Toward Information-Driven and Risk-Bounded Autonomy for Adaptive Science and Exploration
Author(s)
Ayton, Benjamin J; Reeves, Marlyse; Timmons, Eric; Williams, Brian C; Ingham, Michel D
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© 2020 The MITRE Corporation. All Rights Reserved. While the primary purpose of robotic space exploration systems is to gather scientific data, it is equally important that engineering operations are performed and engineering constraints are respected in order to prolong the mission life and ensure the integrity of the observations taken. However, science and engineering operations are often at odds with each other as attempting to obtain the “best” data may violate engineering operations constraints and place the mission at risk. Historically, mission systems engineering has separated the process of planning for science from engineering operations, with the engineering operations constrained to support the science measurement plan with acceptable risk. This task division leads to multiple design iterations between the science and engineering operations which results in compromised, conservative operations that reduce science return and are more brittle than desired. To overcome these limitations, we present an approach for autonomous mission planning that explicitly models and reasons about the coupling between science and engineering operations, resulting in higher science return, while maintaining acceptable levels of risk. Our approach is to develop an information-driven, risk-bounded plan executive that is capable of producing missions satisfying the goals and constraints expressed in these programs. In this paper, we describe in detail the risk-bounded, information-driven execution problem and lay out the architecture used in our information-directed plan executive ‘Enterprise’. We then show the performance of the current version of Enterprise on two space exploration scenarios. Finally, we conclude with thoughts on future work, including on the design of a proposed information-theoretic language that will allow operators and scientists to specify their objectives in terms of questions about scientific phenomena or the configuration of the space system.
Date issued
2020Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer ScienceJournal
Accelerating Space Commerce, Exploration, and New Discovery Conference, ASCEND 2020
Publisher
American Institute of Aeronautics and Astronautics
Citation
Ayton, Benjamin J, Reeves, Marlyse, Timmons, Eric, Williams, Brian C and Ingham, Michel D. 2020. "Toward Information-Driven and Risk-Bounded Autonomy for Adaptive Science and Exploration." Accelerating Space Commerce, Exploration, and New Discovery Conference, ASCEND 2020.
Version: Author's final manuscript