Improvement of dead reckoning accuracy of a mobile robot by slip detection and compensation using multiple model approach

Although dead reckoning based on odometry and inertial sensors is essential for a robotic localization system, none of previous works gives reliable and accurate position estimates on irregular terrain over long periods of time. Classical approaches use one estimator (such as a Kalman filter) with a...

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Bibliographic Details
Main Authors: Hyoung-Ki Lee, Kiwan Choi, Jiyoung Park, Yeon-Ho Kim, Seokwon Bang
Format: Conference Proceeding
Language:English
Subjects:
Accelerometers
Kalman filters
Mobile robots
Robot sensing systems
Robots
Sensors
Wheels
Online Access:Request full text
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Summary:Although dead reckoning based on odometry and inertial sensors is essential for a robotic localization system, none of previous works gives reliable and accurate position estimates on irregular terrain over long periods of time. Classical approaches use one estimator (such as a Kalman filter) with a single system model. However the single system model is not good to deal with both of slip and no-slip situations because of the dynamics changes. In this paper, a multiple model approach that uses two Kalman filters is presented: one Kalman filter accounting for no-slip condition and the other for slip condition. The Interacting Multiple Model (IMM) is adopted to switch two Kalman filters depending on whether slip occurs or not, and gives the weighted sum of two filter estimates. Experimental results are included to validate our approach.
ISSN:2153-0858
2153-0866
DOI:10.1109/IROS.2008.4650843