Proceedings of the 2015 International conference on Applied Science and Engineering Innovation

Research on the state of estimation for unmanned research and rescue helicopter

Authors
JingHeng Wang, Wei Zhao, DongQi Meng
Corresponding Author
JingHeng Wang
Available Online May 2015.
DOI
10.2991/asei-15.2015.11How to use a DOI?
Keywords
unmanned helicopter , state estimation, Kalman filter, simulation
Abstract

This paper presents a technique to accurately estimate the state of unmanned research and rescue helicopter, Two Kalman filters were used, one for the gyroscope data and the other for the accelerometer data. Our approach is unique because it explicitly avoids dynamic modeling of the system and allows for an elegant combination of sensor data available at different frequencies. We also describe the larger context in which this work is embedded, namely the design and implementation of an unmanned research and rescue helicopter.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 International conference on Applied Science and Engineering Innovation
Series
Advances in Engineering Research
Publication Date
May 2015
ISBN
978-94-62520-94-3
ISSN
2352-5401
DOI
10.2991/asei-15.2015.11How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - JingHeng Wang
AU  - Wei Zhao
AU  - DongQi Meng
PY  - 2015/05
DA  - 2015/05
TI  - Research on the state of estimation for unmanned research and rescue helicopter
BT  - Proceedings of the 2015 International conference on Applied Science and Engineering Innovation
PB  - Atlantis Press
SP  - 48
EP  - 52
SN  - 2352-5401
UR  - https://doi.org/10.2991/asei-15.2015.11
DO  - 10.2991/asei-15.2015.11
ID  - Wang2015/05
ER  -