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

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/).

Download article (PDF)

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  -