The collapse of the Surfside building in Florida was a great tragedy, leaving nearly 100 dead. The rescue operations went on for weeks. They might have taken longer without autonomous drones — flying robots.
Robots have been used increasingly in rescue operations in recent years. In this case, nine different models of drones pitched in to search for survivors, and then for the deceased. Thermal imaging allowed them to search around the clock.
304 missions were flown just for strategic purposes, making this the most extensive use of drones for any disaster to date. In addition to searches for human victims of the collapse, drones were also used to identify the best places to use water to fight fires and to map the changing surfaces of the disaster.
Sometimes things seem to bee a big improvement in the lab, but in real life they’re not worth it. More flight time and better mapping skills made some drones a better bet than others — ordinary consumer models actually worked out well.
Computer vision/machine learning (CV/ML) was expected to be more useful than it really was. People in need of rescue weren’t visible enough under the rubble for this technology to help. Dogs hunting by scent were more effective.
Completely new software?
New apps are usually constructed for new robotic technology, but that may not be a good thing in rescue situations. In disasters, the urgency and stress levels make it impractical to learn new software. First responders generally refused. They chose to use familiar apps even if they weren’t as well adapted to the purpose.
Creating interfaces with familiar apps would make more sense.
Real world conclusions
The usefulness of drones was clear in this disaster. The people involved pointed out that many states had planned to stop buying the kinds of drones that turned out to be the most useful. Since disasters are by their nature hard to predict and practice for, this information is valuable and should be taken seriously.
Robotic research is often showy and intended to impress. It might be more useful to look for real-world applications that would make an immediate difference to rescue operations — or to manufacturing.
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