AI Flight Planning for UAV Takeoff, Route, and Landing Schemes
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Solution Overview
Problem
Conventional flight simulation methods for unmanned aerial vehicles (UAVs) do not adequately consider various situations, leading to potential accidents due to insufficient input information and limited simulation results, which can result in human accidents or property damage.
Innovation Solution
A method and device that utilize an artificial intelligence model to generate flight plans for UAVs, considering factors like flight environment, traffic, and user preferences, by inputting departure and destination information, and generating multiple flight plans with associated scores based on preference information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional flight simulation methods are used with insufficient input information, then the simulation process is simple and quick, but the simulation accuracy and reliability are poor leading to potential accidents
Solution Approach 1:
The system performs preliminary actions by collecting comprehensive input information including departure location, destination, user preferences, and flight environment data before generating flight plans. This preliminary data gathering and processing ensures that the simulation is based on sufficient and accurate information, improving reliability while managing complexity through structured pre-processing
Solution Approach 2:
The flight plan management system acts as an intermediary between the user's requirements and the flight simulation process. It processes user preferences, generates multiple flight plans with different characteristics, and provides them to the simulation system, thereby bridging the gap between simple input and complex simulation requirements
2Loss of information
If conventional flight simulation provides limited results, then the output is simple and easy to process, but the information completeness is insufficient for comprehensive flight planning
Solution Approach 1:
The flight plan information is segmented into multiple distinct components including travel path, takeoff scheme, altitude climb scheme, arrival scheme, and landing scheme. Each component is generated and processed separately, allowing comprehensive information coverage while maintaining manageable processing through modular organization of flight plan elements
Solution Approach 2:
The system generates multiple flight plans by varying parameters such as travel path, altitude, and timing based on user preferences. This parameter variation approach provides comprehensive information about different flight options without requiring complete regeneration of entire flight plans, thus maintaining efficiency while improving information completeness
3Adaptability or versatility
If multiple flight plans are generated based on user preferences, then the user satisfaction and adaptability are improved, but the computational complexity and processing time increase
Solution Approach 1:
The system generates multiple flight plans by partially varying specific components such as travel path and altitude schemes while keeping other elements consistent. This partial action approach provides adaptability through multiple options without requiring complete regeneration of all flight plan parameters, thus reducing the time penalty compared to generating entirely new plans
Solution Approach 2:
Multiple flight plans are generated by changing specific parameters like departure time, altitude, and route based on user preferences. This parameter-based generation allows rapid creation of varied flight options without extensive computational effort, as it modifies existing plans rather than creating them from scratch
Data Source
AI summary
The present disclosure according to at least one embodiment provides a a method for managing, by a computing device, a flight plan of an unmanned aerial vehicle, the method comprising: receiving input information including a departure location and a destination of the unmanned aerial vehicle, inputting the input information into a pre-constructed artificial intelligence model, acquiring at least one of a travel path, a takeoff scheme, an altitude climb scheme at the departure location, an arrival scheme at the destination, or a landing scheme on the destination from the artificial intelligence model, and providing a flight plan including the acquired at least one of the travel path, the takeoff scheme, the altitude climb scheme at the departure location, the arrival scheme as the destination, and the landing scheme on the destination.