Autonomous innovation to serve the greater good

By combining robotics, automation, and artificial intelligence (AI), Maryland Engineering researchers and students are building solutions that can help save lives, protect property, and safeguard the environment.

One such system, RoboScout, Maryland’s entry in a competition run by the defense agency DARPA, would rapidly survey and assess injuries at sites of disasters or violence. The information RoboScout is designed to collect could help first responders prioritize medical care, a process called triage. The ambitious project, while in its early stages, is an innovative step toward autonomous systems to help as many people as possible survive such events.

Discover how RoboScout would work.

Assisting first responders is just one example of the potential good autonomous tech can do. UMD engineers are building systems that address a multitude of challenges, while also preparing current—and future—workers for this innovation revolution.

Monitoring wildfires

Wildfires can ignite in remote places. But all too often, their destructive fury encroaches on homes and communities. In January 2025 alone, wildfires in California burned more than 57,000 acres, costing 29 lives and destroying more than 16,000 homes and other structures. Maryland engineers are designing drone-based systems for autonomously assessing, and even fighting, fires like these from above.

Two teams are working on separate projects with related goals. The first aims to develop drones that fire departments could fly over fires to collect information about them in real time, so they can make more informed decisions about how to fight them. The machine’s AI would possess the capacity to navigate along a fire on its own.

All the while, it would assess images from its visible light and infrared cameras to identify the burning areas below. This data would be transmitted to the ground, where firefighters could use it to find a fire or modify their strategies for fighting it.

A second team, called Crossfire, is participating in the XPRIZE Wildfire competition, which challenges participants to develop autonomous technology capable of detecting an early-stage wildfire somewhere in a 1,000-square-kilometer area, and then suppressing it (all within 10 minutes). To put out a fire once it’s identified, the team is experimenting with a well-established fire suppressant: water.

This task would likely be carried out by a different drone or drones, which would release a water-carrying vessel that ruptures at a predetermined height above the fire.

Ultimately, Fernando Raffan-Montoya, an assistant professor of fire protection engineering leading the first wildfire project and collaborating on Crossfire, envisions systems like these informing on-the-ground decisions, such as when to order evacuations. Drone-based fire suppression, meanwhile, could one day protect communities from an approaching wildfire, he says.

Between climate change, which creates conditions more conducive to fires, and increased building in wildland areas, the problem will continue to grow. “We believe that autonomy will bring a much-needed part of the solution,” Raffan-Montoya says.

Urgent medical delivery

Maryland’s Smith Island doesn’t have a pharmacy, so to pick up a prescription, any one of the roughly 200 islanders must take a boat across Chesapeake Bay to the mainland. But options are limited since ferries may run only once a day, or less frequently in bad weather.

These logistics can be particularly problematic for residents with chronic health conditions—diabetes, heart disease, and the like—who must take medication regularly. What’s more, urgent situations occasionally arise when someone needs a prescription at short notice.

“There are cases when 24 hours can make a big difference,” says John Slaughter, director of UMD’s UAS Research and Operations Center located in southern Maryland.

Working with partners, including the state of Maryland, Slaughter leads a team that is developing a solution: drones that deliver medications to the island and perhaps bring back samples, such as vials of blood, for testing. With this autonomous system, they aim to help improve the health of island residents, particularly the most vulnerable among them who may have ongoing medical needs and trouble traveling.

The team hasn’t settled on a drone model yet, but because the flight is relatively long, they plan to use an energy-efficient machine that takes off and lands like a helicopter, but flies like an airplane between locations. Once they have selected a drone, they intend to modify it to handle a less-than-five-pound (0.45 kilogram) payload that includes the camera it uses for navigation.

They intend to give the drone’s AI what’s called “conditional autonomy,” Slaughter says. “It’s going to be able to get itself to the delivery location, with the pilot ‘riding along,” as it were, to monitor its progress and intervene if there’s a problem.”

More productive, sustainable oyster farming

When scattering young oysters to seed a new crop, Chesapeake Bay’s oyster farmers have no way of knowing for certain that the seafloor provides the right conditions for the bivalves to grow. Likewise, when dragging a dredge to retrieve their crop, a farmer has limited information about where best to retrieve mature oysters, leading to unnecessary collateral damage to the ecosystem below.

A team led by Miao Yu, a professor of mechanical engineering, intends to update these long-standing strategies to make farming more efficient and productive, and less destructive. “We want to change the current practice from essentially a random approach to precision planting and harvesting,” she says.

Yu is leading a project that aims to make shellfish farming smarter and more sustainable. As part of it, she and her colleagues are developing robotics and AI technologies that will autonomously survey the seafloor of shellfish farming plots like those in the bay.

A submerged robot with a camera would collect detailed images underwater while tethered to a boat or a robot on the water’s surface. This second robot would be equipped with a sonar device that emits pulses of sound to create an acoustic image over a larger field of view.

Based on this information, AI algorithms would create a map of the farm and assess the crop, including, for example, the density of the oysters at a given location. A separate AI model would generate recommendations for farmers, including the GPS coordinates for a path to follow when harvesting.

Ultimately, the team aims to help the farmers improve their oyster yields by at least 10%. This more strategic approach could offer other benefits too, including protecting the seafloor and reducing fuel consumption. Increasing production of oysters could also provide a source of protein responsible for lower levels of greenhouse gas emissions than other sources of this nutrient, notably beef.