Parameterized trajectory planning for dynamic soaring

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Methods for parameterized trajectory planning for dynamic soaring are discussed. Two parameterizations based on flight path are described: the first uses cubic splines, with parameters defining the locations of a set of control points; the second uses skewed/flattened sinusoids, where parameters define skewness, flatness, amplitude, and frequency. Both parameterizations are continuous to at least C2, allowing smooth trajectories to be planned and flown. A trajectory following controller tracks the planned trajectories. Both parameterizations are compared with a collocation method and show faster convergence as well as improved performance in cases where wind fields are not known precisely. A deep neural network is developed to permit fast computation of trajectories under changing wind conditions. Convergence of trajectories using this deep neural network method is shown in simulation.

Original languageEnglish (US)
Title of host publicationAIAA Scitech 2020 Forum
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624105951
DOIs
StatePublished - 2020
EventAIAA Scitech Forum, 2020 - Orlando, United States
Duration: Jan 6 2020Jan 10 2020

Publication series

NameAIAA Scitech 2020 Forum
Volume1 PartF

Conference

ConferenceAIAA Scitech Forum, 2020
CountryUnited States
CityOrlando
Period1/6/201/10/20

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering

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