Title :
Onboard optical flow and vision based localization for a quadrotor in unstructured indoor environments
Author :
Qingji Gao ; Yao Wang ; Dandan Hu
Author_Institution :
Sch. of Pattern Recognition & Intell. Syst. on aviation Inst. of Autom., Civil Aviation Univ. of China, Tianjin, China
Abstract :
This paper considers problem of localization for an aerial robot in unstructured indoor environments. A vision correction method based on linear characteristics is proposed. The dynamic model is established using an optical flow sensor. Use a strap-down camera to capture the frame of perpendicular line on the ground, and calculate the global position of their intersection point. As an observation, the vision position is input to the KALMAN filter in order to eliminate the accumulated error. Experimental results from indoor hover test verified the accuracy and real-time of the approach.
Keywords :
Kalman filters; autonomous aerial vehicles; helicopters; image sensors; image sequences; robot vision; KALMAN filter; aerial robot; dynamic model; global position; indoor hover test; intersection point; linear characteristics; onboard optical flow; optical flow sensor; quadrotor; strap-down camera; unstructured indoor environments; vision based localization; vision correction method; Adaptive optics; Cameras; Computer vision; Image motion analysis; Optical sensors; Robot sensing systems; Visualization;
Conference_Titel :
Guidance, Navigation and Control Conference (CGNCC), 2014 IEEE Chinese
Conference_Location :
Yantai
Print_ISBN :
978-1-4799-4700-3
DOI :
10.1109/CGNCC.2014.7007542
