The idea stems from a proposal that autonomous drones that are able to "bob and weave through trees" could provide a solution for finding hikers that are lost in forests. This could offer an alternative to helicopters and drones flying above the trees, which are unable to see through the tree canopy, however using GPS signals to guide the drones in such forest environments - where the signals would be unreliable or even nonexistent - would be problematic.
The researchers instead propose a solution where the drones use only onboard computation and wireless communication to collaboratively search under dense forest canopies. They describe a system where each autonomous quadrotor drone would be equipped with laser-range finders for position estimation, localization, and path planning, and as the drone flies around, it creates an individual 3D map of the terrain.
The drone uses algorithms to help it recognize unexplored and already-searched spots, so it knows when it's fully mapped an area. An off-board ground station combines individual maps from multiple drones into a global 3D map that can be monitored by human rescuers.
In a real-world implementation, say the researchers, the drones would also be equipped with object detection to identify a missing hiker. When located, the drone would tag the hiker's location on the global map, and human searchers could then use this information to plan a rescue mission.
"Essentially," says Yulun Tian, a graduate student in the Department of Aeronautics and Astronautics (AeroAstro) and first author of a paper on the system, "we're replacing humans with a fleet of drones to make the search part of the search-and-rescue process more efficient."
To test their idea, the researchers tested multiple drones in simulations of randomly generated forests, and tested two drones in a forested area within NASA's Langley Research Center. In both experiments, each drone mapped a roughly 20-square-meter area in about two to five minutes and collaboratively fused their maps