Self-supervised learning for visual obstacle avoidance
Technical report
Book
(2022)
Author(s)
Tom van Dijk (TU Delft - Control & Simulation)
Research Group
Control & Simulation
DOI related publication
https://doi.org/10.34641/mg.19
To reference this document use:
https://resolver.tudelft.nl/uuid:020a8e2c-37fe-44c3-90ac-0022689f184a
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Publication Year
2022
Language
English
Research Group
Control & Simulation
ISBN (print)
9789463665094
Reuse Rights
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Abstract
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.