TY - GEN
T1 - Visual attitude stabilization of a unmanned helicopter in unknown environments with an embedded single-board computer
AU - Yigit, Cihat Bora
AU - Altug, Erdinc
PY - 2012
Y1 - 2012
N2 - Enabling a flying robot to navigate autonomously in an unstructured and unknown indoor or outdoor environment is a big challenge. Attitude is one of the most important parameters for an autonomous UAV during such a flight. In this paper, we present the use of a vision system that can be used to estimate vehicle attitude using monocular pinhole camera only. Vision system are readily available on various UAV platforms and can be used for this purpose. Unlike previous work, this approach does not require (natural or artificial) parallel lines, ground markers or landmarks on the environment as clues, or use external sensors (e.g. VICON or GPS), additional on-board sensors (e.g. IMU), or additional special purpose cameras or multiple sensors. The proposed algorithm relies on on-board vision only, and the vision processing and control are performed on-board the vehicle using a single-board vision computer. After explanation of the algorithm, detailed presentation of the developed system and experimental set-up are provided. Finally, the results of the estimation and control experiments performed on a model quadrotor helicopter are presented.
AB - Enabling a flying robot to navigate autonomously in an unstructured and unknown indoor or outdoor environment is a big challenge. Attitude is one of the most important parameters for an autonomous UAV during such a flight. In this paper, we present the use of a vision system that can be used to estimate vehicle attitude using monocular pinhole camera only. Vision system are readily available on various UAV platforms and can be used for this purpose. Unlike previous work, this approach does not require (natural or artificial) parallel lines, ground markers or landmarks on the environment as clues, or use external sensors (e.g. VICON or GPS), additional on-board sensors (e.g. IMU), or additional special purpose cameras or multiple sensors. The proposed algorithm relies on on-board vision only, and the vision processing and control are performed on-board the vehicle using a single-board vision computer. After explanation of the algorithm, detailed presentation of the developed system and experimental set-up are provided. Finally, the results of the estimation and control experiments performed on a model quadrotor helicopter are presented.
UR - http://www.scopus.com/inward/record.url?scp=84873538906&partnerID=8YFLogxK
U2 - 10.1109/ROSE.2012.6402628
DO - 10.1109/ROSE.2012.6402628
M3 - Conference contribution
AN - SCOPUS:84873538906
SN - 9781467327046
T3 - 2012 IEEE International Symposium on Robotic and Sensors Environments, ROSE 2012 - Proceedings
SP - 49
EP - 54
BT - 2012 IEEE International Symposium on Robotic and Sensors Environments, ROSE 2012 - Proceedings
T2 - 2012 10th IEEE International Symposium on Robotic and Sensors Environments, ROSE 2012
Y2 - 16 November 2012 through 18 November 2012
ER -