3D Drone Flight Planning Around Structures Without GPS
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Solution Overview
Problem
Current drone flight planning systems are limited by their reliance on 2D maps and discrete waypoints, making it difficult to plan missions around 3D structures, especially in GPS-denied areas such as indoor environments.
Innovation Solution
The system uses a 3D model of a location to plan time-optimal and resource-efficient trajectories for drones, allowing for optimization of flight time and survey quality, and enabling planning in GPS-denied areas by refining flight trajectories based on updated survey data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If 2D maps and discrete waypoints are used for flight planning, then the system is simple to operate, but it cannot plan missions around 3D structures in GPS-denied areas
Solution Approach 1:
The patent transitions from 2D map-based planning to 3D model-based planning. The system generates three-dimensional models of the environment and plans flight trajectories in 3D space, allowing drones to navigate around complex structures. This dimensional upgrade enables GPS-denied operation by using visual features and spatial relationships from the 3D model instead of GPS coordinates.
Solution Approach 2:
The system creates a digital copy (3D model) of the physical environment that can be used for planning and navigation. This virtual replica allows the drone to understand and navigate around 3D structures without needing physical presence or GPS signals, solving the adaptability problem while keeping the actual hardware relatively simple.
2Reliability
If traditional waypoint navigation is used, then the system is reliable in GPS-available areas, but it fails in GPS-denied areas such as indoors
Solution Approach 1:
The system creates a universal navigation approach that works both in GPS-available and GPS-denied environments. The 3D model-based planning system can operate with or without GPS signals, making the navigation system multi-functional and adaptable to different operational conditions. This eliminates the reliability limitation of GPS-dependent systems while expanding operational versatility.
Solution Approach 2:
The 3D environmental model serves as an intermediary between the drone and the physical environment. Instead of relying directly on GPS signals (which fail indoors), the system uses the 3D model as a mediator to provide spatial information and navigation guidance, enabling reliable operation in GPS-denied areas while maintaining compatibility with GPS-available environments.
3Productivity
If 3D model-based trajectory optimization is implemented, then flight time and survey quality are optimized, but the computational complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-generating 3D models of the environment and pre-optimizing flight trajectories before the actual survey mission. This advance preparation allows the drone to execute pre-planned optimal paths without real-time computational burden, achieving high survey efficiency while managing computational complexity through offline processing.
Solution Approach 2:
The system incorporates feedback mechanisms where survey data collected during flight is used to refine and update the 3D model, which in turn improves subsequent trajectory optimizations. This iterative feedback loop enhances survey quality and efficiency over time while distributing computational complexity across multiple flight missions rather than requiring all computations to occur in real-time.
Data Source
AI summary
A method for controlling a plurality of drones to survey a location, the method comprising, at a computing system: automatically generating preliminary flight plans for a plurality of drones to survey the location based on a 3D model; receiving survey data from the plurality of drones as the plurality of drones are surveying the location based on the preliminary flight plans; updating the 3D model based on the survey data received from the plurality of drones; and automatically updating at least a portion of the flight plans based on the updated 3D model