DocumentCode :
2341752
Title :
Analysis of local observability for feature localization in a maritime environment using an omnidirectional camera
Author :
Xu, Bin ; Stilwell, Daniel J. ; Gadre, Aditya S. ; Kurdila, Andrew
Author_Institution :
Virginia Polytech. Inst. & State Univ., Blacksburg
fYear :
2007
fDate :
Oct. 29 2007-Nov. 2 2007
Firstpage :
3666
Lastpage :
3671
Abstract :
Autonomous operation by a surface vehicle in a maritime setting requires that the surface vehicle detects non-water objects, including shoreline, hazards to navigation, and other moving vessels. In order to assess the utility of an omnidirectional camera for detecting and localizing non- water objects, we rigorously investigate observability of both stationary and moving features. For stationary features, we find that all but a small subset of the features are observable. For moving features, we show that an important class of feature and ASV trajectories are not observable.
Keywords :
Kalman filters; marine vehicles; mobile robots; nonlinear control systems; observability; remotely operated vehicles; robot kinematics; robot vision; ASV kinematics; Kalman filters; autonomous surface vehicle operation; feature localization; local observability analysis; maritime environment; moving features; nonlinear systems; nonwater object detection; omnidirectional camera; stationary features; Cameras; Hazards; Instruments; Mobile robots; Navigation; Object detection; Observability; Remotely operated vehicles; Simultaneous localization and mapping; Vehicle detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-0912-9
Electronic_ISBN :
978-1-4244-0912-9
Type :
conf
DOI :
10.1109/IROS.2007.4399483
Filename :
4399483
Link To Document :
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