DocumentCode
504133
Title
A comparison of using probabilistic motion models for mobile robot pose estimation
Author
Bui, T. T Quyen ; Hong, Keum-Shik
Author_Institution
Sch. of Mech. Eng., Pusan Nat. Univ., Busan, South Korea
fYear
2009
fDate
18-21 Aug. 2009
Firstpage
528
Lastpage
532
Abstract
This paper addresses a robot pose estimation problem. The data received from the inertial sensors are converted to a diverse odometry, after that the current robot pose is estimated by utilizing the different probabilistic motion models and estimate algorithms. In addition, the experimental evaluations are performed in indoor environment and conclusions are given.
Keywords
distance measurement; estimation theory; mobile robots; motion estimation; pose estimation; probability; diverse odometry; estimate algorithm; indoor environment experimental evaluation; inertial sensor; mobile robot pose estimation; probabilistic motion model; Calibration; Global Positioning System; Mobile robots; Motion estimation; Performance evaluation; Robot sensing systems; Sensor fusion; Sensor systems; Simultaneous localization and mapping; Wheels; Estimation; Localization; Mobile robot; Monte Carlo method; Probabilistic motion model;
fLanguage
English
Publisher
ieee
Conference_Titel
ICCAS-SICE, 2009
Conference_Location
Fukuoka
Print_ISBN
978-4-907764-34-0
Electronic_ISBN
978-4-907764-33-3
Type
conf
Filename
5332439
Link To Document