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公开(公告)号:US11666944B1
公开(公告)日:2023-06-06
申请号:US16886055
申请日:2020-05-28
Applicant: Amazon Technologies, Inc.
Inventor: Jose Luis De La Rosa , Larry Joe Robb , Maxim P. Hoffman , Joshua Martin Middleton , Stephanie Tomasetta , Roland J. Menassa , Justin Stone , Molly Nawalinski , Fernando Zumbado , Duncan Pratt , Jon David DeFant
Abstract: Systems, methods, and computer-readable media are disclosed for detection of overfilled containers in sortation systems. In one embodiment, an example container capacity detection system for use with an item sortation machine may include a first sensor positioned to detect a remaining capacity of a first container in the item sortation system, and a controller. The controller may be configured to determine, using the first sensor, that the remaining capacity of the first container is less than or equal to a first threshold, and to send a signal.
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公开(公告)号:US11969760B1
公开(公告)日:2024-04-30
申请号:US17545945
申请日:2021-12-08
Applicant: Amazon Technologies, Inc.
Inventor: Jose Luis De La Rosa , Ting Xu , Duncan Pratt
CPC classification number: B07C5/34 , B07C5/16 , G06N20/00 , G06T7/0004 , G06V20/64 , G07C3/14 , G06T2207/20081 , G06T2207/30108
Abstract: Disclosed are systems and methods for detecting defects during the handling and processing of items at a material handling facility. Embodiments of the present disclosure can be implemented at material handling to detect quality defects during processing of items in connection with fulfillment operations that may be designed to receive, store, sort, pick, pack, and ship items. Embodiments of the present disclosure provides a plurality of sensors and a trained machine learning model configured to provide real-time acquisition and analysis of item information to facilitate detection and mitigation of processing quality defects.
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公开(公告)号:US11305949B1
公开(公告)日:2022-04-19
申请号:US16532863
申请日:2019-08-06
Applicant: Amazon Technologies, Inc.
Inventor: Roland J. Menassa , Larry Joe Robb , Vatsal Mehta , Duncan Pratt , Max Alfonso Bruccoleri , Robert Brown
Abstract: Automated tray handling systems and methods may include robotic systems having various end effectors to move trays relative to item sortation systems. For example, the robotic systems may include robotic arms and gantry systems. In addition, the various end effectors may include dual end effectors and passthrough end effectors. The dual end effectors may lift, move, and place trays by engaging and clamping onto flanges of the trays. The passthrough end effectors may lift, move, and place trays through an interior of the end effectors by engaging and pulling or pushing flanges, edges, or other surfaces of the trays. The various automated tray handling systems and methods may increase the speed and efficiency of such processes while also reducing or minimizing the space required for such systems.
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