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
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;
Conference_Titel :
ICCAS-SICE, 2009
Conference_Location :
Fukuoka
Print_ISBN :
978-4-907764-34-0
Electronic_ISBN :
978-4-907764-33-3
