The plans that are generated can be optimized for a specific set of goals, such as maximizing science data or minimizing power consumption.
NASA’s Jet Propulsion Laboratory, Pasadena, California
The goal of this work was to model lunar surface systems using a declarative planning system (ASPEN — Activity Scheduling/Planning Environment), provide a parameterizable Excel document to aid in the model generation, and deliver both Mac and PC versions. An adaptation of Microsoft Excel and ASPEN for Lunar Surface System concepts of operations was used. The goal of the system is to enable searching through several concepts of operations. A concept of operations consists of a proposed schedule of high-level activities and parameterization of resources (e.g., power, communications, oxygen, water, etc.) where three distinct phases of development occurred: (1) initial system development for Lunar, (2) planning system development for Lunar, and (3) planning system development for NASA’s 13th Desert Research and Technology Studies (Desert RATS) live trial.
ASPEN is a modular, reconfigurable application framework based on artificial intelligence techniques that is capable of supporting a variety of planning and scheduling applications, including spacecraft operations planning, planning for mission design, surface rover planning, ground antenna utilization planning, and coordinated multiple rover planning.
As a ground-based system, ASPEN uses an internal spacecraft model and set of high-level goals to output a sequence of commands to be executed by the spacecraft to achieve those goals. As a flight-based system, ASPEN receives updates on spacecraft or rover state continuously and updates the current plan to reflect environment changes. As an antenna scheduling system, ASPEN has been used to control autonomously a DSN station.
ASPEN contains several innovations that are not available in other planning and scheduling systems in use today. The ASPEN system does not require any user knowledge in the areas of computer programming, planning, or scheduling. At the same time, the language is flexible enough to support the complex needs of planning multiple spacecraft and resources.
ASPEN contains a generic architecture that allows the user to choose among several different search engines and propagation algorithms to optimize the planning process. It contains an iterative repair search algorithm that enables the user to interact with the schedule and replan quickly and efficiently. The plans that ASPEN generates can be optimized for a specific set of goals, such as maximizing science data or minimizing power consumption. The optimization goals can be easily and succinctly specified within the modeling language.
ASPEN had been adapted to many domains, but this is the first time it was adapted to human lunar operations. The small delivery footprint of ASPEN (less than 10Mb), combined with the expressivity and power of the planning engine, makes it uniquely suited for the task of concept of operations evaluation.
This work was done by Russell L. Knight, Sharon L. Laubach, Robert Gershman, Grailing Jones Jr., Brian K. Bairstow, Micheal A. Seibert, and Gene Y. Lee of Caltech for NASA’s Jet Propulsion Laboratory.
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