MIT team designs robot that helps fight coronavirus

Daniela Rus, Director of the Computer Science and Artificial Intelligence Laboratory at MIT, joins Yahoo Finance’s Kristin Myers to discuss the development of a new robotic system that neutralizes aerosolized forms of the coronavirus.

Video Transcript

KRISTIN MYERS: Well, forget about bleach because a robot is actually able to kill coronavirus. A team from MIT has invented a robot that powerfully disinfects surfaces-- and get this-- neutralizes aerosolized forms of coronavirus. For more on this, we welcome Daniela Rus, director of the Computer Science and Artificial Intelligence Laboratory at MIT. Daniela, thank you so much for joining us today. So the first question I want to ask you is, how does this robot even work?

DANIELA RUS: So the robot, you can see, it looks kind of like the queen piece of a chess set. It has a mobile base, so that is the robot that can navigate a space much like a self-driving car would. And on top of the robot sits a UVC disinfecting light. The robot is controlled by some powerful algorithms that compute exactly where the robot has to go and how long it has to stay in order to neutralize the-- the germs that exist in that particular part of the space.

KRISTIN MYERS: So how quickly can it do that?

DANIELA RUS: Well, the robot-- for the particular space we have-- we have deployed the robots in, which is the Greater Boston Food Bank, a space that is particularly important in Boston's fight against coronavirus because a lot of people get their food and sustenance there, the space is 4,000 square feet. The robot can cover it in half an hour.

KRISTIN MYERS: Wow.

DANIELA RUS: It-- we have computed the speed of the robot so that it delivers the right amount of dosage to neutralize the germs.

KRISTIN MYERS: So I'm thinking, as we're starting to reopen again, especially schools now starting to be reopened, can this be rolled out at scale, you know, to neutralize the virus in, you know, banks, stores, schools perhaps for the fall?

DANIELA RUS: Exactly. This is such an exciting idea to use the solution as a hands-free safe way to neutralize dorms, hallways, hospitals, airports, even airplanes, grocery stores. This solution can be deployed in so many different types of environments. The robot moves autonomously, so a person is not needed to control the robot. And-- but the robot needs to have a-- a map or a-- a sense of the geometry of the space.

KRISTIN MYERS: So everything sounds pretty perfect, but what are the-- the drawbacks or the hurdles that you guys are facing as you're programming this robot to move around warehouses?

DANIELA RUS: So I would say that an important part of the puzzle is that the light emitted by the robot is dangerous to humans, so the robot cannot be in the same space as humans. Or if people are around the robot, they have to wear protective gear. In terms of navigation, the solutions are fairly straightforward. The-- the challenge was to do the-- the coverage modeling and-- and the-- the dosage computation. But in terms of how this robot moves, it's pretty much like a self-driving car, and-- and so the robot has a bunch of sensors. It uses the sensors to identify where the free spaces are, where the obstacles are. It knows where it wants to go. It computes a path.

KRISTIN MYERS: All right--

DANIELA RUS: The cost of the robot is still high, and so this may be a challenge for rapid broad deployment.

KRISTIN MYERS: Well, what's the cost of the robot right now?

DANIELA RUS: The cost of the robot is the cost of the base on which-- on which the UVC disinfection system sits, and so it can be adjusted according to what base you want to use for your-- for your space.

KRISTIN MYERS: Right.

DANIELA RUS: But the robot can also be used as a service, and so maybe you don't need to buy an entire robot set. You can-- you can book the robot for a few hours a day to take care of your space.

KRISTIN MYERS: All right, well, now I've seen everything. Don't need Clorox. Don't need Lysol. You can just get a-- a robot with a UV light. Daniela Rus from MIT, thanks so much.

DANIELA RUS: Thank you.