Imperial College London
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ProfessorJulieMcCann

Faculty of Engineering, Department of Computing

Vice-Dean (Research) for the Faculty of Engineering
 
 
 
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Contact

 

+44 (0)20 7594 8375j.mccann Website

 
 
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Assistant

 

Miss Teresa Ng +44 (0)20 7594 8300

 
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Location

 

260ACE ExtensionSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Awad:2023:10.1109/ICUAS57906.2023.10156123,
author = {Awad, H and Heggo, M and Pang, O and Kovac, M and McCann, J},
doi = {10.1109/ICUAS57906.2023.10156123},
pages = {401--406},
publisher = {IEEE},
title = {Multirotor motion enhancement using propeller speed measurements},
url = {http://dx.doi.org/10.1109/ICUAS57906.2023.10156123},
year = {2023}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Multirotor autopilots often depend on open-loop control without the feedback of propeller speeds, although they are a critical factor in determining motion characteristics. This paper proposes a system that leverages actual propeller speeds as direct feedback to the autopilot to improve the state estimation and dynamics of the multirotor. Software-in-the-Loop (SITL) and Hardware-in-the-Loop (HITL) simulations with real data, in different scenarios, are conducted to demonstrate the impact of combining propeller speeds with typical drone sensors. The results show that the drone becomes more stable with lower trajectory errors. Further, a noticeable reduction in the vehicle position median error while following a trajectory is shown, and a considerable increase in the flying duration time before crashing in case of a motor fault. These results highlight the potential of adding propeller speed feedback to increase the autopilot’s controllability which enhances drone performance in sensitive applications.
AU  - Awad,H
AU  - Heggo,M
AU  - Pang,O
AU  - Kovac,M
AU  - McCann,J
DO  - 10.1109/ICUAS57906.2023.10156123
EP  - 406
PB  - IEEE
PY  - 2023///
SP  - 401
TI  - Multirotor motion enhancement using propeller speed measurements
UR  - http://dx.doi.org/10.1109/ICUAS57906.2023.10156123
UR  - https://ieeexplore.ieee.org/abstract/document/10156123
UR  - http://hdl.handle.net/10044/1/104832
ER  -
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