未来工厂开放环境下工业机器人运动平稳性分析方法
By combining sparse grids and mixed probability distribution models with Bayesian sequence update methods, the problem of multi-source uncertainty in motion stability analysis of industrial robots in open environments of future factories is solved, achieving high-precision and efficient motion stability assessment.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- ZHEJIANG UNIV
- Filing Date
- 2024-04-22
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies cannot effectively assess the impact of multi-source uncertainties on the motion stability of industrial robots in the open environment of future factories, resulting in simple analytical models with insufficient computational accuracy and efficiency.
By combining a sparse grid method and a mixed probability distribution model with a Bayesian sequence update method, the uncertainty of motion speed deviation is quantified by constructing an industrial robot motion speed deviation function and a failure probability characterization model, and accurate evaluation is performed using fractional exponential moments and a mixed probability distribution model.
It enables accurate assessment of the motion stability of industrial robots, reduces calculation errors, and improves the accuracy and efficiency of the analysis model, making it suitable for motion stability analysis of industrial robots in open factory environments of the future.
Smart Images
Figure CN118386228B_ABST