Title :
Accurate feature matching for autonomous vehicle navigation in urban environments
Author :
Sasiadek, Jerzy Z. ; Walker, Michael J. ; Krzyzak, Adam
Author_Institution :
Dept. of Mech. & Aerosp. Eng., Carleton Univ., Ottawa, ON, Canada
Abstract :
The research presented in this paper ultimately aims at accurate Unmanned Aerial Vehicle (UAV) navigation using camera(s) to augment inertial navigation unit data while flying through an urban environment. Accurate position and depth determination requires precise image feature location and matching. This paper investigates accurate feature matching enabling determination of image depth. The paper offers two unique contributions to the field. First, it is shown how to improve feature matching accuracy when a good position estimate is available. Secondly, it is shown how to increase the number of matched features. In this way, there is more data and it may be possible, in future research, to identify the depth plane a feature belongs to and so increase the accuracy of position determination. Preliminary results are reported.
Keywords :
aerospace computing; feature extraction; image matching; image sensors; mobile robots; path planning; remotely operated vehicles; robot vision; UAV; autonomous vehicle navigation; feature matching; image depth; image feature location; image feature matching; unmanned aerial vehicle; urban environment; urban environments; Accuracy; Correlation; Detectors; Global Positioning System; Robot sensing systems; Urban areas;
Conference_Titel :
Methods and Models in Automation and Robotics (MMAR), 2011 16th International Conference on
Conference_Location :
Miedzyzdroje
Print_ISBN :
978-1-4577-0912-8
DOI :
10.1109/MMAR.2011.6031318