DocumentCode
1863418
Title
Sensor-based self-localization for wheeled mobile robots
Author
Curran, A. ; Kyriakopoulos, K.J.
Author_Institution
Rensselaer Polytech. Inst. Troy, NY, USA
fYear
1993
fDate
2-6 May 1993
Firstpage
8
Abstract
A reliable and robust algorithm for localizing a mobile robot in an indoor environment that is relatively consistent with an a priori map is demonstrated. The algorithm uses an extended Kalman filter that combines dead-reckoning, ultrasonic, and infrared sensor data to estimate current position and orientation. Through a thresholding approach, unexpected obstacles can be detected. Experimental results from implementation in a mobile robot, Nomad-200, are presented
Keywords
Kalman filters; filtering and prediction theory; mobile robots; sensor fusion; Nomad-200; a priori map; dead-reckoning; extended Kalman filter; indoor environment; infrared sensor data; obstacle detection; orientation estimation; position estimation; sensor-based self-localization; thresholding; ultrasonic data; wheeled mobile robots; Costs; Indoor environments; Infrared sensors; Mobile robots; Optical filters; Optical sensors; Recursive estimation; Robot sensing systems; Robotics and automation; Robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
Robotics and Automation, 1993. Proceedings., 1993 IEEE International Conference on
Conference_Location
Atlanta, GA
Print_ISBN
0-8186-3450-2
Type
conf
DOI
10.1109/ROBOT.1993.291954
Filename
291954
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