基于无人机的高速公路智能巡检及异常状态处理方法
By combining knowledge graphs and dynamic path planning in a closed-loop control technology, autonomous inspection and intelligent feedback learning of UAVs in complex environments are achieved, solving the problems of dynamic adaptation and safe flight path planning in existing technologies, and improving inspection efficiency and anomaly identification accuracy.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- ANHUI KONGAN INFORMATION TECH CO LTD
- Filing Date
- 2026-02-10
- Publication Date
- 2026-07-17
AI Technical Summary
Existing drone inspection technology struggles to achieve dynamic adaptive inspection in complex environments, lacks real-time environmental perception and safe flight path planning, and lacks a closed-loop feedback mechanism from anomaly detection to handling, making it difficult to continuously optimize the system.
By employing a closed-loop control technology that combines knowledge graphs and dynamic path planning, contextualized inspection tasks are generated by semantically decomposing natural language commands. Dynamic safety corridors are generated in real time, and three-dimensional potential field repulsion force is calculated. Combined with sensor configuration and flight mode optimization, the UAV achieves autonomous planning and intelligent feedback learning.
It improves the intelligence level and anomaly identification accuracy of inspection tasks, ensures the safety and detection efficiency of drones in complex environments, achieves seamless connection from large-scale rapid inspection to precise diagnosis of key points, and has the ability to self-evolve and continuously optimize.
Smart Images
Figure CN121963000B_ABST