UAV Well-Clear Boundary Control Using Trajectory-Based Sensing
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Solution Overview
Problem
The increasing complexity of maintaining safe distances between aerial vehicles, particularly with the proliferation of unmanned aerial vehicles, due to size, weight, and cost constraints that make it infeasible for small UAVs to equip with necessary sensors, and the inefficiency of ground-based radar systems for managing large numbers of UAVs.
Innovation Solution
Implementing onboard sensors and computing devices in aerial vehicles to dynamically calculate and maintain a well clear boundary based on instantaneous and planned trajectories, capabilities, and field of view, allowing for autonomous avoidance maneuvers without the need for extensive ground-based infrastructure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If small unmanned aerial vehicles are equipped with sensors to detect the required volume of air, then collision avoidance capability is improved, but weight, size, and cost increase making it infeasible
Solution Approach 1:
The patent introduces ground-based radar systems as intermediary devices that perform the detection function externally. The radar infrastructure on the ground acts as a mediator between multiple UAVs, providing collision avoidance information without requiring heavy sensors on each vehicle. This transfers the detection burden from the moving object (UAV) to a stationary external system.
Solution Approach 2:
The ground-based radar system serves multiple UAVs simultaneously, providing a universal detection service. Instead of each UAV carrying its own dedicated sensors, a single radar installation can monitor and protect multiple vehicles in the airspace, reducing the sensor burden on individual vehicles while maintaining collective safety.
2Productivity
If ground-based radar systems are deployed to manage aerial vehicles, then airspace management capability is improved, but cost and infrastructure complexity increase
Solution Approach 1:
The patent segments the airspace management function by assigning different responsibilities to different systems. Ground-based radar handles long-range detection and macro-level traffic management, while onboard sensors on UAVs handle local micro-level collision avoidance. This segmentation allows each system to operate at its optimal level without requiring full-capability infrastructure everywhere.
Solution Approach 2:
The system implements partial sensing coverage through ground-based radar for areas requiring macro-management, while relying on partial onboard sensors on UAVs for local protection. This partial action approach avoids the excessive complexity of deploying full sensor suites on every vehicle or comprehensive ground-based coverage everywhere, achieving adequate protection through distributed partial capabilities.
3Reliability
If static well clear boundary is maintained between aerial vehicles, then safety is improved, but operational efficiency decreases due to excessive separation distances
Solution Approach 1:
The patent transitions from static well clear boundaries to dynamic separation management. Ground-based radar continuously tracks UAV positions and velocities, enabling real-time calculation of risk-based separation distances. This dynamic approach allows separation distances to adjust based on current operational conditions, vehicle performance characteristics, and environmental factors, optimizing both safety and efficiency.
Solution Approach 2:
The system changes the parameter of separation distance from a fixed static value to a variable dynamic value. By continuously adjusting separation distances based on real-time radar data, vehicle capabilities, and operational context, the system optimizes the balance between safety requirements and operational efficiency, allowing closer separations when conditions permit while maintaining adequate buffers when risks increase.
Data Source
AI summary
Systems and methods for airspace management. One embodiment of an aerial vehicle, includes a first sensor for detecting a lateral field of view of the aerial vehicle and a vehicle computing device. The vehicle computing device may include a memory component and a processor. The memory component may store logic that, when executed by the processor, causes the aerial vehicle to calculate a detection boundary for the aerial vehicle to maintain a well clear requirement, wherein the detection boundary is based on instantaneous trajectory, planned future trajectory, and a capability of the aerial vehicle and utilize the capability of the aerial vehicle and data from the first sensor to maintain the vehicle within detection boundary. In some embodiments the logic may cause the vehicle to provide an instruction to maintain the aerial vehicle within the detection boundary.