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ILP Institute Insider

June 20, 2016
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Making the Sky Safe with Laser Radar

Drones have the potential to transform anything from wedding photography to merchandise delivery. There’s one snag. A sky full of autonomous aerial vehicles would be chaotic, and wouldn’t be accepted by the general public if aircraft were regularly colliding with objects and each other. What’s needed is accurate positioning information and a detailed air traffic monitoring system.
Dale Fried
Founder & CEO
3DEO
This is where 3DEO comes in. The MIT startup is taking 3D imaging technology, originally developed for the military, and applying it to the detection and tracking of small drones anywhere from highly-complex urban areas to sports venues to airports. Additionally, 3DEO is developing compact 3D imaging systems to fly on drones for land surveying, law enforcement, risk assessment, and humanitarian relief possibilities. Until now, such uses have been limited because the technology has been big and expensive. “What we’re talking about here is a way to change that paradigm,” says Dale Fried, 3DEO founder and CEO.

The roots and early uses
Started in 2014, 3DEO spun out of MIT’s Lincoln Laboratory, where Fried worked for 10 years. As part of its partnership with the Department of Defense, the lab developed lidar technology that can rapidly collect 3D images from far distances. While speed is critical for military applications, “time is also money in the commercial market,” Fried says. His goal is to take that defense-related work and bring it to a wider set of users.

At its core, 3DEO’s technology probes distant objects with a short laser pulse and measures the time delay until reflected light returns to the sensor. Instead of the single photo-detector employed in most laser radars, the company’s technology uses an array of tiny detectors placed at the focus of an imaging system, each capable of identifying photons one at a time, Fried says.

With only 5-10 photons needed to reliably make a measurement, the simplest 3DEO sensors can collect 3D maps at more than 300 square kilometers (115 square miles) per hour and at 10 cm (4 inch) 3D resolution – New York City’s Central Park could be surveyed in less than one minute, he says. Alternatively, as a means to spot and track rogue drones in sensitive airspace, 3DEO systems can monitor a 40-degree by 360-degree volume of airspace once per second and pinpoint small drones out to 1 km.

At Lincoln Lab, while the airborne 3D mapping technology was being developed under military funding, Fried says that it was also used for humanitarian relief efforts. In 2010, after the Haiti earthquake, daily missions were flown around Port-au-Prince imaging refugee camps. The results estimated how the volume of tents, and therefore the population, changed daily and directed where aide should be delivered. Additionally, the 3D terrain maps could predict which camps would be vulnerable to flooding during the impending rainy season.

Currently, Fried is working on miniaturizing the sensor technology. As a starting point, there’s ALIRT, a research and development prototype system that mapped about 400,000 square kilometers to sub-meter accuracy in Afghanistan between 2010 and 2014. It was large and heavy, enough to load up a small business jet, Fried says. He wants to shrink that to below the size of a soccer ball, transforming it to something that can work on a drone, vehicle, or boat. “By making it smaller, more applications can benefit from the technology, and the increased manufacturing volume will further drive down costs,” he says.

Out in the public sphere
As Fried says, the ability to take quick, detailed images from long range benefits many sectors. In something like land surveying, especially flood plain mapping, governments can accurately predict where water goes when rivers and oceans rise and what areas are most vulnerable. Insurance companies could use the information to determine more accurate rates, based on the likelihood of a claim.

In responding to disasters, the technology could rapidly assess a damaged area and know what roads are serviceable. All of these applications are available now, but only in a limited scope because of the current expense. The 3D imagery simplifies automation because the computer starts with a geometric description of the scene; using industry-standard camera imagery, the computer has to infer it, which is slow and error-prone, says Fried, adding, “This difference allows us to collect these kinds of measurements affordably and make these kinds of maps at scale.”

The same laser radar technology that is being miniaturized to fit on a drone can also be applied to make drones themselves safer. Avoiding collisions requires a geometric (3D) understanding of a vehicle’s surroundings and how far away other objects are. 3DEO’s lidar can perform detailed sweeps of a 270-degree by 40-degree area, out to 1 kilometer, and do it all in a package smaller than that soccer ball, he says.

It’s providing this kind of air traffic safety and the ability to detect and track UAVs that is fundamental. “First and foremost, people need to feel comfortable with drones flying overhead, and, to have that, law enforcement needs the tools to spot drone incursions. These laser radars do just that,” Fried says.

However it’s employed, the technology’s essential element is fast, accurate detection. With lidar, there is no background noise or clutter in the empty spaces through which drones fly; faint signals from small drones can therefore be spotted and the drone can be tracked in 3D. “False alarm rates are dramatically lower than non-lidar-based technologies, leading to systems that are much more sensitive and reliable than what is currently on the market,” Fried says.

And then there’s what can’t be foreseen in the lab. For example, Fried says that an MIT urban planning postdoctoral scientist wanted to understand the historical timeframe of buildings, hoping to predict earthquake susceptibility, based on safety codes in place at the various stages of construction. Lidar 3D images provide geometric shape information that helps infer the ages of the different sections. Once validated, the approach could allow urban planners to assess earthquake vulnerability of entire urban areas. It’s not something that Fried says that he could have imagined, “but available, detailed 3D data enables the application.”

Having an MIT foundation
3DEO has deep MIT roots beyond the Lincoln Lab connection. Fried received his Ph.D. in physics from the Institute and landed his first job with another MIT startup. He has built up his contacts over the years and is located in the Cambridge-Boston ecosystem. But, as he says, the advantage of an MIT company is more than geography. It’s about the guidance that comes from something like the MIT Venture Mentoring Service.

As he transitioned from Lincoln Lab, Fried says that he wasn’t sure about how to exactly start a company, and the VMS was critically helpful. Using its specialized advisers, along with his long-term confidants, he could figure out strategy questions, such as how to work successfully with co-founders and what type of funding to pursue.

Those same contacts will continue to play a role as 3DEO grows and takes on employees. Early hires will be key; they won’t only need the skill set but also the necessary attitude, motivation, and chemistry. More than just providing a labor pool, the MIT connections will act as a vetting process. “It’s a great advantage to the company to be able to get the right person at the right time who can jump in with both feet and thrive in our culture,” Fried says.


MIT Startup Exchange (STEX) is an initiative of MIT’s Industrial Liaison Program (ILP) that seeks to connect ILP member companies with MIT-connected startups. Visit the STEX website and log in to learn more about 3DEO and other startups on STEX.

Research News

June 20, 2016

Parallel programming made easy

Computer chips have stopped getting faster. For the past 10 years, chips’ performance improvements have come from the addition of processing units known as cores.

In theory, a program on a 64-core machine would be 64 times as fast as it would be on a single-core machine. But it rarely works out that way. Most computer programs are sequential, and splitting them up so that chunks of them can run in parallel causes all kinds of complications.

In the May/June issue of the Institute of Electrical and Electronics Engineers’ journal Micro, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) will present a new chip design they call Swarm, which should make parallel programs not only much more efficient but easier to write, too.

MIT Sloan
Management Review

June 20, 2016

Data and Devices Bringing Transparency to Energy Use

As vice president of engineering for the energy management company EnerNOC, Hugh Scandrett is deep in the trenches of bringing energy management applications for the smart grid to a wide variety of companies — utilities as well as commercial, institutional, and industrial customers.

Scandrett joined the Boston-based company in 2011, and as head of engineering he leads the company’s software development, engineering, quality assurance, and R&D teams. EnerNOC supplies guaranteed electrical capacity to commercial end-users, utilities, and wholesale energy suppliers, and accompanies that capacity with energy intelligence software. It helps companies gure out how they buy energy, when they’re seeing the highest demand, and how to optimize their usage.

In a conversation with Sam Ransbotham, an associate professor of information systems at the Carroll School of Management at Boston College and the MIT Sloan Management Review guest editor for the Data and Analytics Big Idea Initiative, Scandrett says that being able to predict energy usage is key to saving money, and explains why turning on the AC at 7:00 a.m. on a hot day can be more e cient than waiting until 8:00 a.m.