Hello,

We noticed you're browsing in private or incognito mode.

To continue reading this article, please exit incognito mode or log in.

Not an Insider? Subscribe now for unlimited access to online articles.

Intelligent Machines

Robotic Weather Planes

Fleets of robotic aircraft could improve weather forecasts.

Weather forecasters may not have the best reputation for accuracy, but with today’s computational modeling, it’s possible to make pretty reliable weather predictions up to 48 hours in advance. Researchers at MIT, however, believe that autonomous aircraft running smart storm-chasing algorithms could get that figure up to four days. Better weather forecasting could help farmers and transportation authorities with planning and even save lives by providing earlier warnings about storms and severe weather, says Jonathan How, principal investigator at MIT’s Department of Aeronautics and Astronautics.

Nimble sensors: Small, unmanned aerial vehicles, such as this 18-kilogram Boeing ScanEagle, could provide more precise data about weather systems, to increase the accuracy of long-term forecasts.

Long-term predictions don’t necessarily go wrong because of forecasting models, but rather because initial conditions were inaccurately measured, says Martin Ralph, a research meteorologist at the National Oceanic and Atmospheric Administration’s earth systems laboratory, in Boulder, CO. Such inaccuracies come from gaps in the data, he says.

Ground-based sensors are already used to record temperature, wind speed, humidity, air density, and rainfall, but they gauge conditions only at ground level, says How. At sea, where many severe weather fronts originate, the coverage is much sparser. Satellite observations help build up a picture, but satellites are blind to a number of useful types of data, such as low-altitude wind speed and atmospheric boundary conditions, says Ralph.

To get the most accurate readings, you really want to get your sensors into the weather itself, says How. In theory, weather balloons can do this, but only if they happen to be in the right place at the right time. So weather services currently attempt to track down weather systems using piloted planes that fly prescribed routes, taking measurements along the way. The logistics of deploying such planes is so complicated, however, that it’s difficult to change their routes in response to changing weather conditions.

Consequently, says How, there has been a lot of interest in using unmanned aerial vehicles, or UAVs, instead. The idea is that there would be a constant number of UAVs in the air, continuously working together to position themselves in what would collectively be the most useful locations.

The problem, says How, is that calculating the most useful locations is an enormously complex task. It involves analyzing more than a million data states from hundreds of thousands of sensor locations, and using this data to predict the weather conditions six to eight hours from now. But that’s exactly the challenge that the MIT researchers tackled.

So far, the algorithms they developed have been used only in a simulation, as part of a National Science Foundation project. MIT’s Han-Lim Choi, who has been working on the algorithms as part of his PhD research, presented the latest results of the project last week at the IEEE Conference on Decision Control in Cancun, Mexico. The work has attracted the interest of the U.S. Navy, and the MIT group is applying for funding to put the algorithms into practice, says How.

One of the challenges presented by the project is fuel management, says Dario Floreano, an expert in flying robotics and head of the Laboratory of Intelligent Systems at the École Polytechnique Fédérale de Lausanne, in Switzerland. The algorithms will need to be able to quickly and efficiently reroute the UAVs so that they maintain optimal coverage, he says. “This will have to take into account many variables, including energy requirements for different reallocation strategies.”

Another challenge is size, says Floreano. The UAVs need to be small and safe enough to not harm humans and objects if they are deployed in large numbers. He points out, however, that subkilogram UAVs are now becoming available.

In fact, How and his colleagues are more interested in testing their algorithms on the relatively large ScanEagle UAVs from Boeing, which weigh about 18 kilograms apiece. These would be capable of flying distances in excess of 1,000 miles, even laden with sensors and communications equipment. With this sort of range, a fleet of just four could reasonably cover a good-sized area, reducing the risk of collisions with manmade objects.

Keep up with the latest in robotics at EmTech Digital.
Don't be left behind.

March 25-26, 2019
San Francisco, CA

Register now
More from Intelligent Machines

Artificial intelligence and robots are transforming how we work and live.

Want more award-winning journalism? Subscribe to Insider Plus.
  • Insider Plus {! insider.prices.plus !}*

    {! insider.display.menuOptionsLabel !}

    Everything included in Insider Basic, plus the digital magazine, extensive archive, ad-free web experience, and discounts to partner offerings and MIT Technology Review events.

    See details+

    Print + Digital Magazine (6 bi-monthly issues)

    Unlimited online access including all articles, multimedia, and more

    The Download newsletter with top tech stories delivered daily to your inbox

    Technology Review PDF magazine archive, including articles, images, and covers dating back to 1899

    10% Discount to MIT Technology Review events and MIT Press

    Ad-free website experience

/3
You've read of three free articles this month. for unlimited online access. You've read of three free articles this month. for unlimited online access. This is your last free article this month. for unlimited online access. You've read all your free articles this month. for unlimited online access. You've read of three free articles this month. for more, or for unlimited online access. for two more free articles, or for unlimited online access.