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RF-Pick


Submitted to the ACM International Symposium on Wearable Computers, an academic conference with a 24% paper acceptance rate. We were one of 62 accepted papers to be awarded Best Paper

Abstract

Order picking accounts for 55% of the annual $60 billion spent on warehouse operations in the United States. Reducing human-induced errors in the order fulfillment process can save warehouses and distributors significant costs. We investigate a radio-frequency identification (RFID)-based verification method wherein wearable RFID scanners, worn on the wrists, scan passive RFID tags mounted on an item’s bin as the item is picked; this method is used in conjunction with a head-up display (HUD) to guide the user to the correct item. We compare this RFID verification method to pick-to-light with button verification, pick-to-paper with barcode verification, and pick-to-paper with no verification. We find that pick-to-HUD with RFID verification enables significantly faster picking, provides the lowest error rate, and provides the lowest task workload.

Contributions

  • Integration of novel wearable system with HUDs
  • Comprehensive and rigorous HCI user study
  • Embedded systems and networking programming
  • Application of software engineering principles to increase development speed and system robustness

Advisor: Professor Thad Starner, Technical Lead, Google Glass


© Pramod Kotipalli 2018

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