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

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.
Publisher
CAMBRIDGE UNIV PRESS
Issue Date
2001
Language
ENG
Keywords

MOBILE ROBOT NAVIGATION; ULTRASONIC SENSORS; MODEL; ARRAY

Citation

ROBOTICA, v.19, pp.437 - 4

ISSN
0263-5747
URI
http://hdl.handle.net/10203/1348
Appears in Collection
EE-Journal Papers(저널논문)
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