Aircraft Performance Model Calibration and Validation for General Aviation Safety Analysis

Puranik, Tejas G.; Harrison, Evan; Chakraborty, Imon; Mavris, Dimitri N.

doi:10.2514/1.c035458

Cited by 6 publications

(1 citation statement)

References 25 publications

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“…Proximity to buildings [35], flying over people [15], navigating unmapped areas algorithm properties. Fixed-wing aircraft typically optimize cruise altitude (atmospheric density), airspeed, climb rate, lift/drag ratio [36,37], and hazardous weather avoidance [38] but do not consider ground-based obstacles due to their substantial cruise altitude. Multicopter UAS operate at much lower altitudes thus typically optimize motions over clearance from obstacles, distance / time, and mission requirements [39].…”

Section: Environmentmentioning

confidence: 99%

Urban Metric Maps for Small Unmanned Aircraft Systems Motion Planning

Ochoa¹,

Atkins²

2021

Preprint

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Low-altitude urban flight planning for small Unmanned Aircraft Systems (UAS) requires accurate vehicle, environment maps, and risk models to assure flight plans consider the urban landscape as well as airspace constraints. This paper presents a suite of motion planning metrics designed for small UAS urban flight. We define map-based and path-based metrics to holistically characterize motion plan quality. Proposed metrics are examined in the context of representative geometric, graph-based, and sampling-based motion planners applied to a multicopter small UAS. A novel multi-objective heuristic is proposed and applied for graphbased and sampling motion planners at four urban UAS flight altitude layers. Monte Carlo case studies in a New York City urban environment illustrate metric map properties and planner performance. Motion plans are evaluated as a function of planning algorithm, location, range, and flight altitude.

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