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Advancements in Human-Robot-Computer Research



Advancements in Human-Robot-Computer Research

The automated experimental facility, called the Intelligent Towing Tank (ITT), conducted around 100,000 total experiments in its first year of operation. What would normally take a PhD student to complete within five years of experiments, the ITT was able to do within weeks. The development of the ITT in the MIT Sea Grant Hydrodynamics Laboratory takes us further into the area of human-robot-computer research. 

The ITT automatically and adaptively performs, analyzes, and designs experiments. The experiments are focused on exploring vortex-induced vibrations (VIVs). VIVs are important for engineering offshore ocean structures such as marine drilling risers, which are responsible for connecting underwater oil wells to the surface. With VIVs, there are a high number of parameters involved.

The ITT is guided by active learning, and it conducts a series of experiments. Within the experiments, the parameters for each next experiment are selected by a computer. The system uses an “explore-and-exploit” methodology, which helps greatly reduce the number of experiments required for mapping and exploring the complex aspects of VIVs.

PhD candidate Dixia Fan began the project while searching for a way to reduce the thousand or so experiments that needed to be conducted by hand. That led to the development of the ITT system. 

A paper was published last month in the journal Science Robotics. 

Fan is now a postdoc, and the project was worked on by a team of researchers from the MIT Sea Grant College Program and MIT’s Department of Mechanical Engineering, École Normale Supérieure de Rennes, and Brown University. The new project showcases the type of cooperation that can take place between humans, computers, and robots in order to make scientific discoveries at a faster pace.

The ITT is a 33-foot tank, and it works without interruption or suspension. The researchers would like to see the system used in a variety of different disciplines, which could lead to the creation of new models in nonlinear systems. 

The ITT allowed Fan and his collaborators to explore a wider parametric space. “If we performed traditional techniques on the problem we study, it would take 950 years to finish the experiment,” he explained. 

In order to shorten the long time it would take for the experiment, Fan and the team integrated a Gaussian process regression learning algorithm into the ITT. By doing this, the researchers were able to reduce the amount of experiments needed, down to a few thousand. 

The robotic system is capable of automatically conducting an initial sequence of experiments. It then takes partial control over the parameters of the next experiment. 

Fan was awarded an MIT Mechanical Engineering de Florez Award for “Outstanding Ingenuity and Creative Judgement” in the development of the ITT. 

According to Michael Triantafyllou, Henry L. and Grace Doherty Professor in Ocean Science and Engineering, and also Fan’s doctoral advisor, “Dixia’s design of the Intelligent Towing Tank is an outstanding example of using novel methods to reinvigorate mature fields.”

Triantafyllou was a co-author on the paper and the director of the MIT Sea Grant College Program. 

“MIT Sea Grant has committed resources and funded projects using deep-learning methods in ocean-related problems for several years that are already paying off,” he said.

MIT is funded by the National Oceanic and Atmospheric Administration and administered by the National Sea Grant Program. It is a federal-institute partnership that combines research and engineering at MIT to help tackle ocean-related issues, 

Other contributors to the paper include George Karniadakis from Brown University, affiliated with MIT Sea Grant; Gurvan Jodin from ENS Rennes; MIT PhD candidate in mechanical engineering Yu Ma; and Thomas Consi, Luca Bonfiglio, and Lily Keyes from MIT Sea Grant.


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Autonomous Vehicles

William Santana Li, CEO of Knightscope – Interview Series




William Santana Li, CEO of Knightscope - Interview Series

Knightscope is a leader in developing autonomous security capabilities with a vision to one day be able to predict and prevent crime disrupting the $500 billion security industry. The technology is a profound combination of self-driving technology, robotics and artificial intelligence.

William Santana Li,  is the Chairman and CEO of  Knightscope. He is also a seasoned entrepreneur, intrapreneur and former corporate executive at Ford Motor Company. He is also the Founder and COO of GreenLeaf, which became the world’s 2nd largest automotive recycler.

Knightscope was launched in 2013 which was very forward thinking for the time. What was the inspiration behind launching this company?

A professional and a personal motivation.  The professional answer is as a former automotive executive, I believe deeply that autonomous self-driving technology is going to turn the world upside down – but just not in agreement on how to commercialize the technology.  Over $80 billion has been invested autonomous technology with something like 200 companies on it – for years.  Yet, no one has shipped anything commercially viable.  I believe Knightscope is literally the only company in the world operating fully autonomous 24/7/365 across an entire country, without human intervention, generating real revenue, with real clients, in the real world.  Our crawl, walk, run approach is likely more suitable for this extremely complicated and execution intensive technology.  My personal motivation: someone hit my town on 9/11 and I’m still furious – and I am dedicating the rest of my life to better securing our country.  You can learn more about why we built Knightscope here.


Knightscope offers clients a Machine-as-a-Service (MaaS) subscription which aggregates data from the robots, analyzes it for anything out of the ordinary and serves that information to clients. What type of data is being collected?

Today we can read 1,200 license plates per minute, can detect a person, run a thermal scan, check for rogue mobile devices….it is over 90 terabytes of data a year that no human could ever process.  So our clients utilize our state-of-the-art browser-based user interface to interact with the machines.  You can get a glimpse of it here – we call the KSOC (Knightscope Security Operations Center).  In the future, our desire is to have the machines be able to ‘see, feel, hear and smell’ and do 100 times more than a human could ever do – giving law enforcement and security professionals ‘superpowers’ – so they can do their jobs much more effectively.


K1 is a stationary machine which is ideal for entry and exit points. What are the capabilities that are offered with this machine?

Yes, the K1 operates primarily at ingress/egress points for either humans and/or vehicles.  All our machines have the same suite of technologies – but at this time the K1 does have facial recognition capabilities which has proven to be quite useful in securing a location.

William Santana Li, CEO of Knightscope - Interview Series

The K3 is an indoor autonomous robot, and the K5 is an outdoor autonomous robot, both capable of autonomous recharging and of having conversations with humans. What else can you tell us about these robots, and is there anything else that differentiates the two robots from each other?

The K3 is the smaller version capable of handling much smaller and dynamic indoor environments.

William Santana Li, CEO of Knightscope - Interview Series

Obviously the K5 is weatherproof and can even go up ramps for vehicles – one of our clients is a 9-story parking structure – and the robot patrols autonomously on multiple levels on its own, which is a bit of a technical feat.

William Santana Li, CEO of Knightscope - Interview Series


Your robots have been tested in multiple settings including shopping malls and parking lots. What are some other settings or use cases which are ideal for these robots?

Basically, anywhere outdoors or indoors you may see a security guard.  Commercial real estate, corporate campuses, retail, warehouses, manufacturing plants, healthcare, stadiums, airports, rail stations, parks, data centers – the list is massive.  Usually we do well when the client has a genuine crime problem and/or budget challenges.


Could you share with us some of the noteworthy clients which are currently using the robots in a commercial setting?

Ten of the Fortune 1000 major corporations are clients, Samsung, Westfield Malls, Sacramento Kings, City of Hayward, City of Huntington Park, Citizens Bank, XPO Logistics, Faurecia, Dignity Health, Houston Methodist Hospital – are just a few that come to mind.   We operate across 4 time zones in the U.S. only.  Can check them out on our homepage at


The K7 is Multi-Terrain Autonomous robot which is currently under development. The pictures of this robot look very impressive. What can you tell us about the future capabilities of the K7?

The K7 is technically challenging but is intended to handle much more difficult terrain and much larger environments – with gravel, dirt, sand, grass, etc.  It is the size of a small car.

William Santana Li, CEO of Knightscope - Interview Series


Knightscope is currently fundraising on StartEngine. What are the investment terms for investors?

We are celebrating our 7th anniversary and have raised over $40 million since inception to build all this technology from scratch. We design, engineer, build, deploy and support it.  Made in the USA – and we are backed by over 7,000 investors and 4 major corporations and you learn about our investor base here.  We are now raising $50 million in growth capital to scale the Company up to profitability – we can accept accredited and unaccredited investors as well as domestic and international investors from $1,000 to $10M completely online.  You can learn more about the terms and buy shares here:


Is there anything else that you would like to share about Knightscope?

As I write this response, we are in complete lockdown in Silicon Valley due to the global pandemic.  The crazy thing is that our clients are ‘essential services’ (law enforcement agencies, hospitals, security teams) so we must continue to operate 24/7/365.  You can read more about why I think you should consider investing in Knightscope here – but these days the important thing to remember is that robots are immune!

Thank you for sharing information about your amazing startup. Readers who wish to learn more may visit Knightscope or the StartEngine investment page.

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Chadwick Xu, Co-Founder & CEO of Shenzhen Valley Ventures – Interview Series




Chadwick Xu, Co-Founder & CEO of Shenzhen Valley Ventures - Interview Series

Chadwick Xu, is the Co-Founder & CEO of Shenzhen Valley Ventures, a hardware-focused company for engineers, by engineers. They partner with startups to prototype, design for manufacturing, test, debug, and manufacture their hardware products.

When did you first want to become an entrepreneur?

From day one when I first came to Shenzhen in 1992, and this is the very reason I came to the city. The path I followed is similar to many other young graduates (at that time), working for a corporate to learn, accumulate expertise, and build connections, then they start their own business.


You founded Zowee Technology in 2004 which was officially listed on the Shenzhen Stock Exchange in 2010. Could you give us some details on what Zowee is and the journey you had creating such a successful company?

The founders of Zowee knew each other by doing business, each partner had their own business before Zowee was founded. The idea is that, instead of having many small businesses, it made more sense to combine the small businesses together and build a bigger company, hence Zowee was born.

Zowee was positioned as a contract manufacturer, and it has remained to be so till today. Besides the effort we put into it, I think the major driving power of its success is the overall economic environment. The 1990s and 2000s was the golden era for Chinese to enter into private businesses. China’s opening up policy and the strong global demand created an ideal opportunity.


Shenzhen Valley Ventures (SVV) is your newest venture. What was the inspiration behind this business?

The success of Zowee represents the opportunity of “Made in China”, but in the future, the big opportunity is not in manufacturing, it’s in technology. What Zowee took advantage of was the labor bonus China had, and what SVV is trying to take advantage of is the engineering bonus China now has today. China is still falling behind on research, but China has the most engineering talent (globally). If SVV can put together a mechanism, enabling the best engineering resources to support the advanced research, so that research could be commercialized faster, it will be a mutually beneficial business structure.

Furthermore, China is becoming the largest single market, both in B2C and B2B business, if SVV’s engineering platform could help international deep-tech startups enter the Chinese market more efficiently, that will be another bonus.


What are some of the more interesting companies that are using SVV’s batch manufacturing services?

There are three groups of projects that have been using SVV’s small-batch manufacturing services:

  1. Startups: Generally, there is a long growing curve for startup companies to reach the volume that a contract manufacturer is willing to take. SVV has been helping startups when they are still very small and in the early stages of their delivery. This group is the group SVV has been supporting the most. e.g., Neosensory Buzz, a wearable device maker that helps people suffering from hearing or visual problems can now “hear” environmental noises with their skin, and eventually improve their living quality. Sutro, a water quality monitoring device that allows users to access their pool water quality data 24/7, streaming wireless to their cellphone.


  1. Corporate innovation projects: These projects are identified as “testing the water” projects in a corporate, it may or may not convert into a commercial project, depending on how the testing goes. e.g., an IoT box B/S/H tested to convert non-connected home appliances into connected smart appliances, or the air quality data monitoring device MANN+HUMMEL plans to embed into their existing air filters.


  1. Universities and institutional research projects: Some researchers need to have physical devices built and deployed to validate or prove the research they made, e.g., an earthquake forecast system/algorithm Beijing university have been researching, SVV helped them to design and build several hundreds of units, these testing units have been deployed nation wide in China, helping researchers collect huge amounts of valuable data for their studies. From 2019, international institutes joined in the study program, and more units are being deployed in Taiwan, Japan, Pakistan, India, and other countries.


SVV enables companies to use their services to prototype products before full scale production launches. Could you elaborate on why SVV is a good partner for prototyping versus other competitors?

SVV is not only a prototyping service provider, instead, it’s a full-cycle development platform provider, including prototyping, engineering, development, testing, certification pre-scanning, pilot production validation, and commercial-ready small-scale production.

This full cycle platform is usually owned by large-scale manufacturers, for the business of large-scale orders from large brands. A innovation dedicated full-cycle platform is a scarce resource, not only for startups, but also for corporations “testing the water” innovation projects.


Can you discuss how SVV is using computer vision to guide manufacturing robots towards better assembly?

SVV is not deploying computer vision guided robotics on its own production lines since SVV’s facilities are used only for small-scale production and for less mature products, the products of such products are more efficient with using manual assembly, since robots are more efficient in producing higher volume and mature designed products. However, SVV has been supporting computer vision guided robotic startups throughout their development.


At a recent Web Summit panel, you discussed how robots will soon be taking over manufacturing from humans, due to how precise robots are. How long until humans are completely removed from the assembly process?

It’s difficult to predict a precise point in time, but it may come much faster than most people think, and it will come gradually, the more standardized the assembly process becomes, the earlier it will be replaced by robots, and gradually will get to the level of fully automated processes.

Just as shown in “American Factory”, there will be a longer period to have robots and humans working together, with the trend of more and more humans replaced by robots, if you stay in a factory for a long period, this replacement process is quite visible.


What are your views on the current AI rivalry between the United States and China?

Competition is always good for the economy and technology, and in almost every competition scenario, the output is not like boxing, with the end result as a lose or win, instead, it often ends up as a symbiotic relationship, each party ends up with its own differentiated advantage.

The past several decades has been the history that China gradually catches up from low-end to middle-end innovation, in areas such as, telecommunications, to directly compete with the US, but the US still takes the leading position in most areas. In the 1800’ and 1900’, US and EU worked very hard, just like the Chinese are doing now, but the wealth and technology advantage somehow created a lay back, welfare dependent society. In many cases, China’s catching up serves as a power to push the US and EU out of their comfort zones and drive them to be more innovative to keep the leading position.


Is there anything else that you would like to share about SVV?

I have been reiterating my opinion on jobs being taken by robots, most discussions are highlighting the bad side, taking jobs from people, increasing the joblessness percentage, creating severe social problems. But on the good side, imagine if smarter machines were built, to improve production efficiency unlimitedly high, constantly growing until the machines can produce an abundance of materials for everyone on this planet, that is supposed to be the bright ending for the AI revolution.

This is almost exactly what Karl Marx describes as the ideal world, “From each according to his ability, to each according to his need”. Or, a perfect utopian society. For the first time in human history we have the opportunity to witness the elimination of hunger entirely from Earth.

We are excited that SVV is a part of this new AI revolution, to help more creative ideas become reality. Drops of water can eventually become flowing rivers, the idea of participating and being witness to this new history is hugely rewarding for us.

Thank you for this great discussion on robotics. To learn more readers may visit Shenzhen Valley Ventures.

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AI Makes it Easier for Drones to Scan and Excavate Terrain



AI Makes it Easier for Drones to Scan and Excavate Terrain

Researchers from Aarhus University (AU) and the Technical University of Denmark (DTU) have collaborated on a project that aims to decrease the costs of measuring and documenting gravel and limestone quarries, while at the same time being faster and easier than the traditional method. 

The project included the use of artificial intelligence (AI), which took over the traditionally human-controlled drones that are currently relied on to complete the task. 

Erdal Kayacan is an associate professor and expert in artificial intelligence and drones at the Department of Engineering at Aarhus University. 

“We’ve made the entire process completely automatic. We tell the drone where to start, and the width of the wall or rock face we want to photograph, and then it flies zig-zag all the way along and lands automatically,” says Kayacan.

Limitations of Human-Controlled Drones

The current method of measuring and documenting gravel and limestone quarries, cliff faces, and other natural and human-made formations relies on drones to photograph the area. A computer then receives the recordings and automatically converts everything and creates a 3D terrain model.

One of the downsides of this method is that drone pilots cost a lot, and the measurements are time-consuming. In an excavation, the drone pilot has to make sure that the drone keeps a constant distance from the wall. At the same time, the drone camera has to be kept perpendicular to the wall, making it a complex and difficult task. 

In order for the computer to convert and create a 3D figure out of the images, there has to be a specific overlap in the images. This is the main process that was automated by artificial intelligence, and it drastically reduced the complexity of completing the task. 

“Our algorithm ensures that the drone always keeps the same distance to the wall and that the camera constantly repositions itself perpendicular to the wall. At the same time, our algorithm predicts the wind forces acting on the drone body,” says Kayacan.

AI Overcomes Wind Problem

The artificial intelligence also helps overcome the wind, which is one of the biggest challenges with autonomous drone flight. 

Mohit Mehndiratta is a visiting Ph.D. student in the Department of Engineering at Aarhus University.

“The designed Gaussian process model also predicts the wind to be encountered in the near future. This implies that the drone can get ready and take the corrective actions beforehand,” says Mehndiratta.

When a human-controlled drone is completing this task, even a light breeze can alter the course of it. With the new technology, wind gusts and the overall wind speed can be accounted for. 

“The drone doesn’t actually measure the wind, it estimates the wind on the basis of input it receives as it moves. This means that the drone responds to the force of the wind, just like when we human beings correct our movements when we are exposed to a strong wind,” says Kayacan.

The research was completed in collaboration with the Danish Hydrocarbon Research and Technology Centre at DTU, and the results of the project will be presented in May 2020 at the European Control Conference. 


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