Uncovering Drone Intentions using Control Physics Informed Machine Learning: data
Date published
2024-03-04 10:36
Free to read from
Supervisor/s
Journal Title
Journal ISSN
Volume Title
Publisher
Cranfield University
Department
Type
Software
ISSN
Format
Citation
Perrusquia Guzman, Adolfo; Wei, Zhuangkun; Guo, Weisi; Fraser, Benjamin (2024). Uncovering Drone Intentions using Control Physics Informed Machine Learning: data. Cranfield Online Research Data (CORD). Software. https://doi.org/10.17862/cranfield.rd.25204409
Abstract
This repository provides the data and code of the paper "Uncovering Drone Intentions using Control Physics Informed Machine Learning"
Description
Software Description
Software Language
Github
Keywords
drone intentions', 'physics informed', 'reward function', 'deep learning', 'machine learning'
DOI
10.17862/cranfield.rd.25204409
Rights
Apache 2.0
Relationships
Relationships
Funder/s
UKRI Trustworthy Autonomous Systems Node in Security