AI News, Fleets of drones could aid searches for lost hikers

Fleets of drones could aid searches for lost hikers

Finding lost hikers in forests can be a difficult and lengthy process, as helicopters and drones can’t get a glimpse through the thick tree canopy.

In a paper being presented at the International Symposium on Experimental Robotics conference next week, MIT researchers describe an autonomous system for a fleet of drones to collaboratively search under dense forest canopies.

An off-board ground station fuses individual maps from multiple drones into a global 3-D map that can be monitored by human rescuers.

In a real-world implementation, though not in the current system, the drones would come equipped with object detection to identify a missing hiker.

“Essentially, we’re replacing humans with a fleet of drones to make the search part of the search-and-rescue process more efficient,” says first author Yulun Tian, a graduate student in the Department of Aeronautics and Astronautics (AeroAstro).

The drones also performed well across several metrics, including overall speed and time to complete the mission, detection of forest features, and accurate merging of maps.

Exploring and mapping On each drone, the researchers mounted a LIDAR system, which creates a 2-D scan of the surrounding obstacles by shooting laser beams and measuring the reflected pulses.

When two drones loop around to the same cluster of trees, the ground station merges the maps by calculating the relative transformation between the drones, and then fusing the individual maps to maintain consistent orientations.

In the ground station, robotic navigation software called “simultaneous localization and mapping” (SLAM) — which both maps an unknown area and keeps track of an agent inside the area — uses the LIDAR input to localize and capture the position of the drones.

“It has to stop and turn, so that means it’s very inefficient in terms of time and energy, and you can’t really pick up speed.”  Instead, the researchers’ drones explore the closest possible area, while considering their current direction.

Fleets of drones could aid searches for lost hikers

Finding lost hikers in forests can be a difficult and lengthy process, as helicopters and drones can't get a glimpse through the thick tree canopy.

In a paper being presented at the International Symposium on Experimental Robotics conference next week, MIT researchers describe an autonomous system for a fleet of drones to collaboratively search under dense forest canopies.

An off-board ground station fuses individual maps from multiple drones into a global 3-D map that can be monitored by human rescuers.

In a real-world implementation, though not in the current system, the drones would come equipped with object detection to identify a missing hiker.

'Essentially, we're replacing humans with a fleet of drones to make the search part of the search-and-rescue process more efficient,' says first author Yulun Tian, a graduate student in the Department of Aeronautics and Astronautics (AeroAstro).

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 together in real-time.

The drones also performed well across several metrics, including overall speed and time to complete the mission, detection of forest features, and accurate merging of maps.

Exploring and mapping On each drone, the researchers mounted a LIDAR system, which creates a 2-D scan of the surrounding obstacles by shooting laser beams and measuring the reflected pulses.

When two drones loop around to the same cluster of trees, the ground station merges the maps by calculating the relative transformation between the drones, and then fusing the individual maps to maintain consistent orientations.

In the ground station, robotic navigation software called 'simultaneous localization and mapping' (SLAM) -- which both maps an unknown area and keeps track of an agent inside the area -- uses the LIDAR input to localize and capture the position of the drones.

Finding Lost Hikers in Dense Forests with Autonomous Drone Fleets

Calculating that relative transformation tells you how you should align the two maps so it corresponds to exactly how the forest looks,” explains Tian.

Instead of searching the closest possible unknown area, the drones “explore the closest possible area while considering their speed and direction and maintaining a consistent velocity.

This strategy—where the drone tends to travel in a spiral pattern—covers a search area much faster.” However, in order to merge maps, the drones must still be in communication with a ground station.

MIT’s autonomous drone fleet can operate in dense forests without GPS

Those who don’t hike or live in an area where hikers flock don’t understand how easy it can be to get lost in unfamiliar terrain, even when using maps.

The problem with using traditional drones under the forest canopy is that drones typically require GPS and under thick tree cover, GPS signals can’t reach.

While the MIT drones currently lack object detection, when the system is used in the real-world object detection capabilities would be integrated allowing drones to tag the location of hikers on the map.

Currently, the drones require a wireless router nearby to send map data to the ground station, in future implementations the engineers hope have the drones communicate wirelessly when close to each other and then disconnect when they separate.

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