In what could one day help find missing people in forests, a team of researchers used deep learning to train an autonomous drone to navigate a previously-unseen trail in a densely wooded forest completely on its own.
The researchers from Dalle Molle Institute for Artificial Intelligence, the University of Zurich, and NCCR Robotics, mounted three GoPro cameras to a headset to train their deep neural network and took over 20,000 pictures from hours of trail hikes in the Swiss Alps. These images were then used alongside an NVIDIA GeForce GTX 580 GPU to teach the model what the boundaries of a hiking trail generally look like.
Check out the autonomous drone in action in the video below.
The researchers claim the resulting deep learning network is even better than humans at determining the correct direction of the trails on which it travels, guessing the correct direction of a trail with 85 percent accuracy. Humans tasked with determining the direction of the same trails were able to do so correctly only 82 percent of the time.
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Autonomous Search-and-Rescue Drones Outperform Humans at Navigating Forest Trails
Feb 11, 2016
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AI-Generated Summary
- Researchers from the Dalle Molle Institute for Artificial Intelligence, the University of Zurich, and NCCR Robotics trained an autonomous drone to navigate a previously unseen forest trail using deep learning.
- The team collected over 20,000 images from hours of trail hikes in the Swiss Alps using three GoPro cameras mounted on a headset to teach a neural network what trail boundaries look like.
- Training was accelerated with an NVIDIA GeForce GTX 580 GPU, and the resulting model achieved 85 percent accuracy in determining trail direction compared to 82 percent for humans.
Next Step
- Read the The Verge article for additional details on the autonomous drone navigation research.
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