Simulated Excavation Environment for Lunar Operations (SEELO)

With new pushes to reach and establish long term presences on both the Moon and Mars, significant effort has begun to develop methods of In-Situ Resource Utilization. Many of these methods involve excavation and manipulation of local regolith and, at this time, many of these missions are in the early planning phases. As such, simulations provide both an inexpensive and relatively easy method to perform high level proofs of concept and mission overviews along with an environment to perform machine learning for rovers and other robots.
The Simulated Excavation Environment for Lunar Operations (SEELO) was born out of this need for consolidated capabilities. SEELO seeks to provide accurate life mission environments and regolith interaction mechanics while remaining lightweight enough to run in faster than real-time. These combined features allow SEELO to be used for mission planning purposes that offer an environment for lunar robots to perform Machine Learning on moving, digging, and various other activities. Using the Real-Time Development Platform (Unity) to utilize regolith excavation models created by Intelligent Capabilities Enhanced-Regolith Advanced Surface Systems Operations Robot and lunar surface data collected by NASA’s Lunar Reconnaissance Orbiter, SEELO has been able to provide NASA with a tool to plan, train, and even devise lunar missions.

For In-Situ Resource Utilization missions currently in the planning stages, leveraging the data generated by this simulation in a wide variety of mission architectures will significantly improve the fidelity of planning efforts. The skills required to develop this simulation, both for ISRU concept testing and machine learning to enable autonomy, are valuable and transferable to other dynamical systems and environments at the Kennedy Space Center.

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