Welding robot system based on body perception and intelligent route generation method
By acquiring and fusing multi-source data through the embodied perception module and the fusion processing module, the problem of insufficient data adaptability in complex weld welding is solved, generating a high-precision, adaptive welding route to ensure the stability and consistency of welding quality.
Patent Information
- Application Number
- CN202610107386.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-01-27
- Publication Date
- 2026-02-27
- Estimated Expiration
- 2046-01-27
AI Technical Summary
In complex weld welding scenarios, existing technologies struggle to synchronize the physical welding scene with the virtual model in real time. During the multimodal data fusion process, core features are easily obscured by redundant information, resulting in insufficient adaptability of path planning to actual working conditions and a lack of welding quality stability.
Multimodal data is acquired using an embodied perception module. Data is collected in parallel through a basic multimodal sensing unit, a bionic compound eye vision module, and a supplementary sensing unit. This is combined with low-pass filtering, adaptive Gaussian filtering, CLAHE algorithm for noise reduction and enhancement, homogeneous transformation matrix coordinate unification, and Kalman filter data fusion to achieve comprehensive capture and unification of multi-source data. Feature extraction and deep fusion are performed using a 3D attention fusion submodule, a digital twin mapping submodule, and a feature fusion submodule to generate a comprehensive feature set that includes weld features, molten pool state, and environmental adaptability. A progressive design of initial path planning, path optimization, and hierarchical correction is adopted to generate a smooth and adaptive welding path, and closed-loop control is achieved through an execution feedback module.
It achieves high-precision, all-round capture of multi-source data such as weld seam 3D point cloud, RGB image, and temperature distribution, improving the accuracy of feature fusion and scene adaptability. The generated welding route is smooth and adaptive, adapting to the needs of complex welding scenarios and ensuring the stability and consistency of welding quality.