Enter ARM’s new “Autonomous Robot Challenge” and win cool stuff

ARM has just launched a new robotics competition on Hackster.io “The Autonomous Robot Challenge”. Registration is now open and entries will close on Sept 30 but if you get in early you might receive free hardware to help you build, like a DonkeyCar kit. The deadline to apply for free devices is July 21. Winners will be announced in October and prizes will be given for “Best Use of AI”, “Most Creative Project”, “Greatest Social Impact”, “Best DonkeyCar Project” and “Most Fun Social Media Video.” All the details are below.

Arm_logo_blue_150LG.png CONTEST BRIEF:

Join us in an exciting new challenge and build an autonomous machine to push the limits of what low-cost, open-source hardware and deep learning on the edge can do for humanity. We are excited by the potential of drones (flying, rolling and swimming) to help us in our daily lives, delivering food and medicines to those in need, helping in agriculture, responding to emergencies and much more. As a result, we want to see what you (our community) can dream up using advanced hardware kits, sensors, computer vision, and deep learning based on Arm technologies.

Hardware

In this contest, we want you to design the next innovative machine using your choice of some of Arm’s favourite technologies:

  • A drone, rover, underwater ROV or vehicle of your own making

Early applicants will be eligible to receive one of the 50 4-wheeled DonkeyCars Arm have provided Hackster.io which we will be distributing to developers who submit compelling proposals around how these small wheeled robots can be used for good. We are also inviting developers to use drones, rovers, robots, underwater ROVs of their own creation.

Your machine needs to be able to achieve at least one of the following tasks:

  • Autonomously transport a package in an urban, rural or underwater environment
  • Autonomously assist in a real-world scenario

Can you deliver medicine, food, aid to those in need? We imagine a world in which drones of various kinds will be assisting humans and help humanity address some of the world’s greatest challenges. What do you imagine? Bonus points will be given for real use cases in your local environment.

We are giving away thousands of dollars to ten lucky grand prize winners in the form of robots and other cool objects! Our judges at Arm are going to pick the ten best qualifying projects based on the judging criteria outlined in the rules section.

You also have a chance to win a GoPro HERO 6 if you post a fun and entertaining video on social media with the hashtag #ArmRobotChallenge!

We have a few bonus challenges (for bonus points during judging!) for you to consider:

AI on the Edge

  • Does your machine use the latest frameworks released by Arm to enable deep learning on Arm processors?
  • Does it make the best use of the MCUs on board? Is it capable to use the Cortex-M processors for inference?

Sustainability

  • Does your solution help people to live more healthy, sustainable and peaceful lives?
  • Solar Power/Charging does your robot take advantage of renewable energies. Does it park in the sun to recharge?
  • Does your solution help to conserve energy?

Mapping

  • Able to create a map of an unknown environment and use it to navigate?
  • Mapping disaster zones to help first aid / deliver supplies – maybe your DonkeyCar delivers emergency supplies, or your homemade robot maps lava flows to identify open escape routes?

What are the submission requirements? Your project should make use of autonomous vehicle or drone technology based on Arm and follow the theme of this contest (autonomous bots). Please allow at least one week for your submission to be moderated by our team.

Want help getting started? There are major communities in support of all the devices required for this contest. Example projects on getting started with a Raspberry Pi can be found here, and make sure to search Hackster’s project hub to find tutorials on more complicated topics (computer vision, deep machine learning,etc.). The DIY Robocars community has also created some great projects that you can access from here.

Want to get started with artificial intelligence on the edge?

  • Use the software development kit released by Arm. Arm NN bridges the gap between existing NN frameworks and the underlying IP. It enables efficient translation of existing neural network frameworks, such as TensorFlow and Caffe, allowing them to run efficiently – without modification – across Arm Cortex CPUs and Arm Mali GPUs.
  • Use Compute Library to develop AI applications on Cortex-A processors and GPUs, taking advantage of highly optimized libraries that will boost the performance of your robot.
  • Use the CMSIS-NN kernels or uTensor framework to implement inference on your Arm Cortex-M processors.

Want to submit as a team? Go for it! You’re welcome to divide and conquer with a team of up to 5 members. But remember, one prize per team.

The Arm team and other participants are accessible for help and questions as well via the contest discussion forum.

Good luck and happy building!

Call for entries – World Robot Summit 2018 – Japan

Entries are now open for the world’s newest robotics expo and competition, with prize money of around $1 million USD or more than $100 million yen. The World Robot Summit (WRS) 2018 will be held as a preliminary and qualifying event for the WRS 2020. The venue is the Tokyo Big Sight East Halls, over 5 days from Oct 17 to 21.

Japan has a reputation as one of the most advanced robotics nations to uphold, and the upcoming Tokyo 2020 Olympics will be shining the global spotlight on Japan. The WRS organizers, The Ministry of Economy, Trade and Industry (METI), and New Energy and Industrial Technology Development Organization (NEDO), hope to highlight the strength of Japan’s robotics and also create an opportunity to advance global robotics as a whole.

“METI and NEDO aim for a realization of a world where robots and humans successfully live and work together. Toward this realization, they will hold the World Robot Summit (WRS) 2018, an international robotics event that consists of a robot competition and a robot exhibition and aims to 1) bring together the most advanced robot technologies from around the world and accelerate robot R&D through competition, and 2) showcase actual cases where robots solve difficult challenges that arise, deepen people’s understanding of robots, and accelerate implementation of robots in society. “

Not only will top researchers come together for the 5 day period, to compete and to share knowledge, but the state of the art in many robotics areas will be on display, showcasing solutions to difficult problems and enhancing the perception and implementation of robotics in society.

Competition has always been a great driver of research development, from the Longitude prizes of 16th to 18th century and the Napoleonic era food preservation challenge of 1795, to today’s DARPA Challenges, X-Prizes and RoboCup. The World Robot Challenge (WRC) 2018 is the competition section of the WRS and will consist of 9 challenges in 4 categories; Industrial Robotics, Service Robotics, Disaster Robotics, and Junior.

Sponsors are providing prize money exceeding $100 million yen and travel expenses might be granted to some participating teams. For more information and application visit the WRS website. The closing date for registration is March 15, 2018.

The World Robot Expo (WRE) will run in conjunction with the WRC, during Japanese Robotic Week. With the involvement of school teams and the concomitant public and media interest in the competitions, the expo will also be very well attended.

What my Tech Startup Learned Delivering Aid in Puerto Rico

Contributor: Joel Ifill is the founder of DASH Systems. Drone enthusiast and package thrower. He resides in Los Angeles and may be reached by e-mail or twitter

 

Deliveries into Utudao October 2017

After landfall of Hurricane Maria I kept myself updated about the dire situation in Puerto Rico.A terrible story was unfolding: a growing humanitarian crisis marred by logistics challenges to an island with heavily damaged infrastructure. Rather than sitting there wishing we could help, we were poised to contribute. Our startup had been working in “stealth” on Direct Air SHipping technology. Simply put, we throw packages out of cargo airplanes and they land accurately at a designated location by use of a one-way low cost delivery “drone”. This is similar technology as military air drops, but with the intention of delivering packages commercially.

As the cogs start turning in your mind, you can see the applications for this technology. We can deliver anywhere a plane can over fly, we aren’t enslaved to airportswhich allows deliveries in remote and hard to reach areas. Puerto Rico was finding itself with a growing list of areas cut off, hospitals running out of fuel for generators and towns in need of water, food and basic supplies. The military and aid communities came together but the demand was much greater than any one organization’s ability to deliver.

We asked ourselves why couldn’t we use our air to ground delivery experience to deliver humanitarian aid to Puerto Rico? We had been proactively engaged with the FAA to perform civilian air drops in a legal and safe manner an issue that is plaguing many other “Drone delivery” technologies. With that question in hand I told my team that I would spend one hour until I was given a hard no, then two hours, then four hours, and next thing I was booking flights to Puerto Rico to setup air drops into Las Marias and Utuado. Two particularly hard hit mountainous districts southwest of San Juan.

A plane full of aid packages en route for delivery in Utuado. October 2017

Our deliveries were performed safely and successfully; this effort would not have been possible without a mountain of volunteers, aid partners and an air cargo company willing to trust us to convert their planes and supply amazingly pilots. However, this is not a story about congratulating ourselves on a job well done. Instead this is advice to technologists like myself looking to apply high tech solutions for high impact and complex problems.

Technology is amazing; from vaccines to the internet it has fundamentally transformed society and changed our lives. However technology in the land of lean startups and crowd funding is also finicky, expensive, slow to develop and many times ends up being a cool and exciting over engineered solution for a problem that doesn’t need technology to fix. Solutionism is an accusationoften levied at Silicon Valley. Christine Emba said it best,

Their CEO’s statement is a prime example of solipsism masquerading as benevolence, and a self-regard that makes it easy for those who think they have all the answers to avoid discussing actual problems and useful solutions.

Engineers and technologists (like myself) are often prone to seeking technical solutions to all problems. An app a day keeps the doctor away if you are involved in startups, are an inventor, or in the tech ecosphere. Below are some of my thoughts and lessons learned on evaluating technical solutions beforeyou hop on a flight and fly into an active crisis zone.

Know Your Technical Limits

…there are also unknown unknowns — the ones we don’t know we don’t know. And if one looks throughout the history of our country and other free countries, it is the latter category that tend to be the difficult ones. — Donald Rumsefield

Every technology has a technical limitation or trade-off; depending on a plurality of reasons these unknown unknowns may be more or less apparent. For example, I have this great idea for commuter a transportation technology: it is 100% legal and fits on today’s roads while taking less than 1/3rd the resources to manufacture as a passenger car. It can get up to 90 MPG and hold up to two commuters. I can make it with existing factories and manufacturing techniques for a few thousand dollars total shipped cost. If this technology sounds amazing, or too good to be true, I just described a motorcycle!

“Why don’t you ride one to work?”

Now, in your head you have a list of every reason why you never would ride a motorcycle for your daily commute. We went from an exciting list of quantified benefits with unknown unknown negatives, to known unknown negatives. These are all the negative assumptions, biases and justifications we have for never riding a motorcycle. Your technology has the same biases and negative assumptions but the more cutting edge and new it is, the more unknown unknowns you have not discovered.

Some of those known unknowns are addressable with more technical solutions($$) or behavioral solutions (wear a helmet and jacket). Whatever the solution, each brings a whole new set of assumptions and blind spots. The more unknown unknowns and the more behavioral changes you have to make the slower and more expensive adoption will be. You as an inventor may be comfortable riding a motorcycle in January, and are used to wearing a jacket, you’ve had a year to develop the motorcycle and love riding it. However it’s going to be difficult to push this change onto a public expecting the conveniences and comforts of a car, no matter the quantitative benefits in cost savings.
Lesson #1:

Substitutional Technologies require more education and awareness to overcome inherent biases in how we expect things should be done.

What We learned: We knew how to throw things out of airplanes in fact 100% of items have eventually landed on the ground. What is hard is anticipating all the customer concerns, demands, expectations and biases for what civilian air drops should be. In Puerto Rico how do you perform deliveries into areas with no power, no cell phones, no internet, no air traffic control, limited weather data, high winds, and land into places that take days to reach by Jeep? How do you do this all safely, and legally? We learned to appreciate and except corner cases and address concerns technically and procedurally before we ever planned to take off. In controlled environments on a sunny day with no wind it’s easy to line up a delivery. In the real world we have to be able to perform in any and all combinations of adverse conditions to areas we couldn’t control.

It is of dire importance to pessimistically understand all your corner cases and operating parameters for your technology. Too many technologies have a limited application when taken outside of a demonstration environment. If you find yourself or your team dismissing concerns easily, or getting defensive about tech questions. Stop. Write down the concerns and appoint and advocate for the question. My co-founder and CTO often plays devils advocate and makes us thoroughly address corner cases much earlier in product development than most projects, a technique that gives us more robust final products with fewer expensive revisions to come to the same conclusion after being forced to adopt the changes.

Test Soon, Test Often

It’s one thing to have a prototype and claim at a ground breaking technology. It’s another to have fielded a ground breaking technology. The difference is often millions of dollars and multiple years full of caveats, lessons learned and expensive mistakes.

For many technologists it’s easy to get excited about a cool technology (Drone delivery) then double down on the bet (VC Funding) generate a lot of buzz (literal and figurative), high fives and “why didn’t I think of that’s” before you’ve ever done a single delivery via drone. The sooner you test, and test in real world situations you don’t control. The sooner you find out the caveats that surround any particular technology. For drone delivery, just like any automation technology you are applying rigid machine thinking and engineering to a very fluid world full of 1 in a million corner cases. If amazon patents (with perhaps the best patent art of all time) are any indication these problems while seemingly insignificant are crucial barriers to success.

What We Learned: Test often, test soon and receive buy-in from stake holders (those who use your tech) and gate keepers (decision makers and regulators). Going to Puerto Rico was a continuation of this process. This was a very real mission with very real players. Aid organizations with life saving supplies expecting time sensitive deliveries and aviators expecting their planes and operating licenses to remain unharmed. We could not baby the environment or brush off paperwork, we had to have paperwork signed and submitted to the FAA to perform drops. Paperwork that takes time. Be realistic with the demands and concerns of market space you work in, the technology development was much easier than getting permissions to fly from the FAA or social buy-in to fly over your grumpy neighbor’s house.

First Do No Harm

Medicine has a hippocratic oath, but technologists are woefully lacking a similar creed. John Tapelin and the tech industry taught us to move fast and break things. While first mover status and natural barriers to entry may be great formula for a startup, overselling and launching technology that is not ready can harm your long term perspectives, or worse be the death of you and your business. For every new technology there are real risks and real consequences of failure, from patient and customer data inadvertently being released, to customer outages or stop-work events. Perhaps the single question I find so many technologists fail to ask is “What is the failure rate and modes and what are the consequences for failure” from minor inconveniences, to catastrophic disaster. Each technology has different failure modes that are rarely discussed openly by technologists. The more expensive or high risk the failure mode, the greater the benefit needs to be. Autonomous delivery is an amazing proposal, but will go down in flames faster than the Hindenburg if the public loses trust when an autonomous drone crashes into a daycare.

What We learned: Initially our biggest concern was safety during every step of the process for all players. This safety was addressed technically and with training and procedures before any package was dropped. The next question asked is what does failure mean if we couldn’t deliver at all? It’s one thing for your UPS package to arrive a day late, it’s another to tie up precious humanitarian resources in the middle of a natural disaster. Often it’s easy to oversell a technical solution, without regard to what failure or inability to perform means. We had to make sure we could guarantee a delivery before we took off as the cost of failing would have been wasted resources and a betrayal to the people on the ground. To help map out failures we used “Process Failure Modes Effects Analysis” or PFMEA a free tool that can be performed in excel. This technique to help inform engineering design decisions and what features need more time or more robust solutions.

People Pay for Solutions Not for Technology

Perhaps the most obvious and least obvious is that technology and fancy technology very rarely drives a purchasing decision, or won’t lead to long term adoption.

We pay for solutions to pain points. Instead of building a better mouse trap, ask the question what are the solutions people are willing to pay for having no mice in the house? When questions are framed around the pain point many solutions become available that are not always technical in nature. Having spent a career in engineering working in factories I’ve seen many factory modernization efforts fail as the underlying root cause was organizational or procedural rigor; hundreds of thousands into barcode scanners or RFID scanning systems won’t help if people aren’t rigorously maintaining inventory, and hardware won’t magically solve this problem if no one is held accountable for not using the system properly.

Often times technology is a solution, better than the gold standard, but the barriers to entry, development cost, and training and education make the calculus a losing formula over process and behavioral changes. Simply put, a new dewey decimal system won’t solve for people not putting library books away. If your taking credit for solving organizational or process pain problems be careful that adoption rate will be slow and results will be muddled if customers are unwilling to commit to process changes. Also be aware that process and behavioral changes are much harder to sell and may turn key stakeholders or advocates into barriers for success.

What We Learned: While we have exciting and interesting technology for delivering items from planes we found the single biggest pain point was customers who were intimidated or unfamiliar with coordinating air logistics. Overtime our pitch and branding changed from “drone delivery startup” to “enabling air cargo deliveries anywhere in the world”. While the underlying technology never changed and we still do perform civilian air drops the key pain point was smooth and fast coordination of deliveries in remote areas, not the specifics of how we performed the delivery.

Also we learned our ask was big for those who owned the airplanes we fly on, yes we make them a lot of money, but we are asking them to change the process of how they use multi-million dollar planes. We had to provide more training and education and evidence of success before they were willing to sign onto an operation that could risk their operating licenses.

As an end we learned customers don’t care if you package is delivered by drone, bike or airplane, they just want a package fast and safe at an acceptable price. Technology needed to be seamless part of the solution not a flashy showcase of what is possible to do with cutting edge engineering.

Closing Thoughts

Technology is the cornerstone of modern society and has fundamentally solved and changed the way we live. Problems that were once thought impossible are being solved and tackled with new tools. However awesome tech does not make a viable business or necessarily save the day. As a technologist it is easy to get excited about the possibilities of what you could do with a new invention and hard to face the realities of the barriers and feasibility of using that technology in the real world.

Optimism is an amazing human trait and as an entrepreneur or inventor you must be simultaneously optimistic and skeptical of your solutions. Before you hop on your plane to your disaster zone think critically and holistically about the non technical impacts your solution brings and the risks it exposes. Air to ground delivery has been technically possible to develop, getting acceptance of throwing life saving aid out of airplanes has been harder.

Joel Ifill is the founder of DASH Systems. Drone enthusiast and package thrower. He resides in Los Angeles and may be reached by e-mail or twitter

Catalia Health uses social robots for health

Catalia_Health-mabu-1Catalia Health is leading the surge in social robotics, with Mabu, their patient care management system. Catalia Health likes to be seen primarily as a health company that utilizes robots, rather than a robotics company. This focus on solving real world problems while shipping a product has seen Catalia attract both customers and investors, and recently close their Series A round.

Interview with Cory Kidd, Founder & CEO of Catalia Health (edited for clarity)

What is Catalia Health?

Catalia Health is a patient care management company. We focus on helping patients adhere to their treatment, whether that be taking medication, or managing chronic disease over the long term. That’s the focus of what we do, and part of how we deliver this to patients is through a cute little robot called Mabu who engages with patients through conversation. She’s a little over a foot tall, and can sit wherever you want to put her … on a countertop or bedside table … and she has big eyes that make eye contact with you while you’re talking to her. Conversations with her might last a minute or two, or maybe five or ten minutes; it really depends on the individual patient and what they want to talk about.

Mabu has a touch screen on the front that she can use to display information, but our overall focus is to create an engaging relationship between the technology and the patient. The reason that we use the robot — as opposed to just delivering this through a phone screen or a tablet or PC — is about psychology and not about technology. When we are in front of a robot that has eyes that can look at us and blink, we tend to be more engaged, and we find the robot to be more credible and informative than if the same information were delivered to us through an app. While we have a lot of healthcare applications that we’re looking to build, the core of this is really just basic psychology: how can we create engagement that lasts for a long time? Psychologists have studied the benefits of face-to-face communication for decades.

Is speech the primary interaction that people have with Mabu?

Our platform’s primary means of interaction is conversation, but this can happen in more than one way. For example, when Mabu is talking, she also displays what she is saying on her screen, to make it easy for anyone to understand what’s going on. And when I reply, I can speak back to her, or I can touch a button or location on the screen. And if I’m not at home, I can also get a reminder via text message … in the future this might happen through an app or other desktop interface.

The physical robot is the thing that’s creating the engagement — the relationship — but we can interact with people through other forms of technology as well.

Does the conversation with Mabu end at home? How is information transferred to the healthcare provider?

We do send information summaries back to health care providers — a pharmacist or physician or some other caregiver — but the overall problem we are trying to help with is that the healthcare system simply doesn’t have enough people to manage chronic disease at scale. So while our technology might also enable tele-operation or tele-presence, the focus of our business is to be able carry out an autonomous one-on-one interaction with patients in real time.

Is the patient, or end user, your customer?

Patients get a lot of benefit from our platform, but they are not the ones who are paying for it.

Our direct customers are pharmaceutical manufacturers and healthcare providers. They provide programs to help patients be more effective at taking their medications and managing their conditions, so in their eyes we are another tool in their arsenal.

Can you tell us about your first deployments?

The places where we are rolling out first are where there are existing care management programs already in place, and these tend to be in areas such as oncology and immunology where higher-end drugs are being used. Talking robots are very new and different, so we wanted our contract structure to look as similar as possible to existing offerings. These were the areas where there were already contract types that we could follow into market. We have been rolling out the first several hundred units in the first half of 2016 and are bringing patients onto the platform by the end of this year.

What is your business model? Is it “Robots as as Service”?

In terms of the patient relationship, our robot is key. But in terms of our business model and contracts, we don’t think of our robot as the key piece of what we’re delivering. We use a service model for care management; our customers pay us on a per patient per month basis.

What does interaction with your service look like from the patient’s perspective?

If you want to see what the patient interaction with Mabu actually looks like, we have a short video at cataliahealth.com.

Once the patient plugs Mabu in, the robot comes alive and starts talking. The conversation starts off with greetings and small talk (such as “Good morning, great to see you!”) and then moves on to whatever issue is relevant to the patient at that point in time. Maybe this is simply to check in on whether the patient has taken their medication, or maybe the patient is at a point in their treatment where it’s common to experience certain side effects, and the conversation is about how best to mitigate those for that patient. It really depends on the particular condition or treatment the patient is dealing with. We do a lot of research on each condition before rolling the platform out to patients, in order to build an understanding of common treatment challenges into the application.

In the background, the conversation is being crafted in real time for that patient.

When Mabu first comes out of the box, we know a little about the patient’s medical condition — perhaps what drugs they are on — but we don’t know much else. So from that very first conversation we start learning about and adapting to the patient’s individual personality and the treatment issues they are facing. Mabu largely directs the conversations, but the patient has a lot of say in terms of where that conversation goes. As we build more conversations and more AI into the platform, we are able to craft appropriate conversations for the patient.

This will very quickly become applicable to a lot more drugs and a lot more disease states. Let’s look at side effects, for example. Our first conversations about side effects will be new, but there are many common side effects among drugs. So while we are starting out in just a handful of areas, our goal is to help any patient who’s dealing with a condition on an ongoing basis to better manage their care, and to provide information back to their caregivers so that they can be more effective in supporting them.

Is it valid to be concerned about robots being used to replace human companionship?

We certainly don’t think of this as robots replacing people; we think of it as robots augmenting people.

One of the big challenges in healthcare today is that there are not enough caregivers to deliver healthcare the way we need it. Almost half our population is managing a chronic disease in this country, and there are very similar rates in advanced nations around the world; if we look at the rate of people dealing with health issues on an ongoing basis, it approaches 2/3 to 3/4 of the population.

People might get to see their doctor for fifteen minutes every two months, but that’s not much time, and it’s not an effective way to provide the ongoing care that is needed. We simply don’t have enough people to manage healthcare the way we did 50 or 100 years ago.

Patients need reminders, and they need answers to all the little questions that come up — and that’s where technology like this comes in. We see our service as a way for the people who are providing health care — doctors, nurses, and other trained caregivers — to more effectively reach a larger group of patients. We are not trying to be people’s doctors, we are trying to help their doctor do a much more effective job.

What kind of feedback have you received so far?

Broadly speaking, the feedback has been very positive. People tend to like the interaction right from the very first conversation, and they like how Mabu adapts to them.

We have a great solution that we’ve shown can effectively help many patients, but we still have a lot to to learn. We are really excited about the amount of data that we’re going to be getting back from hundreds of person-months of interaction with our platform this year, and how we’re going to use that to improve conversations and personalize them to every patient.

Thanks to social platforms like Siri, Jibo and Amazon’s Echo, we are starting to get used to having conversations with our devices. But you’ve taken a very specialized path into the market. Why did you pick this pathway and business model?

Scalability — being able to provide care to a growing number of patients — is a big challenge in health care. I spent about a year before launching Catalia Health really digging into the US healthcare market to explore the business opportunities. We were thinking broadly around medication adherence and chronic disease management, talking to potential customers and trying to understand where there was a need for this kind of technology. The quick answer was that it is needed pretty much everywhere within the healthcare system. The question of how to provide healthcare in a cost-effective and scalable way is definitely a challenge here in the US, and also in most other nations in the world. We see an enormous opportunity for using technology to provide scalable personalized care.

Of all the robotics and AI movies that have come out in the past five or ten years, Robot and Frank offers a vision comes closest to what we’re doing. The goal of the robot in that movie was to help Frank live healthier by building a relationship with him. We have the same underlying premise in what we’re doing: our technology is focused on building a relationship with the patient, because once we can do that, then we can talk to them about their health care. By comparison, usage rates on healthcare apps are incredibly low; most patients don’t pick them up after the first or second try. But as it turns out, there are particular psychological aspects of how people interact with robots that make them really effective at helping to solve this challenge.

Do you see ways that other robotics companies can leverage what you’ve learned so far?

The broad lesson is to understand where there is a real human or business need. Asking “Where is there a problem that I can solve?” rather than asking “Where can I build a robot?” or “What market can I serve?”

It’s also important to understand what the existing marketplace looks like for those kinds of solutions right now, because the solution today may look very different. Our robot is an alternative to talking to a pharmacist on the phone, and it’s a very different solution, but understanding what the business model is for that kind of service, how those contracts work, who the players are in the space — I think that’s something that any company would be smart to take a look at and understand deeply before trying to compete in those markets.

You’re tackling one of the largest growing areas of our economy, and you’re doing it with a combination of data, AI and robotics. What do you think has changed in the past couple of years to make robotics a viable solution to a broader range of applications?

One of the biggest changes has been in the cost of building both hardware and software. Our robot is pretty simple; we’re not doing anything cutting edge in terms of the physical device that we’re building. But ten years ago producing our device might have cost 100 times what it does today, and that would have limited us to a small set of business models and it would have been very hard to make money.

With the cost of building the technology drastically lowered, it has enabled us to do something very different today than what we could have done five years ago. Today we can build cutting edge technology at a reasonable price point and therefore deliver a cost effective solution.

CATALIA HEALTH

Catalia Health is a patient health management system using social robotics. Founded in 2013 by Dr. Cory Kidd, Catalia Health builds on years of research into Human-Robot Interaction starting at MIT’s Media Lab and continuing with social robot startups like Intuitive Automata. In June 2015, Khosla Ventures led a $1.25 million seed round in Catalia Health for the first trial customer engagements. Catalia Health is on a mission to address both sides of the healthcare equation: improving patients’ health and extending the capabilities and efficiency of healthcare companies.

SILICON VALLEY ROBOTICS

Silicon Valley Robotics is the industry group for robotics and AI companies in the Greater San Francisco Bay Area, and is a not- for-profit (501c6) that supports innovation and commercialization of robotics technologies. We host the Silicon Valley Robot Block Party, networking events, investor forums, a directory, and a jobs board, and we provide additional services and information for members, such as these reports.

WE’LL BE RELEASING ADDITIONAL ESSAYS FROM THE REPORTS EVERY WEEK OR SO. OR READ FULL REPORTS AT https://svrobo.org/reports

Robotics has its first unicorn – small SF startup Cruise Automation

GM-and-Cruise-930x620Forget about Google and Boston Dynamics. This week the real news is that GM acquired small San Francisco based startup Cruise Automation for a rumored “north of $1 billion”, according to Fortune. Robotics has its first unicorn!

For the last 3 years, Cruise Automation has been working on an ‘after market’ kit to make vehicles self driving. Cruise have previously raised over $18 million in venture funding, on a post-money $90 million valuation. Investors include YCombinator, Spark Capital, Maven Ventures and Founder Collective.

Apparently Cruise was in discussion with GM about their next venture round which turned into an acquisition. It would seem that GM is interested less in the after market kit and more in integrating the Cruise team into GM’s core technology development.

According to the press release, Cruise will operate as an independent unit within GM’s recently formed Autonomous Vehicle Development Team led by Doug Parks, GM vice president of autonomous technology and vehicle execution, and will continue to be based in San Francisco, where Cruise has been testing its technology in a challenging city environment.

“Cruise provides our company with a unique technology advantage that is unmatched in our industry. We intend to invest significantly to further grow the talent base and capabilities already established by the Cruise team.” said Mark Reuss, GM executive vice president, Global Product Development, Purchasing and Supply Chain.

“GM’s commitment to autonomous vehicles is inspiring, deliberate, and completely in line with our vision to make transportation safer and more accessible,” said Kyle Vogt, founder of Cruise Automation. “We are excited to be partnering with GM and believe this is a ground-breaking and necessary step toward rapidly commercializing autonomous vehicle technology.”

So the acquisition of Cruise is GM’s latest step toward its goal of “redefining the future of personal mobility”. Since the beginning of the year, GM has entered into a strategic alliance with ride-sharing company Lyft; formed Maven, its personal mobility brand for car-sharing fleets in many U.S. cities, and established a separate unit for autonomous vehicle development.

But really the exciting thing for everyone else is that robotics has finally reached the tipping point. In 2014, Silicon Valley Robotics announced that over $1 billion had been invested in robotics in the last 5 years, 2009 to 2014. In 2015, over $1 billion was invested in robotics in a 12 month period, according to Hizook. And in 2016, over $1 billion has just been invested in one single small robotics startup, Cruise Automation.

Robotics has its first real unicorn, joining our lonely decacorn! Because to be fair, Intuitive Surgical founded in 1995 and IPOd in 2000 for a market valuation of $21.5 billion.

Siemens funds new Industrial Robotics Award in Robot Launch startup competition

 

Siemns_Frontier

Siemens has joined the Robot Launch as a sponsor, offering an impressive “Industrial Robotics Award” consisting of access to the Siemens Frontier Partner program, which provides mentorship and industry leading commercial software. It’s hard to put a dollar value on such a big award because the startup will receive access to a wide range of products and services, but this easily brings the total value of prizes offered to over $100,000, including $5,000 cash or travel prize for Grand Winner. [tweetquote]There are still two days to enter Robot Launch – Don’t miss the July 12 deadline![/tweetquote]

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