Ultrasonic sensor data integration and its application to environment perception

Charles C. Chang, Kai-Tai Song*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

To move in an unknown or uncertain environment, a mobile robot must collect information from various sensors and use it to construct a representation of the external world. Ultrasonic sensors can provide range data for this purpose in a simple and cost-effective way. However, most ultrasonic sensors are not sufficient for environment recognition because of their large beam opening angles. In this article the beam-opening-angle problem is solved by fusing data from multiple ultrasonic sensors. We propose two methods for sensor data fusion. One uses an artificial neural network (ANN), and the other is based on a mathematical model. Simulations and experiments show that the mathematical model is more accurate when there is no noise in the sensor readings, but the ANN method is better when the sensors are subject to much noise. To extract line segments from the ultrasonic image, we develop a line extractor that is more efficient than traditional line fitting methods in this application. Experimental results show that this method is effective for environment perception in a robotic system.

Original languageEnglish
Pages (from-to)663-677
Number of pages15
JournalJournal of Robotic Systems
Volume13
Issue number10
DOIs
StatePublished - 1 Jan 1996

Fingerprint Dive into the research topics of 'Ultrasonic sensor data integration and its application to environment perception'. Together they form a unique fingerprint.

Cite this