Engineering Commons^™

Utilizing An Improved Rotorcraft Dynamic Model In State Estimation, Timothy Mclain, Randal W. Beard, Robert C. Leishman, John Macdonald, Jeffrey L. Ferrin, Stephen C. Quebe

Faculty Publications

Multirotor aircraft have become a popular platform for indoor flight. To navigate these vehicles indoors through an unknown environment requires the use of a SLAM algorithm, which can be processing intensive. However, their size, weight, and power capacity limit the processing capabilities available onboard. In this paper, we describe an approach to state estimation that helps to alleviate this problem. By using an improved dynamic model we show how to more accurately estimate the aircraft states than can be done with the traditional approach of integrating IMU measurements. The estimation is done with relatively infrequent corrections from accelerometers (40Hz) and …