DocumentCode :
3426152
Title :
FineMesh: High-Density Sampling Platform Using an Autonomous Robot
Author :
Kawauchi, Kiyoto ; Rekimoto, Jun
Author_Institution :
Grad. Sch. of Interdiscipl. Inf. Studies, Univ. of Tokyo, Tokyo, Japan
fYear :
2012
fDate :
20-23 Nov. 2012
Firstpage :
477
Lastpage :
486
Abstract :
Mobile devices have become wide spread, as a result of improvements in hardware and communication technologies. These devices are equipped with some sensors to protect themselves. In recently years, technologies have been developed that allow a device to recognize its environments using sensor data are developed. However, in an indoor environment, there are objects that affect sensor data. Therefore, sensors required either calibration to adjust their behavior, or clarification of the cause of incorrect behavior. This requires large amounts of sensor data to be collected indoors, but it is difficult for humans to collect this data in the indoor environment. Methods of data collection by humans are limited by the number of observation points that can reasonably be attained. In this paper, we proposed the Fine Mesh method for dense sampling using an autonomous robot. Our proposed method aims to increase the number of observation points. We constructed an autonomous robot that collects signals at 10 cm intervals using positioning estimates with camera images. To confirm the effect of collecting signals in more detail, we evaluate the accuracy of a Wi-Fi indoor positioning system constructed by our robot. We then use our platform to evaluate the efficacy of detailed signal collection.
Keywords :
Global Positioning System; calibration; data acquisition; indoor radio; mobile computing; mobile robots; signal sampling; wireless LAN; FineMesh method; Wi-Fi indoor positioning system; autonomous robot; calibration; indoor environment; mobile device; sampling platform; sensor data collection; signal collection; size 10 cm; Accuracy; Databases; Estimation; IEEE 802.11 Standards; Robot sensing systems; Digital Compass; Indoor Environments; Location Positioning; Walking Robot; Wi-Fi;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Green Computing and Communications (GreenCom), 2012 IEEE International Conference on
Conference_Location :
Besancon
Print_ISBN :
978-1-4673-5146-1
Type :
conf
DOI :
10.1109/GreenCom.2012.56
Filename :
6468354
Link To Document :
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