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Past Projects

GEO-CAPE Imaging Scenes GEO-CAPE: COEDI Imaging Scenes

GEO-CAPE
Project Lead: Jeremy Frank
The GEO-Stationary Coastal and Air Pollution Events (GEO-CAPE) mission plans to put a visible spectrum imaging instrument on a satellite in geo-stationary orbit to perform ocean color remote sensing. Two different instrument designs, Filter Radiometer (FR) and COastal Ecosystems Dynamic Imager (COEDI), with different shape for the imaged area and image acquisition time, are being evaluated. Scheduling observations for either instrument requires optimizing science objectives in the presence of predicted cloud cover and available daylight. We model this scheduling problem as both Mixed Integer Linear Program (MILP) and Constraint Programming (CP) problems, and compare these two formulations for FR and COEDI using real cloudiness data collected at different times throughout the year. Our results show that MILP is the more suitable technique, and the schedule quality metric shows FR is the preferred design.

An archive containing the problems analyzed in this work and their solution is provided for those who wish to use these problems in their own research.
Download: GEOCAPE_PublicDistribution.zip

Edison Demonstration of Smallsat Networks (EDSN) and Nodes
Project Lead: Javier Barreiro, Michael Dalal
EDSN and Nodes were technology demonstration missions, each featuring a "swarm" of CubeSats designed to orbit approximately 400 kilometers above Earth in loose formation. The missions' primary goal was to demonstrate the potential value of multiple small satellites as tools for a wide array of scientific, commercial, and academic space research. Secondary goals included reducing the cost and time required to design and build future small spacecraft, as well as testing new software applications. EDSN and Nodes made extensive use of LASS (see above), and the flight software adapted some of LASS's constraint-based scheduling algorithms in a novel onboard planner and scheduler that made these nano-satellites fully autonomous.

MSLICE
Project Lead: Alfredo Bencomo
JPL's Mars Science Laboratory (MSL) , known as Curiosity, is a NASA rover that launched in Fall 2011 and landed on Mars in Fall 2012. MSL's overarching science goal is to assess environmental conditions favorable to microbial life, both habitability and preservation. The Mars Science Laboratory Interface (MSLICE) is an application that provides support for the mission with science data visualization & analysis, roundtrip data tracking, scheduling of integrated activity plan, modeling, simulation, and validation of activity plan.

LASS
Project Lead: John Bresina
The LADEE Activity Scheduling System (LASS) is a tool to construct and validate plans at the “orbit” and the “activity” level. The primary components of an activity plan are a set of instantiated activities and a set of temporal constraints between activities. In order for the plan to be valid, these constraints must be satisfied. LASS allows both the science team and engineering team to more quickly plan out what they would like to occur on the spacecraft. This enables the analysis of resource utilization and flight rule compliance before command loads are generated and simulated; thus catching and resolving problems earlier in the operations process.

Solar Array Constraint Engine (SACE)
Project Lead: John Chachere
The SACE software helps International Space Station (ISS) flight controllers safely and effectively operate ISS solar arrays. Flight controllers must position the arrays to collect adequate power for life and experiments on the station, yet avoid numerous hazards, including thruster firings, environmental contamination, communications interference, and extra-vehicular activities. SACE provides flight controllers with awareness of operational constraints that are in danger of being violated either at the current time or in the immediate future, and gives them the ability to plan solar array activities for periods of weeks into the future.

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Next Generation Planning System
Project Lead: Alfredo Bencomo
The Next Generation Planning System (NGPS) is a suite of planning tools being developed as a collaboration between Johnson Space Center (JSC), Ames Research Center (ARC), the Jet Propulsion Laboratory (JPL) which will address planning needs for both ISS and future Mission Operations Directive (MOD) missions. Score is the planning interface to be used by NASA, the European Space Agency (ESA), and the Japan Aerospace Exploration Agency (JAXA) for authoring the operations schedule and validating it against flight rules and constraints. Score also provides an interface for planning collaboration between remote planners as well as a plugin-based architecture for partners from Marshall Space and Flight Center (MSFC), ESA, and JAXA to contribute their own custom tools.

PLATO
Project Lead: Alfredo Bencomo
The Power Planning and Analysis Tool (PLATO), is a preflight planning and a real-time analysis console tool that supports all phases of the International Space Station (ISS) power resource planning. Through consolidation of existing and new power resource planning tools into a single application, PLATO simplifies the power resource planning task, thereby reducing the number of analysts and flight control personnel required to manage the ISS Electrical Power Systems (EPS). Its express purpose is to simplify the power resource planning task and to reduce the number of off-console personnel required for power prediction generation. PLATO provides the capability to allow a SPARTAN Specialist to be able to generate all of the standard Short Term Plan (STP) power planning products, flight specific power planning products, long-range look-ahead power planning products, and any additional what-if scenarios. Additionally, it will permit a SPARTAN Operator, who is managing the electrical power systems and the external thermal control systems, the ability to perform reactive real-time analysis updates without backroom or office support.

ADCO Planning Exchange Tool (APEX)
Project Lead: Michael McCurdy
The objective of APEX is to streamline the existing manual and time-intensive planning tools into a more automated, user-friendly application that interfaces with existing products and allows the Attitude Determination and Control Officer (ADCO) to produce accurate products and timelines more efficiently.

Remote Agent
The Remote Agent Experiment was the first instance of state of the art artificial intelligence system being given primary command of a spacecraft. The Remote Agent software operated NASA's Deep Space 1 spacecraft and its futuristic ion engine during two experiments that started on Monday, May 17, 1999. For two days Remote Agent ran on the on-board computer of Deep Space 1, more than 60,000,000 miles (96,500,000 kilometers) from Earth.
+ Visit Remote Agent

Decision Theoretic Planning for Planetary Exploration
Project Lead: Nicolas Meuleau
This project aimed at producing high-quality contingency planning and re-planning solutions by scaling-up decision theoretic techniques to real NASA problems. We used planetary rovers as a test-bed and focused on these issues: structured and concurrent planning domains, continuous uncertain state variables, and oversubscription.

Constraint and Flight Rule Management (ConFRM)
Project Lead: Jeremy Frank
ConFRM centralizes the creation, maintenance, and validation of the thousands of operational constraints that govern human spaceflight operations.

Game Theoretic Scheduling of the Deep Space Network
Project Lead: Jeremy Frank
NASA missions over the next two decades will require communications bandwidth that exceeds current Deep Space Network capacity by an order of magnitude or more. We explored the use of game theory to extend scheduling technology to negotiate schedules for the Deep Space Network to improve the overall effectiveness of the schedules while reducing the staffing requirements needed to produce and maintain schedules.

Mixed-Initiative Planning
Project Lead: John Bresina
This research explored fundamental issues of mixed-initiative planning and scheduling. We focused on enabling the user to specify preferred solution characteristics, providing effective summarizations and comparisons of solutions, and providing explanations of planning decisions and failures.

SOFIA Observation Scheduling
Project Lead: Jeremy Frank
We prototyped observation scheduling and flight planning techniques for the Stratospheric Observatory for Infrared Astronomy (SOFIA) airborne observatory.

Automation For Operations
Project Lead: Jeremy Frank
(Note: formerly Spacecraft Autonomy for Vehicles and Habitats, led by Ari Jonsson).
The Automation for Operations (A4O) developed advanced mission operations technology for Constellation, NASA’s plan to return to the Moon in response to the President’s Vision for Space Exploration (VSE). A4O developed an evolvable mission operations architecture to automate the operations of manned space vehicles, unoccupied space vehicles, surface assets, and robotic systems. The architecture consists of a small number of modular, interoperable and reconfigurable components, clear component definitions, and interfaces for information exchange. The main components include automated planners, plan execution systems, customizable user interfaces, and integrated verification and validation (V&V) services. Accomplishments included demonstration of peer-to-peer crew, power and stowage planning and automation of human spaceflight procedures to the Mission Operations Directorate at JSC, and robotic systems and habitat automation as part of several analog field tests. Participating centers included NASA Ames, JPL, JSC and LaRC.

Automated Planning Technology (APT)
Project Lead: Brad Clement (JPL)
As part of the Autonomous Systems and Avionics project, we seek to reduce the gaps between models used for high-fidelity simulations and those used for automated planning. We are developing tools and interfaces to extract, modify, and verify high-level plans using simulation models.

Viz
Project Lead: Leslie Keely
Viz is a data visualization tool that provides scientists, robot operators, and mission planners with powerful, interactive 3D displays of remote environments. Viz was originally developed for Mars Polar Lander (2001), and has been used for the Mars Exploration Rover (2003) and the Phoenix Lander (2008).

UAVs in the National Airspace
Project Lead: Javier Barreiro
Unmanned Aircraft Systems (UAS) are increasingly being used by government and the private sector to perform tasks in earth science, disaster monitoring and recovery, transportation and many others. The FAA is leading an effort to streamline UAS access to the National Airspace (NAS). Our group is contributing expertise for nominal and contingency planning to the creation of a Concept of Operations for regular UAS operations in the NAS over the next decade.

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