79 results found Selected 0 items No itemsClear selection Select / deselect all results (all pages, 79 total) Explainable secure deep learning software for spacecraft GNC systems Cyberattacks on aerospace systems are becoming a growing concern for space missions, alth UK Discovery 22-D-T-TEC-02-h CITY, UNIVERSITY of LONDON 2022 - 2024 Explainable secure deep learning software for spacecraft GNC systems Artificial Intelligence applied to code repair after code static analysis verification On-board software quality is crucial for the space industry and is verified from the early stages of development. One of the first steps is static code analysis, performed by tools that assess adherence to coding standards. Developers then need to correct the identified issues, which can be labor-intensive. Reducing this effort is key to accelerating on-board software development. Spain Discovery 22-D-T-TEC-02-f THALES ALENIA SPACE ESPANA 2022 - 2024 Artificial Intelligence applied to code repair after code static analysis verification Improve mutation testing in space software systems The proposed activity aims at consolidating and extending the work performed within the previous GSTP activity G617-206SW - Applicability of Mutation Testing method for Flight Software. This activity concerned the investigation of mutation analysis as a method to evaluate the quality of software test suites and mutation testing as a method to derive new software test cases. ; Luxembourg GSTP GT17-463SW UNIVERSITE DU LUXEMBOURG 2022 - 2024 Improve mutation testing in space software systems Generating formally verified communication protocol implementations A critical moment during the launch of a mission is when communication is established for the first time. For ground control to communicate with a satellite or payload, the engineering teams must formulate the communication protocols as early as the requirements definition phase, refine and implement them during the design, verification, and production phases, and maintain them after launch. ESA addresses this need for reliability despite constant change with the OPUS and the ASN1SCC projects. Switzerland Discovery 22-D-T-TEC-02-b Ateleris 2022 - 2024 Generating formally verified communication protocol implementations De-Risk Assessment: DEVELOPMENT OF AN AUTOMATIC FAILURE ANALYSIS TOOL FOR SPACE APPLICATIONS Background and justification: Spain GSTP G617-241TAka POWER SMART CONTROL SL 2023 - 2024 De-Risk Assessment: DEVELOPMENT OF AN AUTOMATIC FAILURE ANALYSIS TOOL FOR SPACE APPLICATIONS Onboard FDIR based on AI techniques with data streams from Columbus and autonomous TM management control, Early technology project for future orbital missions Artificial intelligence has the potential to become an integral part of space in the future to realize the autonomy of the system without ground control and crew interactions. The demonstrator developed in the scope of the ORBIT-STAR project supports the evaluation of scenarios and techniques for incorporating machine learning algorithms in an operational environment. Germany Discovery 22-D-T-TEC-02-d Airbus Defence and Space GmbH 2022 - 2024 Onboard FDIR based on AI techniques with data streams from Columbus and autonomous TM management control, Early technology project for future orbital missions Crustacea in space - co-operative RUST and C embedded applications in space - theory and practice This activity investigates the feasibility of using Rust as a programming language for onboard software development in space missions. A port of the Rust standard library to RTEMS was successfully implemented, demonstrating Rust's potential for efficient and reliable onboard software development. The research also focuses on quality assurance aspects relevant to ESA ECSS standards, including documentation, testing, and product metrics. Germany Discovery 22-D-T-TEC-02-l DLR - German Aerospace Center 2022 - 2024 Crustacea in space - co-operative RUST and C embedded applications in space - theory and practice AI-based on-board reconfigurable FDIR and lifetime prediction for constellations Constellations require complex operations and must grant high service availability. This makes autonomy and enhanced on-board FDIR one of the most urgent developments for the reduction of operational costs and of reaction times to events. Recent activities aim to use AI to improve FDIR. However, some key issues have to be faced: Italy Discovery 22-D-T-TEC-02-a S.A.T.E. SRL 2022 - 2024 AI-based on-board reconfigurable FDIR and lifetime prediction for constellations Preparation of enabling space technologies and building blocks: Boosting MO security with end2end encryption and space HSMaaS with SDLS Background and justification: Estonia GSTP GT17-137TIce CGI EESTI AS 2022 - 2024 Preparation of enabling space technologies and building blocks: Boosting MO security with end2end encryption and space HSMaaS with SDLS De-risk assessment: Identification and analysis of security services for space missions and space surveillance application data and IT systems Background and justification: Romania GSTP G617-241TAjp ENEA SERVICES ROMANIA 2023 - 2024 De-risk assessment: Identification and analysis of security services for space missions and space surveillance application data and IT systems Pagination 1 2 3 4 5 6 7 8 ›› Next page Last » Last page Filter by Programme GSTP (38) TDE (23) Discovery (17) Preparation (1) Filter by Start Year 2022 (16) 2020 (11) 2018 (8) 2019 (8) 2021 (8) 2016 (7) 2023 (5) 2013 (4) 2011 (3) 2014 (3) 2017 (3) 2015 (2) 2012 (1) Filter by End Year 2023 (16) 2024 (14) 2021 (12) 2022 (12) 2019 (7) 2014 (4) 2015 (4) 2018 (4) 2020 (3) 2013 (1) 2016 (1) 2017 (1) Filter by Keywords 2-Space System Software (5) 26-Spacecraft Avionic System (4) 30-Deep Sub Micron Development (2) 48-Cybersecurity (2) MBSE (2) OPS-SAT (2) 1-Avionics and Processing (1) 3-Platforms / Others (1) 3-Space Segment - Payload (1) 32-Clean Space (1) 40-Design to Produce (1) 49-Artificial Intelligence (1) AI (1) anomalies detection (1) Augmented Reality (1) Autonomy (1) CDF (1) Communication (1) compilation (1) cryptographic protocols (1) data compression (1) DeepCube (1) Envision (1) FDIR (1) image compression (1) knowledge graphes (1) Mars (1) Mission (1) on-board anomaly detection (1) optimal control (1) quadrocopters (1) quantum computer (1) quantum computing (1) Quantum Encryption (1) quantum operations (1) Quantum Optics (1) RF compression (1) Security (1) smart lossy (1) system engineering models (1) Venus (1) video compression (1) VR (1) XR lab (1) Filter by Contractor GMV AEROSPACE AND DEFENCE, SA (6) SPACEBEL SA. 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