Hostname: page-component-586b7cd67f-gb8f7 Total loading time: 0 Render date: 2024-11-24T20:30:23.023Z Has data issue: false hasContentIssue false

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
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.

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.

Type
Research Article
Copyright
© 2001 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)