UAV Airport Path Planning for Autonomous Charging Stopovers
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Solution Overview
Problem
Conventional unmanned aerial vehicles (UAVs) lack the ability to select an appropriate UAV airport based on specific conditions, limiting their ability to fly long distances efficiently.
Innovation Solution
A method and system that enable a UAV to obtain status information, request and receive UAV airport information sets, perform weight value calculations to determine optimal paths, and reserve parking at UAV airports, allowing for efficient long-distance flight planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of moving object
If an unmanned aerial vehicle uses a conventional charging platform to extend its range, then the flight duration is improved, but the system complexity increases due to manual airport selection and coordination
Solution Approach 1:
The UAV autonomously selects airports, calculates optimal paths, reserves parking spaces, and coordinates with airports without human intervention. The system performs self-service by automatically managing the entire charging stopover process, from airport selection to parking reservation and real-time monitoring during flight.
Solution Approach 2:
The system performs preliminary actions by pre-calculating optimal paths, pre-reserving parking spaces at selected airports, and pre-coordinating with airport servers before the UAV arrives. This ensures that when the UAV needs to charge, everything is already prepared and coordinated.
2Ease of operation
If an unmanned aerial vehicle autonomously selects airports and calculates optimal paths, then the ease of operation is improved, but the computational requirements and processing time increase
Solution Approach 1:
The system pre-calculates optimal paths and pre-reserves parking spaces before the UAV needs to charge. By performing these computations in advance rather than in real-time during flight, the system reduces processing time and computational burden during critical flight phases.
Solution Approach 2:
The patent replaces manual airport selection and path planning with automated algorithms. The UAV's onboard computer or ground control system uses computational methods to automatically determine optimal airports and flight paths, substituting human decision-making with machine-based optimization.
3Reliability
If the system reserves parking spaces in advance at multiple airports, then the reliability of flight planning is improved, but the use of energy increases due to continuous communication and data processing
Solution Approach 1:
The system reserves parking spaces and coordinates with airports in advance during low-energy periods (ground phase or between flights). By performing communication-intensive operations before flight rather than during flight, the system ensures reliability while minimizing energy consumption during critical flight phases.
Solution Approach 2:
The system implements real-time monitoring and feedback mechanisms to track the UAV's status, airport availability, and path execution. This feedback loop allows the system to make dynamic adjustments and ensures reliable flight planning while optimizing energy usage based on actual flight conditions and deviations.
Data Source
AI summary
The present invention provides a method and system for an unmanned aerial vehicle (UAV) to pass through an UAV airport, and relates to the field of unmanned aerial vehicle airport technologies. The method for an UAV to pass through an UAV airport includes: obtaining status information of an UAV; sending a request for an UAV airport information set to an index server; receiving the UAV airport information set sent by the index server; obtaining, through weight value calculation based on the UAV airport information set, a connected UAV airport station set; calculating and determining a reachable optimal-weight-value sequentially connected path set; and determining a flight path based on a weight value combination condition. In the present invention, an UAV can implement convenient self-parking and charging on the premise that a weight value combination condition is satisfied, so that a long-distance flight demand can be satisfied.