Behaviour based autonomy for single and multiple spacecraft

Radice, Gianmarco (2002) Behaviour based autonomy for single and multiple spacecraft. PhD thesis, University of Glasgow.

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Abstract

Current research in space systems engineering has highlighted the requirement for increasingly autonomous spacecraft and planetary rovers to meet the stringent needs of future missions. The purpose of this thesis is to present a new approach in the concept and implementation of single and clustered micro-spacecraft. The one true "artificial agent" approach to autonomy requires the micro-spacecraft to interact in a direct manner with the environment through the use of sensors and actuators. As such, there is little computational effort required to implement such an approach, which is clearly of great benefit for limited micro-satellites. Rather than using complex world models, which have to be updated, the agent is allowed to exploit the dynamics of its environment for cues as to appropriate actions to take to achieve mission goals. The particular artificial agent implementation used here has been borrowed from studies of biological systems, where it has been used successfully to provide models of motivation and opportunistic behaviour. The so called "cue- deficit" action selection algorithm considers the micro-spacecraft to be a non linear dynamical system with a number of observable states. Using optimal control theory, rules are derived which determine which of a finite repertoire of behaviours the satellite should select and perform. The principal benefits of this approach is that the micro-spacecraft is endowed with self-sufficiency, defined here to be the ability to achieve mission goals, while never placing itself in an irrecoverable position.

Item Type: Thesis (PhD)
Qualification Level: Doctoral
Keywords: Aerospace engineering
Date of Award: 2002
Depositing User: Enlighten Team
Unique ID: glathesis:2002-71410
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 10 May 2019 10:49
Last Modified: 10 May 2019 10:49
URI: http://theses.gla.ac.uk/id/eprint/71410

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