Communications of the ACM
The Deep Learning Way to Design Fly-Like Robots
Researchers have developed a deep-learning-based motion-capture software that uses multiple camera views to model the movements of a fly in three dimensions.
Credit: P. Ramdya/EPFL
Researchers at Switzerland's Swiss Federal Institute of Technology, Lausanne (EPFL) have developed motion-capture software that uses deep learning to model a fruit fly's movements in three dimensions (3D), in the hope of designing fly-like robots.
The DeepFly3D system uses multiple cameras to record images of a fly crawling atop a small floating ball, which the software processes.
DeepFly3D can infer the insect's pose in three dimensions, predicting and calculating behavioral measurements at ultra-fine resolution without the need for manual calibration.
The system also employs active learning to improve its own performance.
EPFL's Pavan Ramdya said, "If we learn how [the fly] does what it does, we can have important impact on robotics and medicine and, perhaps most importantly, we can gain these insights in a relatively short period of time."
From EPFL (Switzerland)
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Abstracts Copyright © 2019 SmithBucklin, Washington, DC, USA
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