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dc.contributor.advisorRoppel, Thaddeus
dc.contributor.authorZhang, Jian
dc.date.accessioned2016-12-10T03:35:44Z
dc.date.available2016-12-10T03:35:44Z
dc.date.issued2016-12-09
dc.identifier.urihttp://hdl.handle.net/10415/5504
dc.description.abstractThe use of RFID technology is increasing in retail stores, because it improves the performance of automated checkout, inventory and theft detection systems. In this dissertation, we present a novel implementation of a mobile robot that can perform retail inventory autonomously. The robot builds the map by its sensors for surrounding environments. With the built map, the robot can autonomously generate a path to cover all the target spaces in the environment, and then it can perform the RFID based inventory. Experimental results show that our robot can efficiently perform RFID based inventory in a retail environment with complex layout, and provides inventory accuracy that compares favorably to manual inventory. In this dissertation, we also present two RFID tag localization algorithms, the fixed power and variable power tag localization algorithms. Both algorithms are probabilistic in nature. For fixed-power localization, the robot collects RFID tag responses at a fixed power of RFID reader while it navigates in the store. After collecting enough responses for a RFID tag in different positions, the fixed power tag localization algorithm can estimate the location for this tag by recursive Bayes updating. The variable power tag localization algorithm needs the robot to collect the RFID tag responses at varying power levels of RFID reader from multiple locations. When a tag can be read at a high power level, but cannot be read at a low power level, we can determine relative range of the tag to the robot with higher resolution than a reader working at a fixed power level. After a number of successful tag responses are measured, the variable power tag localization algorithm calculates locations for each RFID tag. The experimental results show that the fixed power tag localization algorithm takes about 30 minutes to estimate all the location of items in our mock retail store, in contrast, the variable method needs about 6 hours to complete the same task. The variable power tag localization algorithm provides better localization accuracy, the average error is about 0.5 meter. The fixed power tag localization algorithm provides about 1.5 meter localization accuracy. Therefore, two algorithms are fitted for two different application scenarios: The fix power tag localization algorithm can be used to quickly estimate the location of merchandise, and the variable power tag localization algorithm could be deployed for a scenario where more precise localization result is needed.en_US
dc.rightsEMBARGO_GLOBALen_US
dc.subjectElectrical and Computer Engineeringen_US
dc.titleMobile Robot for Retail Inventory Using RFIDen_US
dc.typePhD Dissertationen_US
dc.embargo.lengthMONTHS_WITHHELD:25en_US
dc.embargo.statusEMBARGOEDen_US
dc.embargo.enddate2018-12-31en_US


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