UAV Crash Probable Region Dynamics
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Solution Overview
Problem
Conventional methods face difficulties in appropriately setting a no-fall region for unmanned air vehicles (UAVs) when objects such as moving people or cars are present, leading to potential damage from unforeseen circumstances.
Innovation Solution
The UAV is equipped with a camera for vertical imaging and circuitry that detects objects in the crash probable region, controlling the flight to avoid these objects and dynamically changing the region based on flight control results, incorporating sensors for altitude, wind speed, and object detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a no-fall region is set in advance for UAV flight control, then damage from fall is reduced, but the system cannot appropriately handle moving objects such as walking persons or moving cars
Solution Approach 1:
The patent applies dynamics by transitioning from a static no-fall region to a dynamic crash probable region that moves and changes shape based on real-time UAV position, altitude, and wind conditions. The region is continuously updated during flight to maintain accuracy in predicting where the UAV would crash if it lost control, thereby adapting to moving objects and changing environmental conditions.
Solution Approach 2:
The system uses feedback by continuously monitoring UAV flight state, altitude, and wind conditions to update the crash probable region in real-time. This closed-loop approach allows the no-fall region to adapt to current flight conditions and moving objects, improving both reliability and adaptability simultaneously.
2Ease of operation
If the no-fall region is set in advance, then the flight route can be planned, but the region cannot be changed according to flight control results
Solution Approach 1:
The patent makes the no-fall region dynamic by continuously updating it based on real-time flight control results, UAV position, altitude, and wind conditions. This allows the region to adapt during flight while still providing a basis for initial route planning, resolving the contradiction between ease of operation and adaptability.
3Device complexity
If the no-fall region is set statically, then the system is simple to implement, but it cannot account for changes in wind speed and altitude during flight
Solution Approach 1:
The patent implements a dynamic crash probable region that adjusts based on real-time altitude and wind speed measurements. This dynamic approach improves reliability by accounting for changing flight conditions while maintaining reasonable system complexity through the use of standard sensors and continuous calculation based on flight state.
Solution Approach 2:
The system employs feedback mechanisms by continuously measuring altitude and wind conditions, then using this information to update the crash probable region. This closed-loop control improves accuracy without requiring overly complex system architecture, as it builds upon existing flight control systems.
Data Source
AI summary
An unmanned air vehicle includes: a camera that takes an image in a vertical direction from the unmanned air vehicle; an image processor that indicates, on the image, a region in which the unmanned air vehicle is likely to crash and that detects an object of avoidance that is present in the region; a crash-avoidance flight controller that, in a case where the object of avoidance is detected, controls flight of the unmanned air vehicle so that the object of avoidance becomes undetectable in the region; and a crash probable region determiner that changes the region according to a result of the flight control.