一种基于工业视觉的机器人轨迹规划方法及系统
By synchronously acquiring and processing data from multi-source heterogeneous vision sensors, combined with confidence-weighted fusion and online deviation estimation, the problem of unstable pose estimation for industrial robots in complex environments was solved, achieving high-precision trajectory tracking and stable operation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ZHEJIANG HEHUI ROBOT TECHNOLOGY CO LTD
- Filing Date
- 2026-06-17
- Publication Date
- 2026-07-17
AI Technical Summary
Existing industrial robot vision sensors are susceptible to changes in lighting, reflections from metal surfaces, and occlusions in complex industrial environments, resulting in low reliability of pose estimation and difficulty in achieving high-precision trajectory tracking and stable operation in unstructured chemical conditions.
Data is collected synchronously using multi-source heterogeneous vision sensors. Operating parameters are extracted for sensor adjustment and redundancy degradation. An online dynamic deviation estimation model is constructed by combining calibration matrix mapping and confidence weighted fusion. Trajectory correction is performed through fifth-order polynomial interpolation.
It effectively overcomes environmental interference, ensures the robot's stable operation under strong environmental interference conditions, improves pose estimation accuracy and trajectory tracking accuracy, avoids mechanical abrupt changes, and achieves high-precision online closed-loop stable tracking.
Smart Images
Figure CN122401451A_ABST