The Mission Execution Crew Assistant: Improving Human-Machine Team Resilience for Long Duration Missions
- Paper number
IAC-08.D3.3.5
- Author
Prof. Mark Neerincx, TNO Defence, Security & Safety , The Netherlands
- Coauthor
Dr. Andre Bos, The Netherlands
- Coauthor
Mr. Antonio Olmedo Soler, The Netherlands
- Coauthor
Mr. Uwe Brauer, EADS SPACE Transportation, Germany
- Coauthor
Dr. Leo Breebaart, The Netherlands
- Coauthor
Ms. Nanja Smets, TNO Defence, Security & Safety , The Netherlands
- Coauthor
Mr. Jasper Lindenberg, The Netherlands
- Coauthor
Prof. Tim Grant, The Netherlands
- Coauthor
Mr. Mikael Wolff, European Space Agency (ESA), The Netherlands
- Year
2008
- Abstract
For long duration missions, the concept of crew autonomy versus ground control is likely to undergo drastic changes. Staffing for mission control will be reduced for cost reasons. Higher on-board and surface autonomy is required to establish sound human-machine team resilience, in which teams can cope with unexpected, complex and potentially hazardous situations (including human and technical failures). The crew should be closely involved in the decision making process and resource management, both to improve this resilience—sometimes as a supervisor of a heterogeneous set of (semi) autonomous systems—and to maintain crew motivation and satisfaction during the long-term mission. Based on a thorough analysis of the (envisioned) operational demands, human factors needs and technological constraints, we derived requirements for a crew support system that includes distributed personal electronic partners (ePartners), which help the team to assess the situation, to determine a suitable course of actions to solve a problem, and to safeguard the astronauts from failures. This support system, called Mission Execution Crew Assistant (MECA), will operate in a so-called “Smart Task Environment” infrastructure with automatic distribution of data, knowledge, software and reference documents. It makes use of innovations in agent and web technology, model-based reasoning and health management methods, and technologies for human-robot collaboration and mixed reality. Based on a situated Cognitive Engineering (sCE) method, we derived a Requirements Baseline for MECA, specifying the requirements with their design rationale consisting of scenarios and use cases, user experience claims. Core support functions concern health management, diagnosis, prognosis & prediction, collaboration, resource management, planning, and sense-making. The claims focus on the predicted effects of these functions on crew operations with respect to effectiveness, efficiency, satisfaction, learnability, situation awareness, trust and emotion. In addition to standard requirements reviews, we tested and refined the RB via storyboarding and human-in-the-loop evaluations of a simulation-based prototype in a virtual environment with 15 participants. The evaluation confirmed the predicted results. Issues for improvement and further research were identified and prioritized (e.g., acceptance of mental load and emotion sensing). In general, the situated CE method provided a reviewed set of 167 high-level requirements that explicitly refers to the tested scenarios, claims and core support functions. A first version of an ontology for this support was implemented in the prototype, which will be used for further ePartner development. Plans are underway for MECA implementation and evaluation for long duration isolation study (MARS 500), onboard ISS, and at a terrestrial Moon/Mars analogue environment.
- Abstract document
- Manuscript document
IAC-08.D3.3.5.pdf (🔒 authorized access only).
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