Multi-Robot Planetary Exploration Architectures

Space policy direction is shifting, particularly with respect to human goals. Given the uncertainty of future missions to the moon, Mars, and other bodies, a tool that allows for informed analysis of the option space is particularly relevant. Aurora Flight Sciences and MIT propose to further develop the Multi-Robot Planetary Exploration Architecture (MRPEA) methodology, a suite of software tools and analysis algorithms developed to provide decision aides to architecture planners of planetary surface exploration missions. MRPEA provides 1. A logical and graphical representation of the system space (e.g. interrelated decision variables with constraints), 2. Structural reasoning for rapid exploration of architectural spaces, 3. Simulation, and 4. Results viewing for a set of feasible architectures. Given the robots available or predicted to be available, the expected duration, and the mission goals, our methodology provides analysis results such as knowledge benefit-vs.-mass Pareto front graphs, to allow the designers to provide the best possible architecture for the planned mission or missions. The MRPEA analysis methodology primarily addresses the planning requirements of planetary surface missions, providing useful analyses of the many elements of the architectural decision space; in addition, the principles and techniques developed to analyze and select multi-robot architectures on planetary surfaces can also be applied to future fractional satellite systems, an area of increasing interest.

Potential non-NASA Commercial Applications primarily includes the Department of Defense. In particular, battlefield asset allocation requires optimizing the fleet of available unmanned and manned resources, depending on the purpose of a particular sortie or overall mission. We anticipate that a planner would be able to use our tool to better understand how to allocate networks of UGV's, manned vehicles, UAV's, and other assets. The MRPEA methodology can be extended to accommodate varying assets and mission purposes. In addition, we anticipate that this methodology could be used for design of human/robotic collaborative medical health care scenarios. Specifically, extended hospital or facility care (e.g. senior citizens) will, in the future, utilize robots for certain tasks. As this market sector grows, MRPEA will be useful in designating appropriate human or robot tasks and timelines, and designing architectural scenarios.

The primary NASA application for which the MRPEA methodology will be used is in overall mission planning of future planetary surface missions. This is applicable to future planetary surface missions. Last summer President Obama formed a "Review of U.S. Human Spaceflight Plans Committee" (NASA, Seeking a Human Spaceflight Program Worth of a Great Nation: Review of U.S. Human Spaceflight Plans Committee, 2009), tasked with identifying viable options for the future of human spaceflight. One option identified by the group, the "flexible pathway", does not explicitly call for human exploration of any planetary surface. This is in contrast to the 2004 Vision for Space Exploration (NASA, 2004), which lays out plans for human exploration of the surface of the moon, followed by Mars. Given the uncertainty of the involvement of crewmembers in planetary surface exploration, the application of a mission planning aide that allows the flexibility to utilize either robots and humans, or just robots, is highly relevant. The MRPEA methodology provides a flexible process by which mission planners can optimize future planetary surface missions, with varying resources (robots and/or humans), purposes, mission lengths and number of missions, and launch capabilities.

This is a mature technology (TRL 7+) — the realistic path in is usually NASA's Technology Transfer Program: licensing an existing NASA patent, or a Space Act Agreement to use NASA facilities/expertise directly. NASA also runs a startup licensing program with no upfront fee for companies formed to commercialize a specific NASA technology.

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