Formal Verification Applied to Spacecraft Attitude Control

Lang, Kendra; Klett, Corbin; Hawkins, Kelsey P.; Féron, Éric; Tsiotras, Panagiotis; Phillips, Sean

doi:10.2514/6.2021-1126

Cited by 5 publications

(2 citation statements)

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“…Solutions will be measured based on fuel use and time to perform the mission. A number of potential safety concerns are identified (there are several risks associated with autonomous proximity operations [65,66]). A prototype reinforcement learning solution is used to train a point mass model of a spacecraft to dock using linearized Clohessy-Wiltshire dynamics in Hill's reference frame [67] [Ex.…”

Section: Design Reference Missionmentioning

confidence: 99%

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Space Trusted Autonomy Readiness Levels

Hobbs¹,

Lyons²,

Feather³

et al. 2022

Preprint

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Technology Readiness Levels are a mainstay for organizations that fund, develop, test, acquire, or use technologies. Technology Readiness Levels provide a standardized assessment of a technology's maturity and enable consistent comparison among technologies. They inform decisions throughout a technology's development life cycle, from concept, through development, to use. A variety of alternative Readiness Levels have been developed, including Algorithm Readiness Levels, Manufacturing Readiness Levels, Human Readiness Levels, Commercialization Readiness Levels, Machine Learning Readiness Levels, and Technology Commitment Levels. However, while Technology Readiness Levels have been increasingly applied to emerging disciplines, there are unique challenges to assessing the rapidly developing capabilities of autonomy. This paper adopts the moniker of Space Trusted Autonomy Readiness Levels to identify a two-dimensional scale of readiness and trust appropriate for the special challenges of assessing autonomy technologies that seek space use. It draws inspiration from other readiness levels' definitions, and from the rich field of trust and trustworthiness.

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Section: Design Reference Missionmentioning

confidence: 99%

“…A gray box system has some properties internal to the system known, while there is no requirement for a black box system to be known,[68].…”

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confidence: 99%