A dual-robot measurement and machining integrated system error collaborative compensation method

By constructing an error collaborative compensation method for a dual-robot measurement and processing integrated system, the problem of unified modeling and collaborative compensation of multi-source errors in multi-robot collaborative systems is solved, achieving efficient error identification and compensation, and improving the collaborative accuracy and stability of the system.

CN122425608APending Publication Date: 2026-07-21DALIAN UNIV OF TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
DALIAN UNIV OF TECH
Filing Date
2026-04-23
Publication Date
2026-07-21

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Abstract

The application of a double-robot measurement and processing integrated system error collaborative compensation method belongs to the field of robot measurement-grinding and polishing automation processing technology, and relates to a double-robot measurement and processing integrated system error collaborative compensation method. The method is based on a measurement and processing integrated double-robot system for error collaborative compensation; the system is composed of a position measurement unit, a clamping unit and a contour machining unit. The method first constructs a measurement and processing integrated double-robot system, and then constructs a multi-stage error transmission chain of the robot system. System differential error identification and multi-stage solution of the differential error chain are performed. Finally, the measurement and processing integrated system error collaborative compensation is performed. The method realizes the synchronous identification and collaborative compensation of multiple types of errors, one-time solution of multiple source errors, avoids the transmission and accumulation of errors in the multi-stage processing process, effectively improves the overall collaboration accuracy of the double-robot system, and significantly reduces the system deployment cost and experimental complexity.
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