A key challenge for low-altitude unmanned air transportation is to minimize operational risks by all means. Besides many other measures to be considered, the aircraft’s trajectory must be planned carefully and optimized as there are inevitable remaining risks which should be minimized when flying over sparsely populated areas. The risk may be mitigated by a safe termination of the flight if circumstances permit. Also, the probability of violating any operational constraints that would lead to a flight termination should be reduced as much as possible. Adequate risk models and efficient algorithmic risk assessment techniques are required to perform such optimizations. Furthermore, the aircraft may have to react to certain events such as high-priority traffic by changing its trajectory online during flight. As command and control (C2) links may have limited reliability, it must be possible to perform trajectory re-planning onboard with limited computational resources. This poses high demands on the runtime efficiency of the planning algorithms. In this work, we present conceptual approaches to risk modeling and assessment based on geospatial datasets and aircraft dynamic models. We further present the design and experimental results of a software framework for onboard and online trajectory planning. Our results demonstrate that risk-based motion planning for unmanned aircraft can be performed with limited onboard computational resources allowing for safe autonomous flight.


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    Title :

    Trajectory Risk Modelling and Planning for Unmanned Cargo Aircraft


    Additional title:

    Research Topics in Aerospace


    Contributors:


    Publication date :

    2021-11-03


    Size :

    39 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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