UAV Flight Path Planning for Adaptive Multi-Aircraft Coverage
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Solution Overview
Problem
Current UAV flight planning systems lack the ability to dynamically adjust flight paths in response to environmental changes and obstacles, and do not efficiently manage power supply and coordination between multiple aircraft during operations.
Innovation Solution
The system plans and adjusts flight paths by dividing surfaces into sections, using GPS coordinates and real-time data to avoid obstacles and adapt to environmental conditions, while also considering power supply refilling and coordinating multiple aircraft operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the flight path is planned to cover all flight sections, then the area coverage is improved, but the flight time and energy consumption increase due to possible detours
Solution Approach 1:
The surface is divided into multiple flight sections, each representing a discrete area to be covered. The system plans the flight path by segmenting the overall coverage area into manageable sections, allowing for systematic coverage while optimizing the sequence to minimize total flight time and energy consumption.
2Reliability
If the flight path is adjusted to avoid obstacles and adapt to environmental conditions, then the safety and reliability are improved, but the flight path complexity and computation requirements increase
Solution Approach 1:
The flight path is designed to be dynamically adjustable rather than fixed. The system can modify the flight path in real-time to avoid obstacles and adapt to changing environmental conditions, ensuring safety while managing complexity through adaptive algorithms that respond to actual conditions rather than pre-planning for all contingencies.
Solution Approach 2:
The system incorporates feedback mechanisms to detect obstacles and environmental conditions during flight, then adjusts the flight path accordingly. This feedback loop allows the system to maintain safety by responding to actual conditions while managing computational complexity through incremental adjustments rather than complete re-planning.
3Productivity
If multiple aircraft are coordinated to operate simultaneously, then the productivity is improved, but the coordination complexity and communication requirements increase
Solution Approach 1:
Multiple aircraft are merged into a coordinated system that operates simultaneously over different flight sections. The system combines the capabilities of multiple aircraft to cover larger areas more efficiently, managing coordination complexity through centralized or distributed control algorithms that allocate sections and manage interactions between aircraft.
4Use of energy by moving object
If the flight path is optimized to minimize detours, then the energy consumption is reduced, but the area coverage may be compromised
Solution Approach 1:
The system performs preliminary planning of the flight path to optimize the sequence of visiting flight sections, minimizing detours and energy consumption. By pre-calculating the optimal path that covers all required sections, the system ensures complete area coverage while reducing unnecessary energy expenditure compared to ad-hoc routing decisions.
Data Source
AI summary
A method for supporting aerial operation over a surface includes obtaining a representation of the surface that comprises a plurality of flight sections, and identifying a flight path based on the representation of the surface. The flight path allows an aircraft, when following the flight path, to conduct an operation over the flight sections.