Neural-based trajectory shaping approach for terminal planetary pinpoint guidance

Roberto Furaro, Jules Simo, Brian Gaudet, Daniel Wibben

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

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In this paper, we present an approach to pinpoint landing based on what we consider to be the next evolution of path shaping methodologies based on potential functions. We employ neural network methodologies to learn the relationship between current spacecraft position and the optimal velocity field required to shape the path to the surface in a fuel efficient fashion. By ensuring that the velocity field is convergent to the desired target, a first-order guidance algorithm is designed to track the optimal velocity field.
Original languageEnglish
Title of host publicationAdvances in the Astronautical Sciences
Subtitle of host publicationAstrodynamics 2013
EditorsStephen Broschart, James Turner, Kathleen Howell, Felix Hoots
Place of PublicationHilton Head SC
Publication statusPublished - 11 Aug 2013
EventAAS/AIAA Astrodynamics Specialist Conference 2013 - Hilton Head, South Carolina, United States
Duration: 11 Aug 201315 Aug 2013

Publication series

NameAdvances in the Astronautical Sciences
PublisherUnivelt Inc


ConferenceAAS/AIAA Astrodynamics Specialist Conference 2013
Country/TerritoryUnited States
CityHilton Head, South Carolina


  • trajectory design
  • planetary pinpoint guidance
  • neural network applications


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