Indoor UAV Positioning via Coordinate Transformation
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Solution Overview
Problem
Existing UAV software faces challenges with localization, path planning, and waypoint flight in indoor environments due to the unavailability of GPS and the lack of onboard systems for accurately tracking movement in the x-y plane.
Innovation Solution
A positioning system that generates GPS-based indoor flight paths for UAVs by creating a digital map of the indoor environment using spatial data from sensors like LIDAR, converting it into a geographic coordinate map, and formatting the coordinates in GPS and NMEA formats to guide the UAV accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS is used for UAV localization and path planning, then positioning accuracy is improved, but GPS is unavailable in indoor environments
Solution Approach 1:
The patent introduces an intermediary coordinate transformation system that converts indoor spatial coordinates to GPS-compatible coordinate formats. This mediator layer allows existing GPS-based UAV software to function in indoor environments by translating between indoor spatial reference frames and GPS coordinate systems, without requiring fundamental changes to the UAV's navigation stack.
Solution Approach 2:
The patent creates a virtual GPS coordinate system that mirrors the structure and format of real GPS coordinates but is adapted for indoor use. By copying the familiar GPS coordinate format and transformation logic, the system enables indoor navigation to work with existing GPS-based flight software, path planning algorithms, and waypoint systems without requiring complete system redesign.
2Measurement precision
If external cameras and calibration systems are used for indoor positioning, then positioning capability is improved, but device complexity and computing resources increase
Solution Approach 1:
The patent enables the UAV to use its existing onboard sensors (accelerometers, gyroscopes, barometers) to perform self-localization through sensor fusion and dead reckoning. By leveraging already-present sensors and algorithms, the system achieves indoor positioning capability without requiring additional external cameras, markers, or calibration infrastructure, thus avoiding increased device complexity.
3Ease of operation
If existing UAV software is used without modifications, then software compatibility is maintained, but indoor flight path accuracy deteriorates due to lack of GPS
Solution Approach 1:
The patent addresses the dimensional mismatch between indoor spatial coordinates and GPS coordinate systems by implementing a coordinate transformation framework that maps between different reference frames. This dimensional transformation allows existing GPS-based software to interpret indoor position data correctly, maintaining software compatibility while achieving accurate indoor flight paths through mathematical coordinate conversion.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution allows existing UAV software to implement accurate indoor flight paths, conserving computing resources by avoiding the need for external cameras and extensive calibration, and enabling efficient navigation through indoor spaces.
Implementation Method 1
spatial data from sensors like LIDAR
Implementation Method 2
LIDAR device...receive spatial data corresponding to an interior of a building
Data Source
AI summary
In some implementations, a device may receive spatial data corresponding to an interior of a building and objects located in the interior of the building. The device may generate a digital map of the interior of the building based on the spatial data. The device may generate a geographic coordinate map of the interior of the building. The device may receive, from a sensor mounted on an uncrewed aerial vehicle (UAV), sensor data indicating three-dimensional geographic points. The device may compare the sensor data to the geographic coordinate map to localize the UAV on the geographic coordinate map. The device may generate coordinate data indicating geographic coordinates associated with the geographic coordinate map and formatted in a global positioning system coordinate format and a National Marine Electronics Association format. The device may transmit, to a controller of the UAV, at least a subset of the coordinate data.