Development of a minaturised forwards looking imager using deep learning for responsive operations
Greenland, Steve and Ireland, Murray and Kobayashi, Chisato and Mendham, Peter and Post, Mark and White, David; (2018) Development of a minaturised forwards looking imager using deep learning for responsive operations. In: 4S Symposium 2018. ESA, Noordwijk.
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Abstract
This work presents the design and prototyping work of a miniaturised camera system with integrated ‘deep learning’ neural network capabilities, developed within a framework for implementing autonomous data processing onboard small and nanosatellites. The framework targets low-resource algorithms developed in other sectors including autonomous vehicles and commercial machine learning. For proof of concept, the system has been initially trained for real time cloud detection and classification, looking 1 min ahead of the satellite to enable responsive decision making for Earth observation and telecommunication applications. The design has been miniaturised and modularised to allow accommodation on small and nanosatellite systems. Flight representative and heritage components have been selected for prototyping. Compatibility of the autonomy framework with ECSS and CCSDS standards and existing off-the-shelf flight software was evaluated. A simulator to facilitate end to end testing of the system has been developed using existing data sets as input, incorporating distortions to test robustness. Results show that a competitive low power < 2 W system can be delivered, with the chain < 5 seconds from capture to input into the onboard planning and with timing consistent with continuous real time decision-making.
ORCID iDs
Greenland, Steve, Ireland, Murray, Kobayashi, Chisato, Mendham, Peter, Post, Mark ORCID: https://orcid.org/0000-0002-1925-7039 and White, David;-
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Item type: Book Section ID code: 63922 Dates: DateEvent28 May 2018Published28 February 2018AcceptedNotes: Title changed from "Design & prototyping of a minaturised forwards looking imager using deep learning for responsive onboard operations" to "Development of a miniaturised forwards looking imager using deep learning for responsive onboard operations" after acceptance. Subjects: Technology > Motor vehicles. Aeronautics. Astronautics Department: Faculty of Engineering > Design, Manufacture and Engineering Management Depositing user: Pure Administrator Date deposited: 02 May 2018 10:09 Last modified: 20 Nov 2024 01:31 URI: https://strathprints.strath.ac.uk/id/eprint/63922