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Feature-based probabilistic map building using time and amplitude information of sonar in indoor environments

Published online by Cambridge University Press:  05 July 2001

Hyoung Jo Jeon  and
Byung Kook Kim
Hyoung Jo Jeon
Affiliation:
Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, 373–1 Kusong-dong, Yusong-gu, Taejon 305–701 (Korea). [email protected], [email protected]
Byung Kook Kim
Affiliation:
Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, 373–1 Kusong-dong, Yusong-gu, Taejon 305–701 (Korea). [email protected], [email protected] Author to whom all correspondence should be addressed.
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Abstract

We present a feature-based probabilistic map building algorithm which directly utilizes time and amplitude information of sonar in indoor environments. Utilizing additional amplitude-of-signal (AOS) obtained concurrently with time-of-flight (TOF), the amount of inclination of target can be directly calculated from a single echo, and the number of measurements can be greatly reduced with result similar to dense scanning. A set of target groups (set of hypothesized targets originated from one measurement) is used and refined by each measurement using an extended Kalman filter and Bayesian conditional probability. Experimental results in a real indoor environment are presented to show the validity of our algorithm.

Keywords

Ultrasonic sensorTime of flightAmplitude of signalMap buildingExtended Kalman filterBayesian reasoning
Type
Research Article
Information
Robotica , Volume 19 , Issue 4 , July 2001 , pp. 423 - 437
Copyright
© 2001 Cambridge University Press

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