Novel Robust Parcel-Size Classification Using mmWave Radar

A novel robust package-height estimation and parcel-size classification scheme is proposed in this work. A pertinent prototype system consisting of a millimeter-wave radar, a shipment track, and a stepping motor has been built for proof of concept. Three new schemes using the range-profile data prod...

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Bibliographic Details
Published in:IEEE transactions on industrial informatics 2024-02, Vol.20 (2), p.2873-2883
Main Authors: Wu, Bo-Han, Fang, Shih-Hau, Wu, Hsiao-Chun
Format: Article
Language:English
Subjects:
Cameras
Classification
Clustering
Current measurement
Darkness
Density-based spatial clustering of applications with noise (DBSCAN)
Height
Hough transform
intelligent parcel processing
Inventory management
Millimeter wave communication
Millimeter waves
millimeter-wave (mmWave) radar
Packages
parcel-size classification
Prototypes
Radar
Radar detection
Radar tracking
Robustness
Stepping motors
Transforms
Ultrasonic variables measurement
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Description
Summary:A novel robust package-height estimation and parcel-size classification scheme is proposed in this work. A pertinent prototype system consisting of a millimeter-wave radar, a shipment track, and a stepping motor has been built for proof of concept. Three new schemes using the range-profile data produced by the mmWave radar, namely, the detection based-on cumulative distribution (DBCD) scheme, the detection based-on peak-value clustering (DBPC) scheme, and the DBCD-DBPC hybrid scheme are introduced here. For benchmark evaluation of the proposed new system, two practical scenarios, namely, the undisturbed scenario (no people is close to the system) and the disturbed scenario (some people is close to the system), are tested. This new system can overcome the serious drawback of the existing camera-assisted systems, which have to rely on sufficient lighting conditions, and operate normally even in complete darkness. Meanwhile, the proposed new system can accommodate parcels/packages in arbitrary orientations, which cannot be allowed by the current camera-assisted systems, during the parcel-size measurements. According to the test experiments, the proposed DBCD-DBPC hybrid scheme can reach up to a very high average classification accuracy of 96.4% for both undisturbed and disturbed scenarios. The proposed novel package-height estimation and parcel-size classification technique in this work can be very useful for intelligent inventory management and smart logistics in the future.
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2023.3298471