DocumentCode
1577087
Title
Orientation estimation fusing a downward looking camera and inertial sensors for a hovering UAV
Author
Araguas, Gaston ; Paz, Claudio ; Gaydou, David ; Perez Paina, Gonzalo
Author_Institution
Center for IT Res. (CIII), Nat. Tech. Univ., Cordoba, Argentina
fYear
2013
Firstpage
1
Lastpage
6
Abstract
Nowadays, a particular kind of UAVs (Unmanned Aerial Vehicle) known as quadcopters or quadrotors have become very popular. This is mainly due to their reduced size and high maneuverability which allow them to operate in indoor environments. The requirement for orientation estimation in these vehicles is twofold: for low level stability control, and for high level navigation and motion planning. Orientation estimation is usually carried out fusing measurements of different sensors including inertial sensor, magnetic compass, sonar, GPS, camera, etc. As is known, GPS signal is not available in indoor environments and the Earth´s magnetic field is highly disturbed by ferromagnetic structures. In the present work we describe a new approach for quadrotor orientation estimation fusing inertial measurements with a downward looking camera. Inertial sensor are used for orientation estimation based on the gravity vector, and the camera provides information related to the heading direction. The camera heading or yaw angle estimation is based on spectral features extracted from the floor plane. Experimental results show the performance of the presented approach applied to a hovering UAV.
Keywords
autonomous aerial vehicles; cameras; feature extraction; inertial navigation; path planning; robot vision; sensor fusion; sonar; spectral analysis; stability; GPS; camera heading; downward looking camera; ferromagnetic structures; fusing measurements; gravity vector; heading direction; high level navigation; hovering UAV; inertial measurements; inertial sensors; low level stability control; magnetic compass; motion planning; quadcopters; quadrotor orientation estimation; quadrotors; size reduction; sonar; spectral feature extraction; unmanned aerial vehicle; yaw angle estimation; Cameras; Estimation; Magnetic sensors; Quaternions; Vectors; Visualization;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Robotics (ICAR), 2013 16th International Conference on
Conference_Location
Montevideo
Type
conf
DOI
10.1109/ICAR.2013.6766576
Filename
6766576
Link To Document