DocumentCode :
3168027
Title :
Integrating visual odometry and dead-reckoning for robot localization and obstacle detection
Author :
Cobos, J. ; Pacheco, L. ; Cufi, X. ; Caballero, D.
Author_Institution :
Inst. of Inf. & Applic., Univ. of Girona, Girona, Spain
Volume :
1
fYear :
2010
fDate :
28-30 May 2010
Firstpage :
1
Lastpage :
6
Abstract :
The research presented introduces a new methodology to infer environment structure and robot localization by using a monocular machine vision system. The local field of view is constrained to the vicinity of the mobile robot in order to accomplish with robust navigation issues. The strategy proposed uses optical flow techniques and planar models to obtain qualitative 3D information and robot localization by using time integration series of acquired frames. In this way, different space resolution and meaningful corner information are considered. The different significant image points are correlated from camera pose knowledge and odometer data. The robot localization is achieved combining on board and visual odometer systems for reducing dead reckoning problems. Therefore, the two system errors are compared in a parallel process that selects the most accurate robot localization. Moreover, it is used to infer qualitative 3D information, when mismatches between both odometer systems are produced, due to the fact that the planar floor model is not accomplished. In this context, experimental results that reinforce the effectivity of the work developed are reported by using the available lab mobile platform. Other remarkable features of the strategy presented are its simplicity and the low computational cost.
Keywords :
collision avoidance; distance measurement; image sequences; mobile robots; robot vision; time series; image points; infer environment structure; lab mobile platform; mobile robot localization; monocular machine vision system; obstacle detection; optical flow techniques; planar floor model; qualitative 3D information; robust navigation issues; time integration series; visual odometry integration; Cameras; Dead reckoning; Image motion analysis; Integrated optics; Machine vision; Mobile robots; Navigation; Robot localization; Robot vision systems; Robustness; autonomous mobile robots; colision avoidance; localization; monocular vision; navigation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation Quality and Testing Robotics (AQTR), 2010 IEEE International Conference on
Conference_Location :
Cluj-Napoca
Print_ISBN :
978-1-4244-6724-2
Type :
conf
DOI :
10.1109/AQTR.2010.5520874
Filename :
5520874
Link To Document :
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