Aerial Vehicle Flight Path Planning for Multi-Target Acquisition
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Solution Overview
Problem
Current methods for generating flight paths for aerial vehicles are inefficient and require operator intervention, especially when dealing with multiple targets, including moving targets and forbidden areas, and do not optimize the path based on target priority.
Innovation Solution
A method using processor and memory circuitry to determine interaction areas for aerial vehicles, generating optimized flight paths by connecting waypoints in interaction areas of multiple targets, avoiding forbidden areas, and updating paths in real-time to account for moving targets, while prioritizing target acquisition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If current methods are used to generate flight paths for multiple targets, then operator intervention is required, but this increases time consumption and reduces productivity
Solution Approach 1:
The system enables the aerial vehicle to autonomously generate and update its own flight path by processing target position data and calculating optimized routes automatically, eliminating the need for continuous operator intervention and significantly reducing time loss
Solution Approach 2:
The patent replaces manual operator-based flight path planning with an automated computational system that uses processor and memory circuitry to calculate optimal routes, substituting human mechanical decision-making with automated algorithmic processing
2Adaptability or versatility
If traditional flight path methods are used, then simple paths can be generated, but they cannot optimize for target priority or handle moving targets effectively
Solution Approach 1:
The flight path generation system is designed to be dynamic, continuously updating the flight path in real-time based on changing target positions and priorities, allowing the system to adapt to moving targets and varying mission requirements without becoming unmanageably complex
Solution Approach 2:
The system optimizes flight paths by dynamically changing parameters such as target priority weights, interaction area dimensions, and path optimization criteria, enabling flexible adaptation to different mission scenarios while maintaining systematic control
3Reliability
If comprehensive target acquisition is performed for all targets, then complete coverage is achieved, but the flight path length increases
Solution Approach 1:
The system defines specific interaction areas around each target with customized dimensions based on the aerial vehicle's acquisition capabilities, allowing focused engagement with each target rather than requiring comprehensive coverage of entire target regions, thus reducing overall flight path length while maintaining acquisition reliability
Solution Approach 2:
The system determines that visiting each target's interaction area is sufficient for mission completion without requiring the aerial vehicle to hover or perform multiple maneuvers at each target, achieving adequate target acquisition with minimized flight path expenditure
Data Source
AI summary
A method comprising, by a processor and memory circuitry, for an aerial vehicle comprising a payload operative to perform an interaction with a target: for each target of a plurality of targets, determining an interaction area based on a position of the target, wherein, for each position of the aerial vehicle located in the interaction area of the target, the interaction between the payload and the target is enabled according to an operability criterion, generating a series of connections, wherein each connection comprises at least one waypoint located in an interaction area of a target of the plurality of targets and at least one waypoint located in an interaction area of another different target of the plurality of targets, wherein each interaction area comprises a waypoint of at least one connection of the series of connections, and obtaining a flight path for the aerial vehicle using the series of connections.