WareVision: CNN Barcode Detection-Based UAV Trajectory Optimization for Autonomous Warehouse Stocktaking

Ivan Kalinov, Alexander Petrovsky, Valeriy Ilin, Egor Pristanskiy, Mikhail Kurenkov, Vladimir Ramzhaev, Ildar Idrisov, Dzmitry Tsetserukou

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)

Abstract

This letter presents a heterogeneous Unmanned Aerial Vehicle (UAV)-based robotic system for real-time barcode detection and scanning using Convolutional Neural Networks (CNN). The proposed approach improves the UAV's localization using scanned barcodes as landmarks in a real warehouse with low-light conditions. Instead of using the standard overlapping snake-based grid (OSBG) trajectory, we implement a novel approach for flight-path optimization based on barcode locations. This approach reduces the time of warehouse stocktaking and decreases the number of mistakes in barcode scanning.

Original languageEnglish
Article number9145639
Pages (from-to)6647-6653
Number of pages7
JournalIEEE Robotics and Automation Letters
Volume5
Issue number4
DOIs
Publication statusPublished - Oct 2020

Keywords

  • AI-based methods
  • computer vision for automation
  • Inventory management
  • multi-robot systems
  • object detection
  • segmentation and categorization

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