Enhanced UAV Flight Plans for Autonomous Emergency Routing
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Solution Overview
Problem
Current UAV flight management systems fail to address unexpected issues during flight, leading to inefficient and unsafe operations, as they lack automation for handling emergencies and do not consider no-fly zones or terrain hazards, requiring human intervention.
Innovation Solution
Enhanced flight plans are implemented with predefined points that allow UAVs to autonomously alter flight paths based on predefined conditions, integrating charging stations, safe landing locations, and sheltered areas, minimizing human interaction and enhancing safety and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single default emergency action (grounding or aborting) is programmed in current UAVs, then the system is simple to operate, but it cannot properly address the large number of unexpected issues that may arise during flight
Solution Approach 1:
The patent applies preliminary action by pre-programming multiple emergency actions and their corresponding triggers in the UAV's flight management system before flight. Instead of relying on a single default response, the system is预先 equipped with a library of emergency protocols (e.g., return-to-launch, land-at-nearest-safe-location, hover-in-place) that are automatically selected and executed based on the specific unexpected issue detected during flight, eliminating the need for real-time human decision-making while maintaining system simplicity.
2Reliability
If current UAVs abort flight missions upon unexpected issues, then the safety of the UAV is improved, but the productivity and efficiency of flight operations deteriorate due to frequent mission interruptions
Solution Approach 1:
The patent applies dynamics by making the emergency response strategy adaptive rather than static. The flight management system dynamically selects from multiple pre-programmed emergency actions based on the specific trigger condition detected during flight. For example, if a motor failure is detected, the system determines whether to return-to-launch or land-at-nearest-safe-location based on real-time conditions such as battery level, proximity to safe zones, and flight phase, thereby optimizing both safety and mission continuity rather than always aborting.
Solution Approach 2:
The patent applies parameter changes by modifying the operational parameters of the UAV during emergency situations rather than always terminating the mission. The system can change parameters such as flight mode (from normal to emergency), destination (from original target to safe location), and velocity (from cruise to descent) to handle unexpected issues while continuing the mission when safe, thus improving both safety and productivity simultaneously.
3Ease of operation
If human operators monitor and control each UAV flight manually, then the ease of operation is maintained, but the productivity and efficiency of air traffic management deteriorate
Solution Approach 1:
The patent applies self-service by enabling the UAV's flight management system to autonomously detect unexpected issues, select appropriate emergency actions, and execute corrective maneuvers without human intervention. The system monitors its own operational parameters (battery level, motor status, connectivity) and automatically responds to anomalies by executing pre-programmed emergency protocols, thereby freeing human operators from micromanagement while maintaining ease of operation for normal flights and dramatically increasing air traffic handling capacity.
4Adaptability or versatility
If UAVs are equipped with multiple emergency actions and triggers, then the adaptability to handle unexpected issues is improved, but the device complexity and difficulty of system management worsen
Solution Approach 1:
The patent applies segmentation by dividing the emergency response system into distinct, modular components: multiple predefined trigger conditions (battery low, motor failure, connectivity loss), multiple discrete emergency actions (return-to-launch, land-at-nearest-safe-location, hover-in-place), and a decision logic layer that maps triggers to actions. This segmented architecture allows the system to handle complex emergency scenarios through simple, pre-programmed if-then rules, reducing the perceived complexity while maintaining high adaptability.
Data Source
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AI summary
A method for managing an Unmanned Aerial Vehicle (UAV) is described. The method includes receiving a flight plan that describes a proposed flight mission of the UAV in an airspace; adding one or more predefined points to the flight plan to create an enhanced flight plan, wherein each of the predefined points is associated with a set of conditions and a set of locations; and transmitting the enhanced flight plan to the UAV for storage of the predefined points on the UAV while the UAV carries out the proposed flight mission.