Guidance, navigation, and control (GNC) of aerospace systems is growing more complex. Current verification and validation (V&V) approaches and processes are not adequate to cope with the evolving GNC architectures and topologies being driven by autonomy. To address this, several space agencies (NASA, ESA, DLR, CNES) and the French research center ONERA sponsored a series of seminars and a workshop, presented from fall 2020 to spring 2021. To mobilize the GNC workforce, this white paper summarizes the workshop outcomes, identifies available tools and existing gaps in V&V capability, and suggests a prioritization of tool and method development needs for V&V of advanced GNC algorithms. Several major emerging themes were recognized and examined: state-of-the-art tools being developed mostly in academic research settings; education and awareness within the GNC work force, creating opportunities to address the most urgent V&V gaps; increasingly autonomous systems that still require assurance; formal software verification that has progressed enough to apply to online flight software; NASA’s advances in V&V and certification for airplanes—processes that can be a roadmap for spacecraft applications; and short-term needs for the formulation and release of relevant V&V benchmark problems as a practical way forward. The opportunities provided by the joint resolution of specific V&V benchmark problems can help close the development gap between academia and industry while gradually tightening the awareness gap. This provides a good basis for further discussions with the goal of converging to a consensus white paper for GNC V&V.
VERIFICATION AND VALIDATION (V&V) OF GUIDANCE & CONTROL SYSTEMS: RESULTS FROM THE FIRST INTER-AGENCY WORKSHOP ON GNC V&V
Proceedings of the 44th Annual American Astronautical Society Guidance, Navigation, and Control Conference, 2022 ; Kapitel : 25 ; 399-432
2024-01-01
34 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
New Verification and Validation Methods for Guidance/Control of Advanced Autonomous Systems
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