Multi-robot virtual simulation and adaptive parameter setting method based on digital twinning

By constructing a digital twin model that records the evolution of equipment status and an adaptive parameter tuning method, the problem of robotic arm trajectory deviation under static models was solved, and safe collaborative operation of multi-robotic arm systems under dynamic working conditions was realized.

CN122142987APending Publication Date: 2026-06-05DONGGUAN XINBAIREN ROBOT TECH CO LTD
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
DONGGUAN XINBAIREN ROBOT TECH CO LTD
Filing Date
2026-02-05
Publication Date
2026-06-05

AI Technical Summary

Technical Problem

Existing digital twin collaborative virtual simulation methods are based on static geometric models, which cannot accurately predict the nonlinear deformation of equipment under dynamic working conditions. This leads to deviations in the trajectory of the robotic arm during actual execution, causing equipment collisions or production interruptions.

Method used

A digital twin work area model capable of recording the cumulative evolutionary offset of equipment status is constructed. Multi-robot virtual simulation is performed by inputting the equipment status evolution trend to identify collaborative anomalies. Based on this, an adaptive parameter tuning method is constructed to generate collaborative parameter constraint targets and verify the stability of cross-domain collaboration under dynamic conditions.

Benefits of technology

It enables the early identification and avoidance of potential path interference and action chain breakage risks in virtual simulation, improves the robustness and safety of multi-robotic arm systems in dynamic environments, and ensures production stability.

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Abstract

The disclosure provides a multi-robot virtual simulation and adaptive parameter setting method based on digital twinning, including constructing a digital twinning work area model with the ability to record the cumulative evolution deviation of equipment state; inputting the equipment state evolution trend from the engineering site to the digital twinning work area model, performing multi-robot collaborative virtual simulation, and identifying collaborative abnormal events caused by dynamic evolution of equipment state; constructing a constraint target for the influence of state evolution on execution; performing adaptive parameter setting of collaborative parameters based on the constraint target in the digital twinning environment; injecting the set parameters into the physical multi-robot system to verify the cross-domain cooperation stability under dynamic state conditions, which can effectively integrate the equipment state evolution characteristics into the digital twinning and perform adaptive parameter setting based on the dynamic characteristics in collaborative virtual simulation, thereby fundamentally improving the execution reliability and safety of the multi-robot system in the dynamic physical environment.
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