Limits to ground control in autonomous spacecraft (original) (raw)
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Autonomy in future space missions
NASA missions are becoming more complicated due to the decreasing cost of spacecraft; the increased sensitivity and data gather capability of onboard instruments, and the need to use multiple spacecraft to accomplish new science. To accommodate these new missions current ground and space operations will need to use new paradigms to implement these new missions while keeping costs and logistics manageable. This paper gives some background on some of the new multi-satellite missions in the near future, challenges of these types of missions, how autonomy could be added to these missions and why adding autonomy will be necessary to make them successful from a science gathering, operational and financial standpoint.
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Science-driven Spacecraft Autonomy
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Advances in Control System Technology for Aerospace Applications, 2015
In early 2011, NASA's Office of the Chief Technologist released a set of technology roadmaps with the aim of fostering the development of concepts and cross-cutting technologies addressing NASA's needs for the 2011-2021 decade and beyond. NASA reached out to the National Research Council (NRC) to review the program objectives and prioritize their list of technologies. In January 2012, the NRC released its report entitled "Restoring NASA's Technological Edge and Paving the Way for a New Era in Space." While the NRC report provides a systematic and thorough ranking of the future technology needs for NASA, it does not discuss in detail the technical aspects of the prioritized technologies (that is clearly beyond the scope of the report). This chapter, building upon the NRC report, aims at providing technical details for a selected number of high-priority technologies in the autonomous systems area. Specifically, this chapter focuses on technology area TA04 "Robotics, Tele-Robotics, and Autonomous Systems" and discusses in some detail the technical aspects and challenges associated with three high-priority TA04 technologies: "Relative Guidance Algorithms", "Extreme Terrain Mobility", and "Small Body/Microgravity Mobility." Each of these technologies is discussed along four main dimensions: scope, need, state of the art, and challenges and future directions. The result is a unified explanation of key autonomy challenges for next generation space missions.
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Onboard autonomy technologies such as planning and scheduling, identification of scientific targets, and content-based data summarization, will lead to exciting new space science missions. However, the challenge of operating missions with such onboard autonomous capabilities has not been studied to a level of detail sufficient for consideration in mission concepts. These autonomy capabilities will require changes to current operations processes, practices, and tools. We have developed a case study to assess the changes needed to enable operators and scientists to operate an autonomous spacecraft by facilitating a common model between the ground personnel and the onboard algorithms. We assess the new operations tools and workflows necessary to enable operators and scientists to convey their desired intent to the spacecraft, and to be able to reconstruct and explain the decisions made onboard and the state of the spacecraft. Mock-ups of these tools were used in a user study to underst...
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The impact of infusing breakthrough autonomy technology into a flight project was a big surprise. Valuable technical and cultural lessons, many of general applicability when introducing system-level autonomy, have been learned by infusing the Remote Agent (RA) into NASA's Deep Space 1 @S 1) spacecraft. The RA's architecture embodies system-level autonomy in three major components: Planning and Scheduling, Execution, and Fault Diagnosis and Reconfiguration. Lessons learned include: The architecture was confirmed. Active participation by nonautonomy personnel in the development is essential. Communication of new concepts is essential, difficult, and hampered by differences in terminology. Giving a spacecraft system-level autonomy changes organizational roles in operating the spacecraft after launch, and hence changes roles during development. Software models supporting functions traditionally handled on the ground must be developed early enough to get on-board. Shortfalls in planned features must be technically and developmentally accomodatable, in particular not to threaten the launch schedule. Traditional commanding must be supported. Testing must be emphasized; end-to-end tests counter skepticism. These lessons and others, on incremental system releases and use of autocode generation, are based on 16 months of spiral development from start of project through the project's decision to reduce the role of the RA from full-time control of the spacecraft to a separable experiment. TABLE: OF CoNrmT's 1. INTRODuCTiON 2. T}IE NEW MILLENNIUM PROGRAM 3. DSI AUTONOMY/FLIGEII' SOFTWARE ARCIIITECTURE 4. FLIGIIT SOFIWARE IMPLEMENTATION APPROACH 5. CIIALLENGING INITIAL CONDITIONS 6. ROLE REDUCTION OF TIIE REMOH; AGEN"I' 7. LESSONS LEARNED 8. SUh4MARY
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This paper presents a description of UNICORN, a prototype system developed at General Electric for the purpose of investigating Artificial Intelligence (AI) concepts supporting spacecraft autonomy. With this objective, UNICORN employs thematic reasoning, of the type first described by Rodger Schank of Northwestern University, to allow the context-sensitive control of multiple intelligent agents within a blackboard-based environment (Schank, 1977). In its domain of application, UNICORN demonstrates the ability to reason teleologically with focused knowledge. Also presented within the following sections are some of the lessons learned as a result of this effort. These lessons apply to any effort wherein system level autonomy is the objective.