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Self-Supervised Learning for Visual Obstacle Avoidance
Tom van Dijk
2022
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With a growing number of drones, the risk of collision with other air traffic or fixed obstacles increases. New safety measures are required to keep the operation of Unmanned Aerial Vehicles (UAVs) safe. One of these measures is the use of a Collision Avoidance System (CAS), a system that helps the drone autonomously detect and avoid obstacles.
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Keywords
- Computer vision
- micro aerial vehicles
- monocular depth estimation
- obstacle avoidance
- self-supervised learning
- stereo vision
- Technology, engineering, agriculture
- unmanned aerial vehicles
Links
DOI: 10.34641/mg.19Editions