agro AI’s self-driving technology is poised to move people and goods around the world.

Uber ATG

Amount Funded: $1 Billion

Transaction Type: Venture

Lead Investor: SoftBank Vision Fund

Uber’s Advanced Technologies Group (ATG), a self-driving car unit of Uber, raised US$1 billion in April 2019. The round was led by SoftBank Vision Fund, Denso and Toyota where SoftBank invested US$333 million and Denso and Toyota invested US$667 million combined. SoftBank is already Uber’s largest shareholder, while Toyota invested US$500 million last year in the company. The investment values the Advanced Technologies Group at US$7.25 billion and develops a newly formed corporate entity with its own board.

Horizon Robotics

Amount Funded: $600 Million

Transaction Type: Series B

Lead Investor: SK China, SK Hynix

Horizon Robotics is the leader of embedded AI that develops artificial intelligence chips for robots. In February 2019, this Chinese AI chip maker secured US$600 million in its latest Series B funding round, which brought its valuation to US$3 billion. The round was led by SK China, SK Hynix, along with additional investors. Horizon Robotics plans to make use of the fresh capital toward continued product and technology development.

Luminar Technologies Inc.

Amount Funded: $100 Million

Transaction Type: Venture

Lead Investor: G2VP

Luminar Technologies, an autonomous vehicle sensor and software company, which powers every autonomous vehicle by delivering the LiDAR technology capable of making them safe and ubiquitous. In July 2019, the company raised US$100 million to boost its LiDar system. This venture funding round led the company’s valuation to US$250 million. Based in Palo Alto, CA, Luminar’s new Iris sensors will be ready to launch commercially on production vehicles rolling out in 2022. The latest funding round was led by G2VP, alongside other investors.

Robotics Mergers & Acquisitions

The year 2019 was the busiest year from the perspective of robotics M&A deals, where most robotics and tech companies poured billions of dollars in funding and investment in order to acquire others to accelerate and expand their business. Today, the M&A segment has become a vital asset for businesses to compete with others. In this way, industry reports indicate that investments in robots, self-driving vehicles, and related systems accounted for at least US$1.3 billion in March 2019. Conversely, automation companies reported US$7.8 billion in mergers and acquisitions last month.

Let’s have a look at top M&A deals that driven the robotics sector to the next level.

Airbus – MTM Robotics

In late December 2019, Airbus SE, a European multinational aerospace company, acquired MTM Robotics, the manufacturer and provider of portable tools and systems to the aerospace industry. For Airbus, the acquisition is the latest step in its industrialization roadmap, intended at leveraging the time- and cost-saving benefits associated with using robotics in the manufacture and assembly of commercial aircraft. According to Airbus, as a subsidiary of Virginia-based Airbus Americas Inc., MTM Robotics will retain its current leadership and 40-employee staff at the 10,000-square-foot Mukilteo facility.

Hitachi – JR Automation

Hitachi has recently completed its acquisition of JR Automation, a leading provider of intelligent automated manufacturing technology solutions, for US$1.42 billion. However, the agreement to acquire JR Automation was announced in April 2019. With JR Automation’s robotic system integration capabilities, combined with Hitachi’s digital solutions and technologies, Hitachi can provide customers with new, unparalleled value by connecting the whole process. Also, the company can now provide its customers with seamless solutions, connecting the entire value chain with data to achieve total optimization.

Siemens Healthineers AG – Corindus Vascular Robotics

Siemens Healthineers AG acquired a leading developer of precision vascular robotics, Corindus Vascular Robotics Inc, for US$1.1 billion. With this deal, Massachusetts-based Corindus has become a part of the Advanced Therapies reporting segment. The acquisition also opens up a new field for Siemens’ Advanced Therapies business, tapping into adjacent growth markets with great potential for the future. Siemens is also taking an important step forward in the upgrading phase of its 2025 strategy.

J&J – Auris Health

Johnson & Johnson (J&J) subsidiary Ethicon has closed a US$3.4 billion acquisition of Auris Health, a surgical robotics developer. Under the deal, Auris Health is eligible for up to US$2.35 billion in additional contingent payments, relying on the accomplishment of select predetermined milestones. After this deal, J&J plans to leverage Auris Health’s Monarch Platform to enlarge its digital portfolio across a variety of surgical specialties, which is currently used in lung diagnostic and therapeutic procedures.

Developments & Innovations in Robotics

Continuous innovation is a core of machines that have long shifted from research labs to venture into new spheres. These robotic machines now have entered the medical sector, automotive, retail, and other fields. The major features why robots are largely being used across industries are relying heavily on its prone to fewer errors, require less downtime, and are cost-efficient.

Almost each industry today is making use of various types of robots, including flying robots SmartBird robotic seagull and the Raven surveillance drone for Aerospace; Consumer robots like the Roomba vacuum and AI-enabled robot assistants; Drones; Educational robots like EMYS; Entertainment robots like RoboThespian, Navi Shaman, and musically inclined bots like Partner.

Also, several types of robotics have been developed in this century such as Exoskeletons for physical rehabilitation or disabled people; Industrial robots for factory and heavy manufacturing hubs; Medical robots for complex surgeries; Military and security robots, Telepresence robots for connecting distant people; Humanoids for mimicking humans and performing several complex tasks that is done by humans.

Let’s have a look at some top real-life robotic innovations and developments in the world.

Sofia – The Humanoid Robot

Sophia, a social humanoid robot developed by Hong Kong-based company Hanson Robotics, which is capable of holding a conversation. This humanoid robot was activated in February 2016 and made her first public appearance at South by Southwest Festival (SXSW) in mid-March 2016 in Austin, Texas. Sophia analyses conversations and extracts data that allows it to improve responses in the future. The company has designed Sophia to be a suitable companion for the elderly at nursing homes, or to assist crowds at large events or parks.

Samsung Bot Care

Electronic giant Samsung launched a fleet of consumer robots that can help users to monitor their health. Bot Care is one of them which is able to measure users’ blood pressure, heart rate, respiration and sleeping state. It can also remind them when it’s time to take their medicine. During its launch at CES 2019, Bot Care rolled out on stage and engaged in a short conversation and when a member placed a finger on its digital face, it checked his blood pressure and heart rate.

Loomo – a Two-Wheeled Self-Balancing E-Vehicle

Loomo is a mobile robot sidekick and mini personal transporter from Segway Robotics, a company backed by Intel and Xiaomi. Loomo includes a lot of features into its self-balancing frame and runs with a top speed of 11 miles per hour and up to a 22-mile range on a single charge. This two-wheeled device can also be controlled with a smartphone app. And with an advanced computer vision system, Loomo can follow a person autonomously, shoot stabilized video, and do more.

Kuri – an Intelligent Robot for Home

Kuri is a robot for the home designed with personality, awareness of its surroundings and the power to move about the house freely. With Wi-Fi, Bluetooth, a 1080p cam and sturdy wheels designed to traverse any interior flooring, Kuri has a lot going for it. It is designed to fit into the home and entertain family member and their loved ones, play music and capture special moments. This nanny-like robot is also capable of reacting to sound, touch and even has a lighting system that lets its users know what mood it’s in. Developed by the Bosch-backed startup Mayfield Robotics, Kuri can set reminders and by using a Wi-Fi connection, it can tell users about the weather.

LG Rolling Bot

LG Rolling Bot is a hybrid security system, smart home device that can roll around the home capturing images and videos. Users can remotely control this ball-shaped device through his/her phone and receive video and audio footage of what’s happening while they are away from their house. The bot can also connect and interact with other smart-home devices like TV and lights, through Bluetooth and the home’s Wi-Fi network. LG Rolling Bot can be used as a security monitoring system for the home or a companion for the pets.

Foldimate – a Laundry Folding Machine

Foldimate is one of the smart home technologies that automatically folds clothes. It can virtually fold almost any type of garment without any problems, except for larger pieces such as sheets or large towels. Created by the US-Israeli company Foldimate, this laundry folding machine is about two-thirds the size of a washing machine. Users just need to simply hang or clip the shoulder area of the shirt on two hooks, afterward, the device pulls the shirt in and in a series of rollers and arms that also move up-down-sideways straighten and fold the item of clothing.

Pepper – a Semi-Humanoid Robot

Developed by SoftBank Robotics, Pepper is in its first kind of robot that can read human emotions. This semi-humanoid robot is built to connect with people, assist them, and share knowledge with them. With its friendly and engaging nature, Pepper can create unique experiences and form real relationships. It is even capable of having a conversation with people, giving them directions, and can dance with them. With a 4-foot-tall, interactive, and ability to read emotions, Pepper is being used by several companies to communicate with customers.

Top Robotics Companies in the World

As robotics defines intelligence in its vibrant style, developments and advancements in robotics technology around the world are continuously increasing. There is rarely an industry anywhere that didn’t improve by robotics. Several companies in this space are growing at a rapid pace, offering different types of opportunities for those who are aware of them. These companies often perform automatic and computerized tasks in higher volume, which is reliable and done securely to confiscate the fatigue level from humans.

Here is the list of top innovative companies in the field of robotics.

Epson Robots

Epson Robots is the leader in the industrial robotics market with its leading factory automation products and solutions. It offered the world with the first PC-based controller called the RC520 and was the first in offering Active X controls. Epson Robots delivers high-performance products, services and solutions that exceed its customers’ expectations. The company is a branch of Japanese corporation Seiko Epson and is leading in PC controlled precision factory automation.

Boston Dynamics

Boston Dynamics, an American engineering and robotics design company, specializes in building dynamic robots and software for human simulation. Headquartered in Massachusetts and founded in 1922, the company is known for its unique robot designs and engineering works. BigDog is Boston Dynamics’ best design that was funded by the US Defense Advanced Research Projects Agency (DARPA) and designed for the American military.

Hanson Robotics

Hanson Robotics, a Hong Kong-based AI and robotics company, which builds socially intelligent machines that enrich the quality of human lives. The company’s innovations in AI research and development, experiential design, robotics engineering, storytelling and material science bring robots to life as engaging characters, useful products, and as evolving AI.

Vex Robotics

Vex Robotics is majorly focused on making tools for students, educators and mentors to facilitate problem-solving. The company’s goal is to create engaging, affordable, and powerful solutions that engage students in STEM (Science, Technology, Engineering, and Mathematics) through the eagerness of developing and programming educational robotics kits. The company has three products – VEX IQ, the VEX Robotics Design System, and VEXpro. Vex Robotics also teams up with the non-profit Robotics Education & Competition Foundation to support the world’s largest and fastest-growing competitive robotics program for elementary schools, middle schools, high schools and colleges around the world.

iRobot

iRobot is an American technology company, which designs and develops behavior-based AI robots. Founded in 1990 by three MIT graduates, the company’s home robots assist people to find smarter ways to clean and accomplish more in their daily lives. Its portfolio of solutions features proprietary technologies for the connected home and advanced concepts in navigation, mobility, manipulation and AI.

KUKA Robotics

The leading manufacturer of robotic systems, KUKA Robotics offers a wide array of industrial robots and robotic systems, which covers all common payload categories and robot types. Founded in 1898 and based in Berlin, Germany, the company provides automation solutions tailored to its customers’ applications and industries and develops robotic systems for individual needs. KUKA Robotics also offers a comprehensive range of services, such as collaborative planning and more to assist its customers to realize the full potential of its products.

DJI

DJI is a China-based technology company, which develops and manufactures innovative drone and camera technology for commercial and recreational use. The company ensures high-end professional photography experience. Besides this, it focuses on drones and unmanned aerial vehicle (UAVs) manufacturing. DJI’s flying and camera stabilization systems redefine camera placement and motion.

Top Industries Making Use of Robotics

Since robotics technology influences each aspect of work and mimic human actions, it is widely used across industries ranging from manufacturing, retail and automotive to earth and space exploration, laboratory and healthcare. Robotics continues to evolve as a large and influential market as it has the capability to positively revolutionize lives and work practices, increase efficiency and safety levels and provide enhanced levels of service.

Thus, here is the list of industries that rapidly utilize robots.

Healthcare

Leveraging robots in the field of healthcare is not new as in 1985 there was a plan to transform industrial robots into precision machines for surgery and beyond. But the appearance of the Da Vinci robotic system in early 2000 opens the way of robotic technology in medical. Today, robots are used for complex surgery, rehabilitation, therapy, patient companionship, among other areas. Even they are providing improved accuracy, precise diagnosis, remote treatment, and boosting human capabilities and performing daily tasks efficiently.

Manufacturing

In today’s factories, robots can be seen working together with human workers, making tedious tasks and freeing up humans to do more valuable works. Currently, most robots are used in manufacturing operations for material handling, processing operations, and assembly and inspection. These robots are generally called industrial robotis that provides a substitute for the human workforce. Most manufacturers are even using cobots (Collaborative Robots), designed to work alongside humans in a shared space. As driven by AI, cobots can learn from their human counterparts, which is a powerful feature that opens up new possibilities for manufacturers.

Agriculture

The agriculture sector nowadays is quickly becoming a high-tech industry, luring new professionals, companies and investors. The sector is now utilizing AI and robotics technology to improve productivity while lowering overall costs. Farmers have already been using tractors and harvesters that are self-guided by GPS. There has also been a rise in the experimental use of autonomous systems automating operations like pruning, thinning, mowing, spraying, and weed removal.

Military

In an effort to secure borders from suspicious or terror activities, most countries’ military forces are making use of some kind of robotics technology. Currently, the majority of military robots are tele-operated and are just used for investigation, surveillance, sniper detection, neutralizing explosive devices, and more. In this way, unmanned aerial vehicles (UAVs) or drones are one of the military robotics systems that are widely used for surveillance activity. Now with technological advancements, the system is used to drop missiles. The U.S. military is already using UAVs to conduct surveillance and drop missiles on suspected terrorist places.

Restaurants

As the advancements in technology are on the rise, robots are now entered in restaurants and are expected to soon be available in kitchens. In restaurants, robots are majorly used for processing foods and warmly serving customers. These food manufacturing robots perform dispensing, feed placement, cutting, packaging or casing of food, and pick-and-placing products into containers. Even some companies are developing robots that can make burgers, cook hundreds of meals, juice, and more. Spyce is one such robotic system that prepares fast-casual bowled meals in its robotic kitchen.

Entertainment

As the AI technologies are still focused on solving real-world issues, these have been now seen in a whole different world of science fiction movies. Today, most movies are depicting AI and robots as good as well as a threat to mankind. Recently released Hollywood movie Terminator: Dark Fate, which is the sixth film of Terminator movie franchise, featured a super-intelligent Terminator. Also, there are several movies that featured AI and robotics, including Alita: Battle Angel, Wandering Earth, Hi, AI, among others.

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As all retail brands are competing against each other in order to stay ahead in technological supremacy. Bentonville-headquartered American MNC Walmart recently unveiled its newest robotic weapon to take on Amazon in the retail battle. The former has rolled out a cadre of robots that are programmed to retrieve items from online grocery orders.

The company has been revamping its tech-landscape from the past few years specifically in the robotics arena. Walmart has also been testing them in a small warehouse attached to a store in Salem, New Hampshire, since the middle of last year. According to the company, the system is now “fully operational and working with associates.” Moreover, it is expected to drastically speed up the online grocery turnaround times.”

As noted by GeekWire, the robots unveiled by the company operate autonomously inside the 20,000-square-foot warehouse, collecting shelf-stable, refrigerated and frozen food. They later deliver the items to a spot where a Walmart employee double-checks everything, bags the food and finishes the order.

When a customer orders items online, employees usually roam around in stores picking them which is a time-consuming process and needs longer lead times between the customer ordering items online and its delivery. However, even after the implementation of robots, employees will continue to pick items that are produced by hand.

Brian Roth, a senior manager of pickup automation and digital operations for Walmart US said in a statement, “Ultimately, this will lower dispense times, increase accuracy and improve the entirety of online grocery. And it will help free associates to focus on service and selling, while the technology handles the more mundane, repeatable tasks.”

Moreover, the company has allied with Alert Innovation since 2016 to work on this project. Walmart will continue to refine the Alphabot and the Salem store is expected to remain its home. According to the company, after receiving employee feedbacks, it will consider rolling out the system at other stores as well.

The growth of this technology, the merger of online ordering with the company’s numerous stores’ network under the banner of Walmart has been driven by several resources. Although Walmart is the country’s largest grocery retail brand yet it faces tough challenges from Amazon which is and has been making a hefty investment in grocery shopping innovation by acquiring Whole Foods, a supermarket company.

Talking about Walmart’s online grocery business, Tom Ward, senior vice president of central operations for Walmart said, “Demand for this business continues to grow and systems like Alphabot allow us to scale enormously.”

According to Roth, Alphabot will prove to be transformative for the company. He further added in his statement, “By assembling and delivering orders to associates, Alphabot is streamlining the order process, allowing associates to do their jobs with greater speed and efficiency. Ultimately, this will lower dispense times, increase accuracy and improve the entirety of online grocery. And it will help free associates to focus on service and selling, while the technology handles the more mundane, repeatable tasks.”

Moreover, he is optimistic about its impact on the company’s supply chain, for which he asserted, “This is going to be a transformative impact on Walmart’s supply chain. Alphabot is what we think of as micro-fulfillment – an inventive merger of eCommerce and brick-and-mortar methods.”

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The company that is known for intelligent robot-systems, CloudMinds has developed a smart robot rental program that serves intelligent cloud service humanoid robots. This robot, as announced by the company, is designed for entertainment at trade shows, weddings, special events, conferences, and offices.

Well-equipped with advanced NLP (Natural Language Processing) and sophisticated task ability, the robots are accessible to everyday people through smart interactions. The system can interact in multiple languages and entertain people through dancing and gestures while delivering customized brand experience.

Bill Huang, founder, and chief executive officer of CloudMinds said, “We’re bringing the power of cloud artificial intelligence-powered robots, which learn with human input, closer to society. This further strengthens our foundation in providing an even wider range of intelligent compliant service robots from CloudMinds – from wheeled to two-legged form factors. Ultimately, we’re elevating what is now the ‘new normal’ expectation of helpful, friendly robots for homes and businesses.”

According to Alberto Scherb who works as the senior director of the CloudMinds Smart Robot rental program, this rental program will start with the Cloud Pepper robot, which is already quite well-known across several industry verticals in the world. He also implied that the future plans with this program include Cloud Cleaning, Cloud Assistant, Cloud Patrol, and Cloud Vending robots.

As noted by BiometricUpdate, Cloud Pepper is developed on SoftBank Robotics’ Pepper, considered the first personal humanoid robot, and runs on cloud-based AI developed by CloudMinds. The intelligence of the robot can be judged as it integrates CloudMinds’ Human Augmented Robotics Intelligence (HARIX) platform (or “Cloud Brain”) and an ultra-secure virtual backbone intranet (“Nerve Network”). It also uses facial recognition to identify people and is capable of understanding their moods as well.

Moreover, Cloud Pepper’s NLP feature enables it to communicate in different languages, record demographics and analyze customer interactions. Its suggested use cases include – brand ambassador at tech or medical tradeshows, fashion events and book launches, receptionist or representative at airports, schools, hospitals, and other public spaces.

Apart from CloudMind’s innovation SpaceX’s Dragon capsule includes a robo astronaut called Cimon-2 which can entertain the crew for the next three years, according to WTKR.

Notably, Cimon-2 is a brand-new model of the Crew Interactive Mobile Companion that has been built by Airbus at the German Aerospace Center and its AI is developed on IBM’s Watson technology.

Cimon-2 is an autonomous robot with abilities such as emotional intelligence and is expected to assist with different tasks on the space station, including serving as a conversation companion. The robot has two facial recognition cameras for eyes and five extra cameras for autonomous navigation and video recording. Through the contribution of psychologists, Cimon-2 has a personality and is capable of using different tones in conversation.

During a demonstration session, Cimon played music, gave instructions, and used facial recognition to recognize the person it was interacting with. It can also make eye contact with the same person. It also possesses the capabilities of photo and video recording which sparked the concern about what it will end up sharing.

Judith Buchheim, a researcher involved in the robot’s ethics evaluation said, “The new Cimon has a built-in switch that enables the data streams from all cameras and microphones to be interrupted from the ISS. The astronaut has control over Cimon at all times, which was especially important for us.”

Matthias Biniok, IBM’s Lead Watson Architect for Germany asserted, “When it was first deployed on the ISS, Cimon proved that it could understand not only the content within its given context but also the intention behind it. Cimon-2 goes one step further. With the help of the IBM Watson Tone Analyzer from the IBM Cloud in Frankfurt, it is now able to evaluate the emotions of the astronauts and respond to the situation in an appropriate way if this is desired by the astronauts, or if its emotional analysis capabilities are being tested as part of an experiment. This allows Cimon-2 to transition from a scientific assistant into an empathetic companion, as required.”

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Today, technology like robotics and AI are taking over the world while providing greater comfort, innovative lifestyle and better business prospects to people. Specifically, robots are something which people used to fantasize about while watching sci-fi movies but with the boom of industry 4.0, such innovative, versatile and useful robots have become the reality now. Who would have thought that one-day people will be staying in a robot hotel with robots providing usual hospitality services? Japan a few years back had set up a robot enabled hotel named Henn na, or “Strange”. However, the hotel was not much of a success when it came to serving with desired hospitality to guests.

Where on one hand Robot enabled hotels are yet to become a commercial reality-success for earthly people, NASA has already taken a quantum leap where it has established a robotic hotel in space.

Sounds Imaginary? Fortunately, it’s true.

A SpaceX Dragon spacecraft last month arrived at the International Space Station to deliver tons of fresh supplies and equipment for NASA, including a “robot hotel”, notes Space.com.

According to NASA, at times robots too need a place to stay even if they are in space. The organization has attached a robot hotel to the outside of the International Space Station with the launch of the Robotic Tool Stowage (RiTS), a protective storage unit for critical robotic tools. RiTS was launched on December 4, 2019, aboard the 19th SpaceX commercial resupply mission.

As stated by NASA, “its first residents will be two Robotic External Leak Locators (RELL). Outfitted with mass spectrometers capable of “sniffing” out the presence of gases such as ammonia, these robotic tools are used to detect leaks from the station. Two RELL units are on board the station right now: the first RELL launched in 2015, and it proved to be such a success that a second RELL was launched as a backup earlier this year.”

Prior to the launch of RiTS, Mark Neuman, RiTS hardware manager said, “For each of its stored tools, RiTS will provide heat and physical protection from radiation and micrometeroids, or tiny, high-speed objects hurtling through space. Its thermal system maintains ideal temperatures for the instruments, helping them stay functional.”

Moreover, the organization said, having this housing unit in place will also help the space station’s robotic arm, Dextre, to easily locate, grab and put back important tools.

Further NASA informs that, in space, storage is especially important. Keeping RELL inside the station takes up space that could be used for other scientific hardware and experiments.

Additionally, the process of deploying RELL takes much longer when the tool is not externally stored. RELL is a robotic tool operated remotely by mission controllers on the ground, created to facilitate space station repairs, but requires crew schedule and airlock availability to bring RELL outside the station with the use of station’s Dextre robotic tool.

According to the space organization, once outside the station, RELL currently needs to wait 12 hours in space before it can be used. This allows for RELL’s extremely sensitive gas analyzer to clear itself of water vapor and other gases from inside the station, essentially giving the instruments a clean slate. Because of this extensive process, it could take multiple weeks or even months from the time a leak is suspected, to the time RELL is deployed, to then find out where it is coming from. With RiTS, this entire process would only depend on Dextre’s availability, greatly expediting the search for leaks.

Furthermore, NASA believes that the human and robotic collaborations like these can be applied to more than just the space station, including potential exploration of the Moon, Mars and beyond.

Notably, RiTS was developed by the Satellite Servicing Projects Division at NASA’s Goddard Space Flight Center in Greenbelt, Maryland, in partnership with NASA’s Johnson Space Center in Houston.

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The global stage for innovation again created a stir in technology-industry this year. The Consumer Electronic Show or CES 2020 was nothing like a usual show off of technologies rather the event went to whole another level with several innovative tech-companies’ participation. From Samsung to Hyundai, the Las Vegas event narrated the ode of new age innovations in Artificial Intelligence (AI), Robotics, Drones Technology, Autonomous Vehicle and Smart City prototypes, that are about to hit the market soon and will potentially become a fashionable yet essential part of our lives.

All those who thrive on the business of consumer technologies has served with unusual and breakthrough creations to locate where next-generation innovations lie.

Here is a list of 15 never-seen before ideas and machines which took center stage at CES 2020.

Take a sneak peek to the future through CES 2020 window!

Artificial Intelligence

BrainCo

BrainCo has unveiled a new AI-powered prosthetic hand that works with an amputee’s brain waves and muscle signals. The invention has been named as one of Time Magazine’s top 100 inventions of 2019 — at CES 2020. The company expects commercial launch of this hand in the US market later this year.

Max Newlon, president of BrainCo USA, told CNET, “We came up with a new way to understand electrical signals coming from the brain, going into the residual limb of the amputee, and detecting the intention of the user.”

Samsung

Ballie
Samsung, at CES 2020, introduced its vision of robots as ‘life companions.’ The company rolled out a tiny, ball-shaped AI device that rolls around the house and responds to commands like a pet dog. It is designed to act as a personal assistant for the home.

The AI device employs a mobile interface, on-device artificial intelligence (AI) capabilities, voice activation and an in-built camera to identify and respond to its users, and assist them with various household tasks.

Neon

Samsung along with Star Labs, unveiled its another innovative technology known as Neon. The company describes it as “a computationally created virtual being that looks and behaves like a real human, with the ability to show emotions and intelligence.”

According to the company, “Neons are not AI assistants. Neons are more like us, an independent but virtual living being, who can show emotions and learn from experiences. Unlike AI assistants, Neons do not know it all, and they are not an interface to the internet to ask for weather updates or to play your favorite music.”

LG

LG has released some of the details for its 2020 lineup of soundbars with biggest new feature of AI Room Calibration. It is a system that automatically adjusts the sonic properties of LG’s premium soundbar models to better match the acoustics of the room.

As noted by Digital Trends, LG said in its press release that, “These advanced models are self-calibrating, able to recognize and analyze tones to accurately assess the dimensions of a given space and adjust accordingly.” Moreover, the benefits of this system are particularly noteworthy when playing content mastered with Dolby Atmos or DTS:X.

Intel

According to Intel, “The American Red Cross, its Missing Maps project and Intel are using artificial intelligence (AI) to map vulnerable populations in developing nations to aid with disaster preparedness. Throughout 2019, Intel data scientists built a computer vision model that can identify previously unmapped bridges and roads on satellite images from Uganda.”

The AI model augments mappers’ abilities to cover more ground and can catch things that may be difficult for the human eye to find. For example, the model found 70 bridges in southern Uganda that had been missed in either OpenStreetMap or the official Ugandan Bureau of Statistics map, says Intel.

BIC

At CES 2020, Bic announced its collaborative platform the company plans to use to foster innovation and creative products. One of these collaborative efforts is with Invoxia and it is something surprising: A connected razor, notes Digital Trends.

According to Eric Carreel, the co-founder of Invoxia, “By using a smart device that collects useful data, we can better understand just about anyone’s bats and provide instant and personalized feedback.” Moreover, the AI could help adjust the speed of the razor to better match the density of the hair on your face, for example.

Robotics

Procter & Gamble (Charmin)

Charmin has rolled out its Rollbot which is a cute little robot with a crucial job of getting you toilet paper when all hope is lost. It is a self-balancing robot which rolls around on a pair of wheels while carrying the all-important roll of toilet paper. You can connect this robot with your smartphone via Bluetooth. This does create some limitations, primarily that you’ll need to have your phone with you and it will need to be within 30 feet since it uses Bluetooth instead of Wi-Fi to communicate.

The gadget is part of GoLab, one of the latest marketing innovations commissioned by Charmin, the P&G-owned toilet paper and tissue brand.

Samsung

Across the Samsung’s CES 2020 booth, the visitors discovered Bot Chef which is a pair of robotic arms that cook salad on command. The bot chef can rummage through cabinets, pour ingredients into a pan, and mix them up to create a tofu salad, using AI and computer vision algorithms.

As noted by Tech Radar, “In many ways Bot Chef felt like the most futuristic technology on show at the Samsung CES 2020 booth, despite being situated among the company’s screen-based 5G phones, 8K QLED TVs, giant Wall TVs and rotating Sero displays.”

Delta Airlines

Delta Air Lines Inc. demonstrated the Guardian XO industrial exoskeleton at CES 2020 in partnership with Sarcos Robotics. It is a battery-powered, full-body exoskeleton designed to boost human performance and endurance while helping to prevent injury, according to Sarcos.

As noted by the Robot Report, “This robotic suit does the heavy lifting for employees by bearing its own weight in addition to a payload. Guardian XO can enable a worker to lift up to 200 lb. repeatedly for up to eight hours at a time without strain or fatigue. Because the Guardian XO supports natural, fluid and intuitive movement, it requires relatively minimal operator training. A user can put on or take off the exoskeleton in just 30 seconds, said the company.”

Smart City

Toyota

Toyota announced its ‘Toyota Woven City’ smart city plan at CES 2020. It is an urban prototype for the near future which is the work of the Japanese car giant and Danish architecture firm BIG-Bjarke Ingels Group. The project proposes a fully connected ecosystem, powered by hydrogen fuel cells. This prototype city will act as a living laboratory for testing and advancing mobility ideas – autonomy, connectivity, alternative-powered infrastructures. As noted by Forbes, “this is much more than a conceptual idea. Starting next year, Toyota Woven City will be constructed on a 708,200 m2 site on the foothills of Mount Fuji in Japan.”
BIG’s founder, Bjarke Ingels said, “As a replicable framework, it can serve both as a prototype for future cities and as a retrofit to current cities. By simply ‘reprogramming’ existing streets, we can begin to reset the balance between people, mobility and nature in cities as diverse as Tokyo or New York, Copenhagen or Barcelona.”

Autonomous & Future Vehicles

Qualcomm

The American multinational semiconductor company, Qualcomm revealed a new automotive platform called Snapdragon Ride which has been designed to power all levels of automated driving, from today’s active safety systems in passenger cars to future’s robotaxis.

Nakul Duggal, senior vice president of product management at Qualcomm told TechCrunch, “The Snapdragon Ride platform is designed to support the top three industry segments in automated driving. It can handle the hardware requirements for the active safety advanced driver assistance systems found in today’s passenger vehicles, including lane keeping, traffic sign recognition and automatic emergency braking.”

ZF

The technology company ZF, which is concentrating on Level 2+ semi-automated systems that deliver advanced safety and convenience functions, has, along with its partners, developed the most affordable Level 2+ system in the industry. As noted by Auto Car Pro, ZF’s coASSIST is the first step into the modular Level 2+ hardware and software suite and highlights ZF’s capabilities as the full system supplier. From 2020, ZF says it will equip production vehicles with this new system for a major Asian OEM.

According to the company, this Level 2+ semi-automated driving systems is a pragmatic and feasible approach to help enhance safety and comfort in passenger cars. By combining an advanced sensor suite including cameras and radars with a central electronic control unit, functions such as adaptive cruise control, traffic sign recognition, lane change assist, lane keeping assist and traffic jam support are enabled.

Audi

At the 2020 Consumer Electronics Show (CES), Audi offered a look at tomorrow’s mobility – and is already integrating future technology into its current products. At Las Vegas even, Audi presented the Audi AI:ME as a personal mobility partner with an empathetic Audi Intelligence Experience technology.
The Audi AI:ME is part of the family of concept cars that was launched in 2017. Each of the four vision vehicles with electric drive is tailored specially to its clearly defined area of use: The Audi AI:CON for long-distance driving, the AI:RACE for the race track, and the AI:TRAIL for all-terrain driving.

Drones and Flying Vehicles

Sunflower Labs

CES 2020 has introduced the world with new kind of home security system including drones to patrol people’s property, along with sensors designed to mimic garden light and a central processor to bring it all together.

Sunflower Labs debuted their new Sunflower Home Awareness System, which includes the Bee which is a fully autonomous drone that deploys and flies on its own. It has cameras on board to live-stream video. It has been designed to supplement more traditional passive monitoring, and can be deployed on demand to provide more detailed information and live views.

Hyundai – Uber

Uber and Hyundai unveiled a flying taxi, for transforming ridesharing trips, at the Consumer Electronics Show in Las Vegas. The companies revealed a model of a four-seat, electric flying vehicle that, according to them, people will be able to summon for a ride through Uber’s app someday. As told by Hyundai’s spokesperson, the first actual prototype will be ready in 2023. The company further asserted that a human pilot will fly the air taxi until the companies finalize software to autonomously control it.

However, William Crossley, a Purdue University professor who researches aerospace design said, “It’s going to be a while. If things go well, it’s certainly plausible in the next 10 years.”

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In a world where everything is driven by computers and technology, how far can you imagine the great hypes of Artificial Intelligence (AI) or Quantum Computing (QC) will go? In fact, none can think about the potential applications of both technologies. Both possess the power to be integrated with numerous mechanisms and add more efficiency and value to it.

While everyone is still digesting the fact that robots with the integration of AI can actually be intelligent, quantum computing has also approached robotics to discover some new nuances. As we enter into a new era of computing, the paradigm shift will also impact the work of robotic scientists and the applications of robotics.

According to a research report “Quantum Computation in Robotic Science and Applications” by Bernhard Dieber, we acknowledge that the possibilities, as well as new approaches to known problems, will enable the creation of even more powerful and intelligent robots that make use of quantum computing cloud services or co-processors. The report throws light on potential application areas in quantum computing for robotics.

Application of Quantum Computing in Robotics

As noted by the report authors, there is a high probability that quantum computers will have a positive impact on many scientific disciplines and their applications in the future. In several fields, useful applications are already being explored, including scientific computing, cryptography, chemistry, drug development, and finance. However, across the robotics field, the following are the significant applications of quantum computing.

Sense: Perception, Vision, and Sensor Data Processing

The modern autonomous robots need fast vision capabilities in order to perceive and assess their environment. Computer vision and image recognition algorithms are computationally expensive as they have to compute results on millions of pixels. Therefore, the hopes lie with the quantum efficiency to better understand the nature of visual information, and to secure, store and process them efficiently with the help of quantum properties – entanglement and parallelism. Such attempts lead to a sub-discipline called quantum image processing (QIMP). The basic idea is that properties of an image, like the colors at certain positions, can be encoded as qubit-lattices, which was widely accepted and formally extended by many representations and possible applications, including videos.

As visualized into quantum image representations (QIRs), transformations, applications, and algorithms are required for robotic perception. However, this approach only deals with two-dimensional images, which is not sufficient when dealing with robotic perception, where the input of multiple sensors is often fused into a three-dimensional point cloud, in order to locate and identify objects and environments.

As suggested by the report, currently, only a few methods exist to express a three-dimensional image by quantum representation in the form of the quantum point cloud. As with other quantum technologies, the general expectation is that QIMP will surpass the capabilities and performance of its traditional equivalents by far.

Think: Traditional Artificial Intelligence in Robotics

Traditional AI, in contrast to modern machine learning approaches, is based on formal knowledge representations (e.g., by rules and facts) and algorithms in order to optimize the robot behavior or mimic intelligent (human) behavior. AI-applications are frequently used in robotics, like path planning, the deduction of goal-oriented action plans, system diagnosis, the coordination of multiple agents, or reasoning and deduction of new knowledge. Most of these applications employ variations of uninformed (blind) or informed (heuristic) search algorithms, which are based on traversing trees or graphs, where each node represents a possible state in the search space, connected to further follow-up states.

Whether it is complex search, basic search or graph search, quantum computing works as the alternative for AI in almost every aspect. For example, for graph search algorithms there is also a quantum alternative based on quantum random walks. Moreover, quantum algorithms for ‘decision making under uncertainty’ applications are already formulated, like quantum Markov chain and quantum Markov processes.

Act: Kinematics and Dynamics

For many years now, attempts have been made to solve classical robotic tasks using artificial intelligence methods as an alternative. For this reason, it is not surprising that analogous works can be found, which want to solve kinematic problems with quantum neural networks, e.g., the inverse kinematics problem or using quantum genetic algorithm, e.g., for trajectory planning.

The authors expect that the two levels of control in robotics, i.e. abstract task-planning and specific movement-planning, that are currently often solved separately, due to their combined complexity, can be solved in a more integrative way through quantum computing. In particular, the potential of quantum optimization will provide interesting new opportunities for control schemes that utilize on-line optimization such as model-predictive control or even classic dynamic programming formulations of control problems.

Furthermore, the use of quantum computers in a multi-state operation appears to be useful to find the global solution of complex optimization problems. For this purpose, a first quantum computer resource for the generation of start solutions and a second quantum computer resource for the finding of optimal solutions are used.

Observe: Diagnosis and Data Mining

In modern robotics, experience shows that even carefully designed and manufactured robots encounter faults due to reasons like degradation of components over time or incomplete knowledge of the environment in which a robot operates. Therefore, methods to detect and specify these faults are essential. The problem of diagnosis can generally be characterized as the problem of finding the components in a system that describes the discrepancy between the observed and the expected behavior of the system best. The set of methods builds either on systems theory, AI methodologies or hybrid approaches.

The classic consistency based approach, for example, deduces diagnoses on the basis of solving a minimal hitting-set problem, which is a common optimization problem in AI. The hitting-set problem is one of the 21 classical NP-hard problems of Karp. It can be reformulated as a vertex cover problem for which quantum computing approaches already exist. Data mining is the process of extracting information from and discovering patterns in large data sets. Thus, data mining is a valuable tool for knowledge discovery in order to diagnose systems, e.g. to identify the sources and reasons for erroneous robot behavior by mining the robot’s log files. Data mining and analysis involve methods from machine learning, statistics, and database systems (like index searches), which are optimally suited to be tackled with quantum algorithmic approaches.

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Robotics has ventured into a variety of industries to drive better efficiency. Specifically, in the manufacturing field, its advents are quite commendable. For example, for its assembly line, Henry Ford inherited stationary robotic units that are positioned “behind the fence” and away from humans. This allows the robots to do their work without harming workers. Such robots are extremely energetic and don’t get fatigued. This is what personifies efficiency.

However, efficiency is not the sole advantage offered by robotics, manufacturers are also considering the implementation of the technology to planning and shop-floor operations. As noted by Andreas Bauer who is a Team Lead at University Datacenter (University of Augsburg), robotics can help some enterprises more flexibly program customizations into the assembly process – so this car gets a sunroof, and that one gets the sports trim. This flexibility allows manufacturers to accommodate customer preferences with greater ease.

As assembly lines are still common, the robotics implementation is shifting towards flexible machines as well. With its self-learning capabilities that help optimize processes over time, leveraging robotics at such a scale helps fuel a much higher degree of modularization in production.

However, it is necessary to acknowledge not all manufacturing requires the same robotics support. Possibly, an auto manufacturer follows different processes than a manufacturer of semiconductors. Therefore, for robots to be more broadly adopted, they need to be made in a domain-agnostic way.

Andreas says, robot functionality, in a sense, needs to be modularized which requires a certain amount of standardization across use cases. Basic equipment – such as motion sensors, grippers, joints, voice recognition systems, and welding cells – can be used across models and quickly adapted to a wide range of requirements and unique use cases.

In Horizons by SAP, he quotes that, “as robots are used as part of complex processes manufacturing and otherwise – this notion of standardization needs to extend to backend business and operational systems as well. One area ripe for progress is the technological integration of robots into MESs. By creating robotics that can flexibly adapt to specific use cases and still interoperate with other applications, companies could improve the networking and interdependency among these technologies.”

Moreover, while progress in standardization is still needed, robots are already being employed to make personalization feasible in terms of cost, timely delivery, operational logistics, and other key metrics. Manufacturers can use robots to enhance customization, even with assembly-line production models. However, the production cell approach is leading the way forward in terms of increasing flexibility and responsiveness to customer demand.

Several companies in today’s competitive era are competing in the arena of customer experience. In fact, the product created by manufacturers is an integral part of that experience. Amid this what can make a difference is that – the ability to personalize the product to unique customer expectations and requests.

Andreas says the production cell approach maximizes customization flexibility. With the collaboration of robots and humans, organizations can harmonize unique production runs. The result is sometimes called “mass customization” – or the ability to deliver what customers want with short lead times and optimal price points that drive both sales and profitability.

Moreover, consumer electronics companies can meet demands for storage capacity or screen size without producing large lots ahead of time and hoping to sell what’s produced. Shoemakers, on the other hand, can open their design process to consumers and then deliver precisely what the customer has created.

Such mass customization is already happening today with robotics and modular production techniques. Furthermore, in the future, advancements in robotics will make it easier for manufacturers to bring their customers more intimately into the product experience – from design to production. Also, making the use of modular robotics technologies to increase personalization, manufacturers can increase customer engagement and increase loyalty over time.

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A team of scientists from the University of Vermont has re-purposed living cells—scraped from frog embryos—and assembled them into entirely new life-forms – xenobots. These millimeter-wide bots can move toward a target, perhaps pick up a payload (like medicine that needs to be carried to a specific place inside a patient)—and heal themselves after being cut.

According to Joshua Bongard, a computer scientist and robotics expert at the University of Vermont who co-led the new research, “these are novel living machines. Xenobots are neither a traditional robot nor a known species of animal. It’s a new class of artifact: a living, programmable organism.”

Reportedly, the new xenobots were designed on a supercomputer at UVM—and then assembled and tested by biologists at Tufts University. The co-leader Michael Levin who directs the Center for Regenerative and Developmental Biology at Tufts said, “we can imagine many useful applications of these living robots that other machines can’t do – like searching out nasty compounds or radioactive contamination, gathering microplastic in the oceans, traveling in arteries to scrape out plaque.”

The new research results were published on January 13 in the Proceedings of the National Academy of Sciences.

This research, for the first time ever, “designs completely biological machines from the ground up,” the team writes in their new study.

According to UVM Today, with months of processing time on the Deep Green supercomputer cluster at UVM’s Vermont Advanced Computing Core, the team—including lead author and doctoral student Sam Kriegman—used an evolutionary algorithm to create thousands of candidate designs for the new life-forms. Attempting to achieve a task assigned by the scientists—like locomotion in one direction—the computer would, over and over, reassemble a few hundred simulated cells into myriad forms and body shapes. As the programs ran—driven by basic rules about the biophysics of what single frog skin and cardiac cells can do—the more successful simulated organisms were kept and refined, while failed designs were tossed out. After a hundred independent runs of the algorithm, the most promising designs were selected for testing.

Post selection, the team at Tufts, led by Levin and with key work by microsurgeon Douglas Blackiston—transferred the in silico designs into life. First, they gathered stem cells, harvested from the embryos of African frogs, the species Xenopus laevis (hence the name “xenobots”). These were separated into single cells and left to incubate. Then, using tiny forceps and an even tinier electrode, the cells were cut and joined under a microscope into a close approximation of the designs specified by the computer, notes UVM Today.

Assembled into body forms never seen in nature, the xenobots cells began to work together. The skin cells formed a more passive architecture, while the once-random contractions of heart muscle cells were put to work creating ordered forward motion as guided by the computer’s design, and aided by spontaneous self-organizing patterns—allowing the robots to move on their own.

According to Levin, “if humanity is going to survive into the future, we need to better understand how complex properties, somehow, emerge from simple rules.” Much of science is focused on controlling the low-level rules. He says, “we also need to understand the high-level rules. If you wanted an anthill with two chimneys instead of one, how do you modify the ants? We’d have no idea.”

Further, he adds, “I think it’s an absolute necessity for society going forward to get a better handle on systems where the outcome is very complex. A first step towards doing that is to explore: how do living systems decide what an overall behavior should be and how do we manipulate the pieces to get the behaviors we want?”

According to him, in other words, “this study of xenobots is a direct contribution to getting a handle on what people are afraid of, which is unintended consequences – whether in the rapid arrival of self-driving cars, changing gene drives to wipe out whole lineages of viruses, or the many other complex and autonomous systems that will increasingly shape the human experience.”

UVM’s Josh Bongard says, “there’s all of this innate creativity in life. We want to understand that more deeply—and how we can direct and push it toward new forms.”

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Due to unfortunate limitation of the design and adoption of large datasets in reinforcement learning and robotics, it is not apparent how to move towards an “ImageNet-scale” dataset for robotics that is useful for the entire research community. Hence, Sudeep Dasari along with fellow researchers at University of California, Berkeley proposed to collect data across multiple different settings, including from varying camera viewpoints, varying environments, and even varying robot platforms. Motivated by the success of large-scale data-driven learning, the researchers created RoboNet, an extensible and diverse dataset of robot interaction collected across four different research labs. The collaborative nature of this work allows them to easily capture diverse data in various lab settings across a wide variety of objects, robotic hardware, and camera viewpoints. Finally, they found that pre-training on RoboNet offers substantial performance gains compared to training from scratch in entirely new environments.

According to BAIR (Berkeley Artificial Intelligence Research), the RoboNet consists of 15 million video frames, collected by different robots interacting with different objects in a table-top setting. Every frame includes the image recorded by the robot’s camera, arm pose, force sensor readings, and gripper state. The collection environment, including the camera view, the appearance of the table or bin, and the objects in front of the robot are varied between trials. Since collection is entirely autonomous, large amounts can be cheaply collected across multiple institutions.

The Usage and Implementation of RoboNet

According to the researchers, post collecting a diverse dataset, they experimentally investigated how it could be used to enable general skill learning that transfers to new environments. First, the researchers pre-trained visual dynamics models on a subset of data from RoboNet, and then fine-tuned them to work in an unseen test environment using a small amount of new data. The constructed test environments, all include different lab settings, new cameras and viewpoints, held-out robots, and novel objects purchased after data collection concluded.

After tuning, Sudeep and his fellow researchers deployed the learned dynamics models in the test environment to perform control tasks – like picking and placing objects – using the visual foresight model based reinforcement learning algorithm.

After that, they could then numerically evaluate if their pre-trained controllers can pick up skills in new environments faster than a randomly initialized one. In each environment, the researchers used a standard set of benchmark tasks to compare the performance of their pre-trained controller against the performance of a model trained only on data from the new environment. The results show that the fine-tuned model is ~4x more likely to complete the benchmark task than the one trained without RoboNet. Impressively, the pre-trained models can even slightly outperform models trained from scratch on significantly (5-20x) more data from the test environment. This suggests that transfer from RoboNet does indeed offer large performance gains compared to training from scratch!

Researchers Involved in RoboNet

Frederik Ebert

Frederik is a PhD student in Computer Science at UC Berkeley advised by Prof. Sergey Levine and Prof. Chelsea Finn (Stanford CS department). In his research at the Berkeley Artificial Intelligence Laboratory (BAIR) he focuses on the development of algorithms for robotic manipulation using techniques from deep learning, deep reinforcement learning and classical robotics. He completed a Bachelor’s degree in mechatronics and information technology and a master’s degree in “Robotics Cognition Intelligence” at TU Munich (TUM).

Previously he has worked at the mechatronics institute of the German Aerospace Center (DLR) on the mechanical design and control system of a quadruped robot.

Stephen Tian

Stephen is a third-year Electrical Engineering and Computer Science student at UC Berkeley.
He is fortunate to work with Prof. Sergey Levine and his mentor Frederik Ebert as an undergraduate researcher in the Robotic AI & Learning Lab. His research interests currently lie in robotics and reinforcement learning. He recently spent an amazing summer working with Dr. Roberto Calandra and others of the Facebook AI Research Robotics team.

Suraj Nair

Suraj is a PhD student in Computer Science at Stanford University, where he works at the intersection of machine learning, computer vision, and robotics. Specifically, he is interested in problems relating to multi-task learning, hierarchical reinforcement learning, and perception for robotics. He is co-advised by Professors Chelsea Finn and Silvio Savarese, and is funded by the National Science Foundation Graduate Fellowship.

Suraj completed his Bachelors in Computer Science at the California Institute of Technology (Caltech), where he worked with Yisong Yue on multi-agent reinforcement learning. In the past he has worked at Google Brain and General Electric Current.

Bernadette Bucher

Bernadette is a PhD Student in the GRASP lab at University of Pennsylvania advised by Dr. Kostas Daniilidis. Her research interests broadly lie in developing meaningful representations of sensory data in robotic systems for intelligent autonomous decision making. Her current work focuses on neuromorphic approaches to perceptual decision making.

Prior to starting her PhD, Bernadette was a Senior Software Engineer at Lockheed Martin Corporation where she worked from 2014 to 2019. She received an M.A. in Mathematics, M.A. in Economics, and B.S. in Mathematics and Economics from The University of Alabama in 2014.

Karl Schmeckpeper

Karl is a Robotics Masters student at the University of Pennsylvania. He graduated from the University of Massachusetts Amherst with a major in Computer Science, a concentration in Robotics, and a minor in Mathematics. He completed his undergraduate thesis on Lazy Localization under Professor Roderic A. Grupen at the Laboratory for Perceptual Robotics. Between earning his undergraduate degree and starting his masters, he spent six months working at MIT Lincoln Laboratory on semantic mapping, visual slam, and augmented reality. He is interested in applying artificial intelligence to allow robots to act in complex, changing, and uncertain environments.

Siddharth Singh

Siddharth is a Masters student at University of Pennsylvania pursuing Electrical Engineering and he works in the domain of General Robotics. He believes in a pull-your-sleeves-up and get-it-done approach. He is familiar with the various aspects of Robotic Systems Development including and not limited to Path/Trajectory Planning and Tracking, Control System Design, mapping and bayesian filtering techniques. He is also familiar with Geometric Perception based techniques and Learning based Vision paradigms. Siddharth is now trying to bridge the gap between the planning/control frameworks and the Vision frameworks.

Sergey Levine

Sergey received a BS and MS in Computer Science from Stanford University in 2009, and a Ph.D. in Computer Science from Stanford University in 2014. He joined the faculty of the Department of Electrical Engineering and Computer Sciences at UC Berkeley in fall 2016. His work focuses on machine learning for decision making and control, with an emphasis on deep learning and reinforcement learning algorithms. Applications of his work include autonomous robots and vehicles, as well as computer vision and graphics. His research includes developing algorithms for end-to-end training of deep neural network policies that combine perception and control, scalable algorithms for inverse reinforcement learning, deep reinforcement learning algorithms, and more.

Chelsea Finn

Chelsea is an Assistant Professor in Computer Science and Electrical Engineering at Stanford University. Her lab, IRIS, studies intelligence through robotic interaction at scale, and is affiliated with SAIL and the Statistical ML Group. She also spends time at Google as a part of the Google Brain team. Chelsea is interested in the capability of robots and other agents to develop broadly intelligent behavior through learning and interaction. Previously, she completed her Ph.D. in computer science at UC Berkeley and her B.S. in electrical engineering and computer science at MIT.

Sudeep Dasari

Sudeep is a PhD student at the Robotics Institute in Carnegie Mellon’s School of Computer Science. He aspires to build scalable robotic learning algorithms, which can parse the visual world and enable autonomous agents to perform complex tasks in diverse environments. He is advised by Professor Abhinav Gupta.

In a prior life, he was an undergraduate student at UC Berkeley – where he worked with Professor Sergey Levine on deep reinforcement learning/machine learning research. He also worked at Los Alamos National Laboratory with Dr. David Mascareñas on cyber-phsyical systems research.

Sudeep Dasari’s Thoughts on RoboNet

According to Sudeep, “this work takes the first step towards creating learned robotic agents that can operate in a wide range of environments and across different hardware. While our experiments primarily explore model-based reinforcement learning, we hope that RoboNet will inspire the broader robotics and reinforcement learning communities to investigate how to scale model-based or model-free RL algorithms to meet the complexity and diversity of the real world.”

He further added, “since the dataset is extensible, we encourage other researchers to contribute the data generated from their experiments back into RoboNet. After all, any data containing robot telemetry and video could be useful to someone else, so long as it contains the right documentation. In the long term, we believe this process will iteratively strengthen the dataset, and thus allow our algorithms that use it to achieve greater levels of generalization across tasks, environments, robots, and experimental set-ups.”

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