首页|Patent Application Titled "Modular,Cost-Effective,Field Repairable Chassis And Mechanical Components For Heavy Duty Autonomous Robot" Published Online (USPTO 20240083504)

Patent Application Titled "Modular,Cost-Effective,Field Repairable Chassis And Mechanical Components For Heavy Duty Autonomous Robot" Published Online (USPTO 20240083504)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-According to news reporting originatin g from Washington,D.C.,by NewsRx journalists,a patent application by the inve ntors Chrysanthakopoulos,Georgios (Seattle,WA,US); Felser,Adlai (Seattle,WA ,US),filed on November 14,2023,was made available online on March 14,2024.The assignee for this patent application is Dcentralized Systems Inc. (Seattle,Washington,United States). Reporters obtained the following quote from the background information supplied by the inventors: " "Field of the Invention "This invention relates to a configurable frame body having a single panel,uni- member U-shaped bended frame where the frame has a base,a first side,a first s ide upper plate,a second side,a second side upper plate,a first end,a second end and a plurality of cutouts positioned at predetermined locations in the U-s haped bended frame. Specifically,this frame is used for a ground utility robot,autonomous robot,or autonomous tractor,and more specifically to a chassis and frame design,wheel attachments,batteries,solar panels and solar panel attach ments,implement attachments,component attachments and accessory attachments to the robot. It also teaches a cost effective,reduced part count,high strength chassis,drive unit and modular assemblies for autonomous multi-purpose electric outdoor land care robot and or to human operated machines or hybrid machines th at are easily assembled,simple in design,small in part count and that are rapi dly field-repairable.

Autonomous RobotBusinessDcentralized Systems Inc.Emerging TechnologiesMachine LearningNano-robotRobotRobot ics

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Mar.29)