Work

Neural-based trajectory shaping approach for terminal planetary pinpoint guidance

Year: 2013

Type: book-chapter

Abstract: 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.

Source: Strathprints: The University of Strathclyde institutional repository (University of Strathclyde)

Authors: Roberto Furaro, Jules Simo, Brian Gaudet, Daniel R. Wibben

Institution: University of Arizona

Language: English

Topic: Spacecraft Dynamics and Control

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W3206376248

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