New risk posed by unmanned aircraft systems (UASs) is a pressing concern for industry, regulators, and the public. Failures 480711 and anomalies may force a near-term landing, requiring fast real-time identification of low-risk landing sites and feasible low-risk paths to those sites. Although sensors can scan an immediate area, no safe landing site might be within the current field of view in which case a map of more distant sites is essential. In urban areas, small UAS touchdown on a flat rooftop may pose less risk to people and property than landing on crowded streets, sidewalks, or parks. This paper describes the offline construction of a landing site database using publicly available data sources with focus on rooftop sites. Flat roofs are identified from LiDAR and image data and then processed to extract obstacle-free surface(s) for landing. Flight path and landing site risk maps are defined. Pareto frontiers over these two risk types are examined. A multi-goal planner considers landing site risk and path risk as a weighted sum to minimize. Statistics on case studies in three diverse communities are presented.


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    Title :

    Map-Based Planning for Small Unmanned Aircraft Rooftop Landing


    Additional title:

    Studies in Systems, Decision and Control


    Contributors:


    Publication date :

    2021-06-24


    Size :

    34 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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