A Neural Network Approach for AGV Localization Using Trilateration

• Type: Article in International Conference Proceedings Book
• Date: 2009

Authors

Abílio Azenha (Author) FEUP; Adriano Carvalho (Author) FEUP

Conference proceedings International

Title: IECON: 2009 35TH ANNUAL CONFERENCE OF IEEE INDUSTRIAL ELECTRONICS, VOLS 1-6

Pages: 2551-2554

35th Annual Conference of the IEEE-Industrial-Electronics-Society (IECON 2009)

Porto, PORTUGAL, NOV 03-05, 2009

Indexing

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Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

CORDIS: Technological sciences > Engineering > Control engineering > Robótica Robotics

Other information

Authenticus ID: P-003-QFK

DOI: 10.1109/iecon.2009.5415429

Abstract (EN): This paper describes radio frequency (RF) localization for indoors quasi-structured environments using an artificial neural network (ANN) approach. Making use of available communications sub-system based on wireless protocols, received signal strength indication (RSSI) can become a measurement that sources ANN schemes which emulate trilateration for indoors RF localization. Some ANN learning results are presented which give encouraging insights for going on applying ANN approach to automated guided vehicles (AGVs) indoors localization.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 4