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Deep Impact Sequence Planning Using Multi-Mission Adaptable Planning Tools With Integrated Spacecraft Models

The Deep Impact mission was ambitious and challenging. JPL's well proven, easily adaptable multi-mission sequence planning tools combined with integrated spacecraft subsystem models enabled a small operations team to develop, validate, and execute extremely complex sequence-based activities within very short development times. This paper focuses on the core planning tool used in the mission, APGEN. It shows how the multi-mission design and adaptability of APGEN made it possible to model spacecraft subsystems as well as ground assets throughout the lifecycle of the Deep Impact project, starting with models of initial, high-level mission objectives, and culminating in detailed predictions of spacecraft behavior during mission-critical activities.

Deep Impact Mission

Deep impact sequence planning using multi-mission adaptable planning tools with integrated spacecraft models

The Deep Impact mission was ambitious and challenging. JPL's well proven, easily adaptable multi-mission sequence planning tools combined with integrated spacecraft subsystem models enabled a small operations team to develop, validate, and execute extremely complex sequence-based activities within very short development times. This paper focuses on the core planning tool used in the mission, APGEN. It shows how the multi-mission design and adaptability of APGEN made it possible to model spacecraft subsystems as well as ground assets throughout the lifecycle of the Deep Impact project, starting with models of initial, high-level mission objectives, and culminating in detailed predictions of spacecraft behavior during mission-critical activities.

Seybold, Calina C.

Development Roadmap of an Evolvable and Extensible Multi-Mission Telecom Planning and Analysis Framework

In this paper, we describe the development roadmap and discuss the various challenges of an evolvable and extensible multi-mission telecom planning and analysis framework. Our long-term goal is to develop a set of powerful flexible telecommunications analysis tools that can be easily adapted to different missions while maintain the common Deep Space Communication requirements. The ability of re-using the DSN ground models and the common software utilities in our adaptations has contributed significantly to our development efforts measured in terms of consistency, accuracy, and minimal effort redundancy, which can translate into shorter development time and major cost savings for the individual missions. In our roadmap, we will address the design principles, technical achievements and the associated challenges for following telecom analysis tools (i) Telecom Forecaster Predictor - TFP (ii) Unified Telecom Predictor - UTP (iii) Generalized Telecom Predictor - GTP (iv) Generic TFP (v) Web-based TFP (vi) Application Program Interface - API (vii) Mars Relay Network Planning Tool - MRNPT.

telecommunications

Using Global Simulations of the Magnetosphere for Multi-Satellite Mission Planning and Data Analysis

We use global simulations of Earth's magnetosphere to assess the scientific return from a multi-satellite mission in the magnetosphere. We examine 4 different scenarios with 20, 40, 80, and 160 satellites, respectively. The satellite orbits are randomized with perigee distances ranging from 2 to 5R(sub E), apogee distances between 10 and 50 R(sub E), and within +/-5R(sub E) of the geocentric solar ecliptic (GSE) equator. For each of these satellite configurations we examine the expected observations during a typical substorm by using time traces obtained from a global simulation at the satellite positions. The 160 satellite configuration yields sufficient information to distinguish between different substorm models without any temporal/spatial ambiguities. An 80 satellite configuration still provides sufficient information for this task, however for fewer events with good satellite conjunctions and with less statistical certainty. For constellations with fewer than 40 satellites time-space ambiguities are likely to remain in the observation. However, any multi-satellite constellation would be a quantum leap in magnetospheric research because of the unprecedented coverage of other regions, because it would enable new measurement techniques that are unique to multi-satellite missions, and because it would enable the use of data assimilation techniques in global models for the first time.

Raeder, Joachim

APGEN Scheduling: 15 Years of Experience in Planning Automation

In this paper, we discuss the scheduling capability of APGEN (Activity Plan Generator), a multi-mission planning application that is part of the NASA AMMOS (Advanced Multi- Mission Operations System), and how APGEN scheduling evolved over its applications to specific Space Missions. Our analysis identifies two major reasons for the successful application of APGEN scheduling to real problems: an expressive DSL (Domain-Specific Language) for formulating scheduling algorithms, and a well-defined process for enlisting the help of auxiliary modeling tools in providing high-fidelity, system-level simulations of the combined spacecraft and ground support system.

sequencing

Artificial intelligence techniques for scheduling Space Shuttle missions

Planning and scheduling of NASA Space Shuttle missions is a complex, labor-intensive process requiring the expertise of experienced mission planners. We have developed a planning and scheduling system using combinations of artificial intelligence knowledge representations and planning techniques to capture mission planning knowledge and automate the multi-mission planning process. Our integrated object oriented and rule-based approach reduces planning time by orders of magnitude and provides planners with the flexibility to easily modify planning knowledge and constraints without requiring programming expertise.

Henke, Andrea L.

Development of a Multi-Phase Mission Planning Tool for NASA X-57 Maxwell

The physical design and operation of electric aircraft like NASA Maxwell X-57 are significantly different than conventionally fueled aircraft. Operational optimization will require close coupling of aerodynamics, propulsion, and power. To address the uncertainty of electric aircraft operation, a system level Mission Planning Tool is developed to simulate all aircraft trajectory phases: taxi, motor run-up, takeoff, climb, cruise, and descent. The Mission Planning Tool captures performance parameters at each point of the trajectory including battery state of charge, the temperatures of components in the electrical system, and propulsion system thrust. This work describes the modeling of each mission phase, and compares the results of simulating a user-specified trajectory, and using a collocated optimal control approach to determine an optimal trajectory. The results show that optimization of the mission show a significant increase in the final battery state of charge over the user- specified simulation strategy. These results will inform the operation of the NASA Maxwell X-57 test flights that will take place this year.

Schnulo, Sydney L.

MPS Editor - An Integrated Sequencing Environment

In today's operations environment, the teams are smaller and need to be more efficient while still ensuring the safety and success of the mission. In addition, teams often begin working on a mission in its early development phases and continue on the team through actual operations. For these reasons the operations teams want to be presented with a software environment that integrates multiple needed software applications as well as providing them with context sensitive editing support for entering commands and sequences of commands. At Jet Propulsion Laboratory, the Multi-Mission Planning and Sequencing (MPS) Editor provided by the Multi-Mission Ground Systems and Services (MGSS) supports those operational needs.

Streiffert, Barbara A.

NASA's Current Initiative to Improve Operations Planning

As a follow-on to the Technical Capability Assessment Team, in 2015 NASA began seven Agency-wide efforts to seek out opportunities to improve the effectiveness of NASA operations. One of these technical teams is the Mission Operations Planning team, charged with increasing interactions and efficiency for planning of mission activities. That team is chaired by the author with representatives from eight other centers across the Agency. As the strategic architects for the vision of agency-wide ops planning, the team has identified a number of new initiatives and techniques to improve planning, including: breaking down walls within centers which obstruct multi-mission planning; breaking down walls agency-wide which obstruct the sharing of ops planning lessons and capabilities; strengthening the community of practice of ops planning capability developers; establishing best practices for a variety of types of ops planning; defining standards for activity plans and timelines, and plan inputs; and recommending the presence of "multi-mission operations champions" within each center to implement these recommendations into the next decade.

Seal, David

Sequencing System Building Blocks: Using a Component Architecture for Sequencing Software

Over the last few years software engineering has made significant strides in making more flexible architectures and designs possible. However, at the same time, spacecraft have become more complex and flight software has become more sophisticated. Typically spacecraft are often one-of-a-kind entities that have different hardware designs, different capabilities, different instruments, etc. Ground software has become more complex and operations teams have had to learn a myriad of tools that all have different user interfaces and represent data in different ways. At Jet Propulsion Laboratory (JPL) these themes have collided to require a new approach to producing ground system software. Two different groups have been looking at tackling this particular problem. One group is working for the JPL Mars Technology Program in the Mars Science Laboratory (MSL) Focused Technology area. The other group is the JPL Multi-Mission Planning and Sequencing Group. The major concept driving these two approaches on a similar path is to provide software that can be a more cohesive flexible system that provides a set of planning and sequencing system of services. This paper describes the efforts that have been made to date to create a unified approach from these disparate groups.

multi mission planning

Streamlining Collaborative Planning in Spacecraft Mission Architectures

During the past two decades, the planning and scheduling community has substantially increased the capability and efficiency of individual planning and scheduling systems. Relatively recently, research work to streamline collaboration between planning systems is gaining attention. Spacecraft missions stand to benefit substantially from this work as they require the coordination of multiple planning organizations and planning systems. Up to the present time this coordination has demanded a great deal of human intervention and/or extensive custom software development efforts. This problem will become acute with increased requirements for cross-mission plan coordination and multi -spacecraft mission planning. The Advanced Architectures and Automation Branch of NASA's Goddard Space Flight Center is taking innovative steps to define collaborative planning architectures, and to identify coordinated planning tools for Cross-Mission Campaigns. Prototypes are being developed to validate these architectures and assess the usefulness of the coordination tools by the planning community. This presentation will focus on one such planning coordination too], named Visual Observation Layout Tool (VOLT), which is currently being developed to streamline the coordination between astronomical missions

Misra, Dhariti

Integrated resource scheduling in a distributed scheduling environment

The Space Station era presents a highly-complex multi-mission planning and scheduling environment exercised over a highly distributed system. In order to automate the scheduling process, customers require a mechanism for communicating their scheduling requirements to NASA. A request language that a remotely-located customer can use to specify his scheduling requirements to a NASA scheduler, thus automating the customer-scheduler interface, is described. This notation, Flexible Envelope-Request Notation (FERN), allows the user to completely specify his scheduling requirements such as resource usage, temporal constraints, and scheduling preferences and options. The FERN also contains mechanisms for representing schedule and resource availability information, which are used in the inter-scheduler inconsistency resolution process. Additionally, a scheduler is described that can accept these requests, process them, generate schedules, and return schedule and resource availability information to the requester. The Request-Oriented Scheduling Engine (ROSE) was designed to function either as an independent scheduler or as a scheduling element in a network of schedulers. When used in a network of schedulers, each ROSE communicates schedule and resource usage information to other schedulers via the FERN notation, enabling inconsistencies to be resolved between schedulers. Individual ROSE schedules are created by viewing the problem as a constraint satisfaction problem with a heuristically guided search strategy.

Zoch, David

Sequence System Building Blocks: Using a Component Architecture for Sequencing Software

Over the last few years software engineering has made significant strides in making more flexible architectures and designs possible. However, at the same time, spacecraft have become more complex and flight software has become more sophisticated. Typically spacecraft are often one-of-a-kind entities that have different hardware designs, different capabilities, different instruments, etc. Ground software has become more complex and operations teams have had to learn a myriad of tools that all have different user interfaces and represent data in different ways. At Jet Propulsion Laboratory (JPL) these themes have collided to require an new approach to producing ground system software. Two different groups have been looking at tackling this particular problem. One group is working for the JPL Mars Technology Program in the Mars Science Laboratory (MSL) Focused Technology area. The other group is the JPL Multi-Mission Planning and Sequencing Group . The major concept driving these two approaches on a similar path is to provide software that can be a more cohesive flexible system that provides a act of planning and sequencing system of services. This paper describes the efforts that have been made to date to create a unified approach from these disparate groups.

flexible architectures

MPST Software: grl_pef_check

This innovation is a tool used to verify and validate spacecraft sequences at the predicted events file (PEF) level for the GRAIL (Gravity Recovery and Interior Laboratory, see http://www.nasa. gov/mission_pages/grail/main/index. html) mission as part of the Multi-Mission Planning and Sequencing Team (MPST) operations process to reduce the possibility for errors. This tool is used to catch any sequence related errors or issues immediately after the seqgen modeling to streamline downstream processes. This script verifies and validates the seqgen modeling for the GRAIL MPST process. A PEF is provided as input, and dozens of checks are performed on it to verify and validate the command products including command content, command ordering, flight-rule violations, modeling boundary consistency, resource limits, and ground commanding consistency. By performing as many checks as early in the process as possible, grl_pef_check streamlines the MPST task of generating GRAIL command and modeled products on an aggressive schedule. By enumerating each check being performed, and clearly stating the criteria and assumptions made at each step, grl_pef_check can be used as a manual checklist as well as an automated tool. This helper script was written with a focus on enabling the user with the information they need in order to evaluate a sequence quickly and efficiently, while still keeping them informed and active in the overall sequencing process. grl_pef_check verifies and validates the modeling and sequence content prior to investing any more effort into the build. There are dozens of various items in the modeling run that need to be checked, which is a time-consuming and errorprone task. Currently, no software exists that provides this functionality. Compared to a manual process, this script reduces human error and saves considerable man-hours by automating and streamlining the mission planning and sequencing task for the GRAIL mission.

Call, Jared A.

Science opportunity analyzer - a multi-mission tool for planning

For many years the diverse scientific community that supports JPL's wide variety ofinterplanetary space missions has needed a tool in order to plan and develop their experiments. The tool needs to be easily adapted to various mission types and portable to the user community. The Science Opportunity Analyzer, SOA, now in its third year of development, is intended to meet this need. SOA is a java-based application that is designed to enable scientists to identify and analyze opportunities for science observations from spacecraft. It differs from other planning tools in that it does not require an in-depth knowledge of the spacecraft command system or operation modes to begin high level planning. Users can, however, develop increasingly detailed levels of design. SOA consists of six major functions: Opportunity Search, Visualization, Observation Design, Constraint Checking, Data Output and Communications. Opportunity Search is a GUI driven interface to existing search engines that can be used to identify times when a spacecraft is in a specific geometrical relationship with other bodies in the solar system. This function can be used for advanced mission planning as well as for making last minute adjustments to mission sequences in response to trajectory modifications. Visualization is a key aspect of SOA. The user can view observation opportunities in either a 3D representation or as a 2D map projection. The user is given extensive flexibility to customize what is displayed in the view. Observation Design allows the user to orient the spacecraft and visualize the projection of the instrument field of view for that orientation using the same views as Opportunity Search. Constraint Checking is provided to validate various geometrical and physical aspects of an observation design. The user has the ability to easily create custom rules or to use official project-generated flight rules. This capability may also allow scientists to easily impact the cost to science if flight rule changes occur. Data Output generates information based on the spacecraft's trajectory, opportunity search results or based on a created observation. The data can be viewed either in tabular format or as a graph. Finally, SOA is unique in that it is designed to be able to communicate with a variety of existing planning and sequencing tools. From the very beginning SOA was designed with the user in mind. Extensive surveys of the potential user community were conducted in order to develop the software requirements. Throughout the development period, close ties have been maintained with the science community to insure that the tool maintains its user focus. Although development is still in its early stages, SOA is already developing a user community on the Cassini project, which is depending on this tool for their science planning. There are other tools at JPL that do various pieces of what SOA can do; however, there is no other tool which combines all these functions and presents them to the user in such a convenient, cohesive, and easy to use fashion.

SOA science planning mission operations sequence s

A Planning Pipeline for Large Multi-Agent Missions

In complex multi-agent applications, human operators are often tasked with planning and managing large heterogeneous teams of humans and autonomous vehicles. Although the use of these autonomous vehicles broadens the scope of meaningful applications, many of their systems remain unintuitive and difficult to master for human operators whose expertise lies in the application domain and not at the platform level. Current research focuses on the development of individual capabilities necessary to plan multi-agent missions of this scope, placing little emphasis on the integration of these components in to a full pipeline. The work presented in this paper presents a complete and user-agnostic planning pipeline for large multiagent missions known as the HOLII GRAILLE. The system takes a holistic approach to mission planning by integrating capabilities in human machine interaction, flight path generation, and validation and verification. Components – modules – of the pipeline are explored on an individual level, as well as their integration into a whole system. Lastly, implications for future mission planning are discussed.

Chandarana, Meghan