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Self-Supervised Learning for Visual Obstacle Avoidance

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...

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Hlavní autor: van Dijk, Tom
Médium: Online
Jazyk:angličtina
Vydáno: TU Delft OPEN Publishing 2025
Témata:
computer vision
stereo vision
monocular depth estimation
obstacle avoidance
self-supervised learning
unmanned aerial vehicles
micro aerial vehicles
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TR Transport technology and trades::TRP Aerospace and aviation technology
On-line přístup:ONIX_20250522T133704_9789463665094_29
Tagy: Přidat tag
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Shrnutí: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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