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Drones learn to search forest trails for lost people

11 February 2016

Researchers have developed artificial intelligence software to teach a small quadrocopter to autonomously recognize and follow forest trails.

With the new drones, missing persons can be found and rescued quickly in forests and mountain areas (image: UZH; USI; SUPSI)

Every year, thousands of people lose their way in forests and mountain areas. In Switzerland alone, emergency centres respond to around 1,000 calls annually from injured and lost hikers. But drones can effectively complement the work of rescue services teams. Because they are inexpensive and can be rapidly deployed in large numbers, they substantially reduce the response time and the risk of injury to missing persons and rescue teams alike.

A group of researchers from the Dalle Molle Institute for Artificial Intelligence and the University of Zurich has developed artificial intelligence software to teach a small quadrocopter to autonomously recognize and follow forest trails. Believed to be a first in the fields of artificial intelligence and robotics, this success means drones could soon be used in parallel with rescue teams to accelerate the search for people lost in the wild.

"While drones flying at high altitudes are already being used commercially, drones cannot yet fly autonomously in complex environments, such as dense forests," says says Professor Davide Scaramuzza from the University of Zurich. "In these environments, any little error may result in a crash, and robots need a powerful brain in order to make sense of the complex world around them."

The drone used by the Swiss researchers observes the environment through a pair of small cameras, similar to those used in smartphones. Instead of relying on sophisticated sensors, their drone uses very powerful artificial-intelligence algorithms to interpret the images to recognize man-made trails. If a trail is visible, the software steers the drone in the corresponding direction.

"Interpreting an image taken in a complex environment such as a forest is incredibly difficult for a computer," says Dr Alessandro Giusti from the Dalle Molle Institute for Artificial Intelligence. "Sometimes even humans struggle to find the trail!"

The Swiss team solved the problem using a so-called 'Deep Neural Network', a computer algorithm that learns to solve complex tasks from a set of 'training examples', much like a brain learns from experience. In order to gather enough data to 'train' their algorithms, the team hiked several hours along different trails in the Swiss Alps and took more than 20 thousand images of trails using cameras attached to a helmet.

The effort paid off: When tested on a new, previously unseen trail, the deep neural network was able to find the correct direction in 85 percent of cases; in comparison, humans faced with the same task guessed correctly 82 percent of the time.

The research team warns that much work is still needed before a fully autonomous fleet will be able to swarm forests in search of missing people.


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