DocumentCode :
177006
Title :
A method about state-space representation and location estimation by computational geometry
Author :
Yi Zhang ; Mengyin Fu ; Meiling Wang
Author_Institution :
Acad. of AutoControl, Beijing Inst. of Technol., Beijing, China
fYear :
2014
fDate :
May 31 2014-June 2 2014
Firstpage :
4579
Lastpage :
4583
Abstract :
This paper analyzes the accuracy concerns of self-positioning of some unmanned ground vehicle that is undertaking simultaneous localization and mapping. The environment information description provided by vehicle sensor usually has strong geometric feature. Thus, the paper puts forward a method with geometric feature for simultaneous localization and mapping environment description. After analyzing the uncertainties in this type of environment description, the paper uses computational geometry to model and describe the uncertainties caused by measuring error of the sensor. At last, by using computational geometry, the paper proposes a location estimation algorithm that helps to reduce the impact of measuring errors on calculation coordinates.
Keywords :
SLAM (robots); computational geometry; position control; remotely operated vehicles; sensors; state-space methods; calculation coordinates; computational geometry; geometric feature; location estimation; self-positioning; simultaneous localization and mapping environment description; state-space representation; unmanned ground vehicle; vehicle sensor; Kalman filters; Simultaneous localization and mapping; SLAM; UGV; computational geometry;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-3707-3
Type :
conf
DOI :
10.1109/CCDC.2014.6852990
Filename :
6852990
Link To Document :
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