基于惯性导航的车辆导航方法及系统
By constructing a hypergraph structure and fusing multi-source data using a hypergraph neural network algorithm, the positioning accuracy and path planning problems of traditional vehicle navigation in complex environments are solved, achieving efficient and reliable navigation services.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SICHUAN KETAI INTELLIGENT ELECTRONICS CO LTD
- Filing Date
- 2025-07-15
- Publication Date
- 2026-07-17
AI Technical Summary
Traditional vehicle navigation technology suffers from decreased positioning accuracy in complex environments, cannot comprehensively utilize multi-source heterogeneous data, and lacks dynamic collaborative optimization in its navigation models, resulting in insufficient adaptability and reliability.
A hypergraph structure is constructed that integrates inertial measurement data, map data, and environmental data. The hypergraph neural network algorithm is used for feature extraction and learning. Combined with a multi-source heterogeneous data solution model, the positioning accuracy is dynamically adjusted, and the optimal driving path is planned.
It achieves high-precision positioning and navigation in complex environments, enhances the system's adaptability and reliability in different scenarios, and provides high-quality navigation services.
Smart Images
Figure CN120820151B_ABST