科技报告详细信息
Real-Time UAV Trajectory Prediction for Safety Monitoring in Low-Altitude Airspace
Corbetta, Matteo ; Banerjee, Portia ; Okolo, Wendy A ; Gorospe, George E ; Luchinsky, Dmitry G
关键词: AERODYNAMICS;    AEROSPACE SYSTEMS;    ALGORITHMS;    AUTONOMY;    DATA BASES;    DECISION MAKING;    ENVIRONMENT EFFECTS;    FLIGHT PATHS;    FLIGHT PLANS;    FORECASTING;    HAZARDS;    HOVERING;    LINEAR QUADRATIC REGULATOR;    LOW ALTITUDE;    MATHEMATICAL MODELS;    PILOTLESS AIRCRAFT;    REAL TIME OPERATION;    SAFETY FACTORS;    SYSTEMS ENGINEERING;    TRAJECTORY PLANNING;   
RP-ID  :  ARC-E-DAA-TN63006
学科分类:航空航天科学
美国|英语
来源: NASA Technical Reports Server
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【 摘 要 】

The rising number of small unmanned aerial vehicles (UAVs) expected in the next decade will enable a new series of commercial, service, and military operations in low altitude airspace as well as above densely populated areas. These operations may include on-demand delivery, medical transportation services, law enforcement operations, traffic surveillance and many more. Such unprecedented scenarios create the need for robust, efficient ways to monitor the UAV state in time to guarantee safety and mitigate contingencies throughout the operations. This work proposes a generalized monitoring and prediction methodology that utilizes realtime measurements of an autonomous UAV following a series of way-points. Two different methods, based on sinusoidal acceleration profiles and high-order splines, are utilized to generate the predicted path. The monitoring approach includes dynamic trajectory re-planning in the event of unexpected detour or hovering of the UAV during flight. It can be further extended to different vehicle types, to quantify uncertainty affecting the state variables, e.g., aerodynamic and other environmental effects, and can also be implemented to prognosticate safety-critical metrics which depend on the estimated flight path and required thrust. The proposed framework is implemented on a simplified, scalable UAV modeling and control system traversing 3D trajectories. Results presented include examples of real-time predictions of the UAV trajectories during flight and a critical analysis of the proposed scenarios under uncertainty constraints.

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