DocumentCode :
2031192
Title :
Invariant filtering for simultaneous localization and mapping
Author :
Deans, Matthew C. ; Hebert, Martial
Author_Institution :
Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
Volume :
2
fYear :
2000
fDate :
2000
Firstpage :
1042
Abstract :
This paper presents an algorithm for simultaneous localization and map building for a mobile robot moving in an unknown environment. The robot can measure only the bearings to identifiable targets and its own relative motion. The approach is to recursively estimate features of the environment which are invariant to the robot pose in order to decouple the pose error from the map error. The highly nonlinear nature of this problem requires more explicit reasoning about the spatial relationships between landmarks and between the robot and landmarks than those used in previous methods
Keywords :
filtering theory; mobile robots; recursive estimation; spatial variables measurement; invariant filtering; map building; mobile robot; recursive feature estimation; simultaneous localization; simultaneous mapping; spatial relationships; Extraterrestrial measurements; Filtering; Mobile robots; Nonlinear filters; Position measurement; Recursive estimation; Robot kinematics; Simultaneous localization and mapping; Stochastic processes; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 2000. Proceedings. ICRA '00. IEEE International Conference on
Conference_Location :
San Francisco, CA
ISSN :
1050-4729
Print_ISBN :
0-7803-5886-4
Type :
conf
DOI :
10.1109/ROBOT.2000.844737
Filename :
844737
Link To Document :
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