UAV Survey Flight Patterns for Turn Radius and Wind Constraints
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Solution Overview
Problem
Current UAV flight planning systems require significant user input and do not efficiently account for constraints such as minimum turning radius and wind conditions, leading to suboptimal flight paths and increased flight time or distance during inspections of large areas like agricultural or mining sites.
Innovation Solution
A flight planning system that determines a flight pattern with minimal user input, constraining UAVs by minimum turning radius and adapting to wind conditions, by dividing areas into parallel inspection legs with specific widths and orders, and modifying plans based on real-time weather information to optimize sensor data collection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a UAV follows a pre-programmed flight plan with manual user input, then the flight path can be controlled, but the flight time and distance increase significantly
Solution Approach 1:
The flight planning system automatically generates optimized flight patterns by self-calculating parallel inspection legs, turn radii, and traversal directions based on area boundaries and UAV constraints, eliminating the need for manual user input while minimizing flight time and distance
2Productivity
If the UAV performs tight turns to cover the area efficiently, then the inspection coverage improves, but the UAV may exceed its minimum turning radius constraint
Solution Approach 1:
The system dynamically adjusts flight path parameters including turn radii, leg spacing, and traversal directions to ensure all turns meet the minimum turning radius constraint while maintaining optimal inspection coverage through automated optimization algorithms
3Device complexity
If the flight plan does not account for wind conditions, then the planning process is simpler, but the UAV may experience drift and require additional flight distance to compensate
Solution Approach 1:
The system obtains weather information and wind conditions in advance during flight plan generation, pre-calculating compensated flight paths that account for expected wind drift, allowing the UAV to maintain accurate positioning without real-time adjustments or additional flight distance
Data Source
AI summary
Methods, systems and apparatus, including computer programs encoded on computer storage media for an unmanned aerial vehicle aerial survey. One of the methods includes receiving information specifying a location to be inspected by an unmanned aerial vehicle (UAV), the inspection including the UAV capturing images of the location. Information describing a boundary of the location to be inspected is obtained. Inspections to be assigned to the location are determined, with the inspection legs being parallel and separated by a particular width. A flight pattern is determined based on a minimum turning radius of the UAV, with the flight pattern specifying an order each inspection leg is to be navigated along, and a direction of the navigation.