Exploration Technologies for Operations

Although the International Space Station (ISS) assembly has been completed, the Operations support teams continue to seek more efficient and effective ways to prepare for and conduct the ISS operations and future exploration missions beyond low earth orbit. This search for improvement has led to a significant collaboration between the NASA research and advanced software development community at NASA Ames Research Center and the Mission Operations community at NASA Johnson Space Center. Since 2001, NASA Ames Research Center has been developing and applying its advanced intelligent systems and human systems integration research to mission operations tools for several of the unmanned Mars missions operations. Since 2006, NASA Ames Research Center has also been developing and applying its advanced intelligent systems and human systems integration research to mission operations tools for manned operations support with the Mission Operations Directorate at NASA Johnson Space Center. This paper discusses the completion of the development and deployment of a variety of intelligent and human systems technologies adopted for manned mission operations. The technologies associated with the projects include advanced software systems for operations and human-centered computing. Human-centered computing looks to the processes and procedures that people do to perform any given job, then attempts to identify opportunities to improve these processes and procedures. In particular, for mission operations, improvements are quantified by specifically identifying how a tool can increase a persons efficiency, enhance a persons functional capability, andor improve the assurance of a persons decisions. The Ames development team has collaborated with the Mission Operations team to identify areas of efficiencies through technology infusion applications in support of the Plan, Train, and Fly activities of human-spaceflight mission operations. The specific applications discussed in this paper are in the areas of mission planning systems, mission operations design modeling and workflow automation, advanced systems monitoring, mission control technologies, search tools, training management tools, spacecraft solar array management, spacecraft power management, and spacecraft attitude planning. We discuss these specific projects between the Ames Research Center and the Johnson Space Centers Mission Operations Directorate, and how these technologies and projects are enhancing the mission operations support for the International Space Station. We also discuss the challenges, problems, and successes associated with long-distance and multi-year development projects between the research team at Ames and the Mission Operations customers at Johnson Space center. Finally, we discuss how these technology infusion applications and underlying technologies might be used in the future to support on-board operations of the crew and spacecraft systems as human exploration expands beyond low earth orbit to destinations in the solar system where communications delays will require more on-board autonomy and planning by the crew. Longer communications delays will require that the ground mission operations support will be primarily strategic in nature, while the tactical level of planning, systems monitoring and control, and failure analysisisolationrecovery will be the responsibility of both the spacecraft autonomous systems and the crew. Our expectation is that the technologie

Coordinating goals, preferences, options, and analyses for the Stanford Living Laboratory feasibility study

Abstract. This paper describes an initial application of Multi-Attribute Collective Decision Analysis for a Design Initiative (MACDADI) on the feasibility study of a mixed-use facility. First, observations of the difficulties the design team experienced communicating their goals, preferences, options, and analyses are presented. Next, the paper describes a formal intervention by the authors, integrating survey, interview, and analytic methods. The project team collected, synthesized, and hierarchically organized their goals; stakeholders ’ established their relative preferences with respect to these goals; the design team formally rated the design options with respect to the goals; the project team then visualized and assessed the goals, options, preferences, and analyses to assist in a transparent and formal decision making process. A discussion of some of the strengths and weaknesses of the MACDADI process is presented and opportunities for future improvement are identified

The Challenge of Configuring Model-Based Space Mission Planners

Mission planning is central to space mission operations and has benefited from advances in model-based planning software, but developing a planning model still remains a difficult task. Mission planning constraints arise from many sources, including simulators and engineering specification documents. Ensuring that these constraints are correctly represented in the planner’s model is a challenge. As mission constraints evolve, planning domain modelers must add and update model constraints efficiently using the available source data, catching errors quickly, and correcting the model. We describe the current state of the practice in designing model-based mission planning tools and the challenges facing model developers. We then propose an Interactive Model Development Environment (IMDE) to configure mission planning systems by integrating modeling and simulation environments to reduce model editing time, generate simulations automatically to evaluate plans, and identify modeling errors automatically by evaluating simulation output