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US Patent RE47108 Automated warehousing using robotic forklifts

Patent RE47108 was granted and assigned to Cybernet Systems Corporation on October, 2018 by the United States Patent and Trademark Office.

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Is a
Patent
Patent

Patent attributes

Patent Applicant
Cybernet Systems Corporation
Cybernet Systems Corporation
Current Assignee
Cybernet Systems Corporation
Cybernet Systems Corporation
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
RE47108
Patent Inventor Names
Glenn J. Beach0
Steve Rowe0
Charles J. Jacobus0
Date of Patent
October 30, 2018
Patent Application Number
15439301
Date Filed
February 22, 2017
Patent Citations Received
‌
US Patent 11872706 Systems and methods for process tending with a robot arm
0
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US Patent 12122367 Systems and methods for operating one or more self-driving vehicles
0
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US Patent 12091303 Motorized vehicles having sensors and methods of operating the same
0
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US Patent 11685049 Robot localization using variance sampling
0
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US Patent 11969882 Material handling vehicle behavior modification based on task classification
0
Patent Primary Examiner
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William Doerrler
Patent abstract

A system for automated inventory management and material handling removes the requirement to operate fully automatically or all-manual using conventional vertical storage and retrieval (S&R) machines. Inventory requests to place palletized material into storage at a specified lot location or retrieve palletized material from a specified lot are resolved into missions for autonomous fork trucks, equivalent mobile platforms, or manual fork truck drivers (and their equipment) that are autonomously or manually executed to effect the request. Automated trucks plan their own movements to execute the mission over the warehouse aisles or roadways sharing this space with manually driven trucks. Automated units drive to planned speed limits, manage their loads (stability control), stop, go, and merge at intersections according human driving rules, use on-board sensors to identify static and dynamic obstacles, and human traffic, and either avoid them or stop until potential collision risk is removed.

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