An open-source scheduler for small satellites

Torgerson, Donovan; Straub, Jeremy; Mohammad, Atif Farid; Korvald, Christoffer; Limesand, Dayln

doi:10.1117/12.2018445

Cited by 7 publications

(1 citation statement)

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“…worked on a plug-and-play CubeSat design where the design is self-reconfigurable [9]. There are of course many other optimization tools applied to other tasks different than design, such as the work by Torgerson et al who optimized the schedule of on-board tasks using heuristic optimization [10]. However, to the best of our knowledge, there is currently no published work on a catalog-based design optimization tool tailored for CubeSats.…”

Section: Introductionmentioning

confidence: 99%

A CubeSat catalog design tool for a multi-agent architecture development framework

Jacobs

Selva

2015

2015 IEEE Aerospace Conference

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Space systems are undergoing an architectural paradigm change. Large space organizations around the world are now considering CubeSats and other novel elements, such as hosted payloads or commercial services, in the architecture studies for the next generations of Earth observation and communications systems. As CubeSats are included in these trade studies, it is necessary to develop design tools that are tailored to these new architectural elements. Indeed, the traditional topdown approach for designing large satellites is not appropriate for CubeSats, which have many fewer components and make heavy use of COTS. This paper presents a bottom-up, catalog design tool tailored for CubeSats. A CubeSat design is represented by a valid combination of components. Components are selected from a database (catalog) of existing components containing information about mass, power, volume, cost, and performance of the components. The tool has two functioning modes: the forward mode and the backward mode. In the forward mode, the user creates a design by selecting a combination of components from the database, and the tool computes the properties of the resulting satellite: mass, power, and volume budgets, pointing accuracy, as well as cost and other systemlevel properties such as reliability. In the backward mode, the user enters a set of requirements (payload mass, power, data rate, volume, pointing accuracy, orbit, lifetime, and others) and the tool finds all valid combinations of components that satisfy all the requirements, and suggests one. If no valid design exists, the tool provides a set of explanations to the user pointing out the unmet requirements. The tool uses a rule-based approach to solve the configuration design problem, and implements the MadKit interface to be able to communicate with other agents in a multi-agent design environment. This paper describes the tool in technical detail and illustrates with examples using Earth observation and communications payloads.

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Section: Introductionmentioning

confidence: 99%