Title: Object localisation through clustering unreliable ultrasonic range sensors

Authors: Lei Pan; Xi Zheng; Philip Kolar; Shaun Bangay

Addresses: School of IT, Deakin University, Geelong, VIC 3220, Australia ' School of IT, Deakin University, Geelong, VIC 3220, Australia ' School of IT, Deakin University, Geelong, VIC 3220, Australia ' School of IT, Deakin University, Geelong, VIC 3220, Australia

Abstract: The increasing popularity and availability of inexpensive ultrasonic sensors facilitates opportunities for tracking moving objects by using a cluster of these sensors. In this paper, we use a cluster of ultrasonic sensors connected to Raspberry Pis. Field tests indicate that the accuracy and reliability of individual sensors depends on the relative position of the tracked object. Hence, we employ data fusion and synchronisation techniques for trilateration to improve accuracy using a cluster of sensor nodes. We successfully conduct multiple runs tracking a moving object and report these field test results in this paper. Our average error is in the order of tens of centimetres, and some of our best results match published results for larger clusters.

Keywords: ultrasonic sensor; sensor network; object tracking; trilateration; data fusion.

DOI: 10.1504/IJSNET.2018.093965

International Journal of Sensor Networks, 2018 Vol.27 No.4, pp.268 - 280

Received: 22 Nov 2016
Accepted: 18 Aug 2017
Published online: 10 Aug 2018 *

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