Drone Airspace Maps Using 3D Building Buffers
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Solution Overview
Problem
Current systems face challenges in automatically routing unmanned aerial vehicles (UAVs) or drones through complex environments, particularly in defining safe navigable spaces around obstacles and adhering to regulatory airspaces.
Innovation Solution
A system that identifies three-dimensional geometries from building models, calculates a buffer space, and defines coordinates for a drone air space, allowing for the generation of navigation commands to guide drones safely through defined path segments while avoiding obstacles and adhering to airspace regulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a drone navigates close to buildings and obstacles to optimize route efficiency, then productivity improves, but the risk of collision and safety hazards increase
Solution Approach 1:
The system performs preliminary calculations to determine buffer spaces around buildings and obstacles before the drone begins navigation. These pre-computed safe zones are stored in the map database and used during route planning to ensure the drone maintains safe distances without real-time computation delays
Solution Approach 2:
The patent extends traditional 2D map navigation to 3D spatial reasoning by calculating buffer spaces in three-dimensional space around buildings and obstacles. This allows the drone to navigate efficiently through vertical and horizontal dimensions while maintaining safety margins
2Measurement precision
If the drone air space is precisely defined using building models and buffer spaces, then measurement precision improves, but device complexity increases
Solution Approach 1:
The system divides the complex task of airspace definition into separate modular components: building model identification, buffer space calculation, coordinate system transformation, and path segment association. Each component is independently implemented and stored in the map database for efficient retrieval
Solution Approach 2:
The system creates simplified coordinate representations of three-dimensional buffer spaces and stores them in the map database. These coordinate copies enable efficient route planning without requiring complex geometric calculations during actual navigation
Data Source
AI summary
Drone space is defined according to a building model and a buffer space. At least one three-dimensional geometry is identified from the building model. The buffer space is calculated from the three-dimensional geometry. Coordinates for a drone air space are defined based on the buffer space. At least one path segment may be identified based on the coordinates for the drone air space, and the coordinates for drone air space are stored in a map database in association with the at least one path segment.