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At least 109 records · Page 6

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↗

Ames Research Center FY 2000 Implementation Plan: Leading Technology into the New Millennium

This document presents the implementation plan for Ames Research Center (ARC) within the overall framework of the NASA Strategic Plan. It describes how ARC intends to implement its Center of Excellence responsibilities, Agency assigned missions, Agency and Enterprise lead programs, and other roles in support of NASA's vision and mission. All Federal agencies are required by the 1993 Government Performance and Results Act to implement a long-term strategic planning process that includes measurable outcomes and strict accountability. At NASA, this planning process is shaped by the Space Act of 1958, annual appropriations, and other external mandates, as well as by customer requirements. The resulting Strategic Plan sets the overall architecture for what we do, identifies who our customers are, and directs where we are going and why. The Strategic Plan is the basis upon which decisions regarding program implementation and resource deployment are made. Whereas the strategic planning process examines the long-term direction of the organization and identifies a specific set of goals, the implementation planning process examines the detailed performance of the organization and allocates resources toward meeting these goals. It is the purpose of this implementation document to provide the connection between the NASA Strategic Plan and the specific programs and support functions that ARC employees perform. This connection flows from the NASA Strategic Plan, through the various Strategic Enterprise plans to the ARC Center of Excellence, primary missions, Lead Center programs, program support responsibilities, and ultimately, to the role of the individual ARC employee.

Source record↗

MAPGEN: Mixed-Initiative Activity Planning for the Mars Exploration Rover Mission

This document describes the Mixed initiative Activity Plan Generation system MAPGEN. This system is one of the critical tools in the Mars Exploration Rover mission surface operations, where it is used to build activity plans for each of the rovers, each Martian day. The MAPGEN system combines an existing tool for activity plan editing and resource modeling, with an advanced constraint-based reasoning and planning framework. The constraint-based planning component provides active constraint and rule enforcement, automated planning capabilities, and a variety of tools and functions that are useful for building activity plans in an interactive fashion. In this demonstration, we will show the capabilities of the system and demonstrate how the system has been used in actual Mars rover operations. In contrast to the demonstration given at ICAPS 03, significant improvement have been made to the system. These include various additional capabilities that are based on automated reasoning and planning techniques, as well as a new Constraint Editor support tool. The Constraint Editor (CE) as part of the process for generating these command loads, the MAPGEN tool provides engineers and scientists an intelligent activity planning tool that allows them to more effectively generate complex plans that maximize the science return each day. The key to the effectiveness of the MAPGEN tool is an underlying constraint-based planning and reasoning engine.

Ai-Chang, Mitchell↗

ISS Operations Cost Reductions Through Automation of Real-Time Planning Tasks

In 2008 the Johnson Space Center s Mission Operations Directorate (MOD) management team challenged their organization to find ways to reduce the costs of International Space station (ISS) console operations in the Mission Control Center (MCC). Each MOD organization was asked to identify projects that would help them attain a goal of a 30% reduction in operating costs by 2012. The MOD Operations and Planning organization responded to this challenge by launching several software automation projects that would allow them to greatly improve ISS console operations and reduce staffing and operating costs. These projects to date have allowed the MOD Operations organization to remove one full time (7 x 24 x 365) ISS console position in 2010; with the plan of eliminating two full time ISS console support positions by 2012. This will account for an overall 10 EP reduction in staffing for the Operations and Planning organization. These automation projects focused on utilizing software to automate many administrative and often repetitive tasks involved with processing ISS planning and daily operations information. This information was exchanged between the ground flight control teams in Houston and around the globe, as well as with the ISS astronaut crew. These tasks ranged from managing mission plan changes from around the globe, to uploading and downloading information to and from the ISS crew, to even more complex tasks that required multiple decision points to process the data, track approvals and deliver it to the correct recipient across network and security boundaries. The software solutions leveraged several different technologies including customized web applications and implementation of industry standard web services architecture between several planning tools; as well as a engaging a previously research level technology (TRL 2-3) developed by Ames Research Center (ARC) that utilized an intelligent agent based system to manage and automate file traffic flow, archiving f data, and generating console logs. This technology called OCAMS (OCA (Orbital Communication System) Management System), is now considered TRL level 9 and is in daily use in the Mission Control Center in support of ISS operations. These solutions have not only allowed for improved efficiency on console; but since many of the previously manual data transfers are now automated, many of the human error prone steps have been removed, and the quality of the planning products has improved tremendously. This has also allowed our Planning Flight Controllers more time to focus on the abstract areas of the job, (like the complexities of planning a mission for 6 international crew members with a global planning team), instead of being burdened with the administrative tasks that took significant time each console shift to process. The resulting automation solutions have allowed the Operations and Planning organization to realize significant cost savings for the ISS program through 2020 and many of these solutions could be a viable

Hall, Timothy A.↗

Domain Compilation for Embedded Real-Time Planning

A recently conceived approach to automated real-time control of the actions of a robotic system enables an embedded real-time planning algorithm to develop plans that are more robust than they would otherwise be, without imposing an excessive computational burden. This approach occupies a middle ground between two prior approaches known in the art as the universal-plan and hybrid approaches. Ever since discovering the performance limitations of taking a sense-plan-act approach to controlling robots, the robotics community has endeavored to follow a behavior-based approach in which a behavior includes a rapid feedback loop between state estimation and motor control. Heretofore, system architectures following this approach have been based, variously, on algorithms that implement universal plans or algorithms that function as hybrids of planners and executives. In a typical universal-plan case, a set of behaviors is merged into the plan, but the system must be restricted to relatively small problem domains to avoid having to reason about too many states and represent them in the plan. In the hybrid approach, one implements actions as small sets of behaviors, each applicable to a limited set of circumstances. Each action is intended to bring the system to a subgoal state. A planning algorithm is used to string these actions together into a sequence to traverse the state space from an initial or current state to a goal state. The hybrid approach works well in a static environment, but it is inherently brittle in a dynamic environment because a failure can occur when the environment strays beyond the region of applicability of the current activity. In the present approach, a system can vary from the hybrid approach to the universal-plan approach, depending on a single integer parameter, denoted n, which can range from 1 to a maximum domain-dependent value of M. As illustrated in the figure, n = 1 represents the hybrid approach, in which each linked action covers a small part of the state space of the system. As n increases, the portion of state space associated with each action and its subgoal grows. When n reaches M, coverage extends over the full state space, so that the system contains a universal plan.

Barrett, Anthony↗

Innovative Development of a Cross-Center Timeline Planning Tool

The Payload Operations Integration Center (POIC) at Marshall Space Flight Center (MSFC) is the United States focal point to support operations controllers and payload developers conducting payload science operations for the National Aeronautics and Space Administration (NASA) aboard the International Space Station (ISS). Some of the key functions are planning, coordination and scheduling of science activities. This effort occurs in coordination with other NASA centers, international partners, and payload developers. The ability to efficiently plan and re-plan in response to change is critical to the flight planning teams. Additionally, in Fall 2017, NASA will increase its ability to perform payload science operations aboard the ISS with a fourth crew member. In order to support this, there will be an increasing need to quickly plan and schedule more activities. In the past, it was cumbersome and time-consuming to consolidate copious amounts of planning and change request data from various sources. Planners would summarize information from the Johnson Space Center (JSC) Operations Planning Timeline Integration System (OPTIMIS) and manually integrate it with other data in order to produce a Timeline Planning Summary (TPS). This lengthy process of updating static documents while planning and re-planning was cumbersome, introduced human error, and was inflexible to last minute changes. There was a need for a dynamic, more efficient, less erroneous, and more concise way of building a report that could be readily updated as fast as payload science plans change.

Pedoto, Ramon W.↗

Abstraction Planning in Real Time

When a planning agent works in a complex, real-world domain, it is unable to plan for and store all possible contingencies and problem situations ahead of time. This thesis presents a method for planning a run time that incrementally builds up plans at multiple levels of abstraction. The plans are continually updated by information from the world, allowing the planner to adjust its plan to a changing world during the planning process. All the information is represented over intervals of time, allowing the planner to reason about durations, deadlines, and delays within its plan. In addition to the method, the thesis presents a formal model of the planning process and uses the model to investigate planning strategies.

COMPUTER PROGRAMMING↗

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol(Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

activity planning↗

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol(Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

activity planning↗

Trimodal interpretation of constraints for planning

Constraints are used in the CAMPS knowledge based planning system to represent those propositions that must be true for a plan to be acceptable. CAMPS introduces the make-mode for interpreting a constraint. Given an unsatisfied constraint, make evaluation mode suggests planning actions which, if taken, would result in a modified plan in which the constraint in question may be satisfied. These suggested planning actions, termed delta-tuples, are the raw material of intelligent plan repair. They are used both in debugging an almost-right plan and in replanning due to changing situations. Given a defective plan in which some set of constraints are violated, a problem solving strategy selects one or more constraints as a focus of attention. These selected constraints are evaluated in the make-mode to produce delta-tuples. The problem solving strategy then reviews the delta-tuples according to its application and problem-specific criteria to find the most acceptable change in terms of success likelihood and plan disruption. Finally, the problem solving strategy makes the suggested alteration to the plan and then rechecks constraints to find any unexpected consequences.

Krieger, David↗

Development of an expert planning system for OSSA

This paper presents concepts related to preliminary work for the development of an expert planning system for NASA's Office for Space Science and Applications (OSSA). The expert system will function as a planner's decision aid in preparing mission plans encompassing sets of proposed OSSA space science initiatives. These plans in turn will be checked against budgetary and technical constraints and tested for constraint violations. Appropriate advice will be generated by the system for making modifications to the plans to bring them in line with the constraints. The OSSA Planning Expert System (OPES) has been designed to function as an integral part of the OSSA mission planning process. It will be able to suggest a best plan, be able to accept and check a user-suggested strawman plan, and should provide a quick response to user request and actions. OPES will be written in the C programming language and have a transparent user interface running under Windows 386 on a Compaq 386/20 machine. The system's sorted knowledge and inference procedures will model the expertise of human planners familiar with the OSSA planning domain. Given mission priorities and budget guidelines, the system first sets the launch dates for each mission. It will check to make sure that planetary launch windows and precursor mission relationships are not violated. Additional levels of constraints will then be considered, checking such things as the availability of a suitable launch vehicle, total mission launch mass required vs. the identified launch mass capability, and the total power required by the payload at its destination vs. the actual power available. System output will be in the form of Gantt charts, spreadsheet hardcopy, and other presentation quality materials detailing the resulting OSSA mission plan.

Groundwater, B.↗

Agent independent task planning

Agent-Independent Planning is a technique that allows the construction of activity plans without regard to the agent that will perform them. Once generated, a plan is then validated and translated into instructions for a particular agent, whether a robot, crewmember, or software-based control system. Because Space Station Freedom (SSF) is planned for orbital operations for approximately thirty years, it will almost certainly experience numerous enhancements and upgrades, including upgrades in robotic manipulators. Agent-Independent Planning provides the capability to construct plans for SSF operations, independent of specific robotic systems, by combining techniques of object oriented modeling, nonlinear planning and temporal logic. Since a plan is validated using the physical and functional models of a particular agent, new robotic systems can be developed and integrated with existing operations in a robust manner. This technique also provides the capability to generate plans for crewmembers with varying skill levels, and later apply these same plans to more sophisticated robotic manipulators made available by evolutions in technology.

Davis, William S.↗

A distributed planning concept for Space Station payload operations

The complex and diverse nature of the payload operations to be performed on the Space Station requires a robust and flexible planning approach. The planning approach for Space Station payload operations must support the phased development of the Space Station, as well as the geographically distributed users of the Space Station. To date, the planning approach for manned operations in space has been one of centralized planning to the n-th degree of detail. This approach, while valid for short duration flights, incurs high operations costs and is not conducive to long duration Space Station operations. The Space Station payload operations planning concept must reduce operations costs, accommodate phased station development, support distributed users, and provide flexibility. One way to meet these objectives is to distribute the planning functions across a hierarchy of payload planning organizations based on their particular needs and expertise. This paper presents a planning concept which satisfies all phases of the development of the Space Station (manned Shuttle flights, unmanned Station operations, and permanent manned operations), and the migration from centralized to distributed planning functions. Identified in this paper are the payload planning functions which can be distributed and the process by which these functions are performed.

Hagopian, Jeff↗

Planning in the Continuous Operations Environment of the International Space Station

The continuous operation planning approach developed for the operations planning of the International Space Station (ISS) is reported on. The approach was designed to be a robust and cost-effective method. It separates ISS planning into two planning functions: long-range planning for a fixed length planning horizon which continually moves forward as ISS operations progress, and short-range planning which takes a small segment of the long-range plan and develops a detailed operations schedule. The continuous approach is compared with the incremental approach, the short and long-range planning functions are described, and the benefits and challenges of implementing a continuous operations planning approach for the ISS are summarized.

Maxwell, Theresa↗

Introduction of International Microgravity Strategic Planning Group

Established in May 6, 1995, the purpose of this International Strategic Planning Group for Microgravity Science and Applications Research is to develop and update, at least on a biennial basis, an International Strategic Plan for Microgravity Science and Applications Research. The member space agencies have agreed to contribute to the development of a Strategic Plan, and seek the implementation of the cooperative programs defined in this Plan. The emphasis of this plan is the coordination of hardware construction and utilization within the various areas of research including biotechnology, combustion science, fluid physics, materials science and other special topics in physical sciences. The Microgravity Science and Applications International Strategic Plan is a joint effort by the present members - ASI, CNES, CSA, DLR, ESA, NASA, and NASDA. It represents the consensus from a series of discussions held within the International Microgravity Strategic Planning Group (IMSPG). In 1996 several space agencies initiated multilateral discussions on how to improve the effectiveness of international microgravity research during the upcoming Space Station era. These discussions led to a recognition of the need for a comprehensive strategic plan for international microgravity research that would provide a framework for cooperation between international agencies. The Strategic Plan is intended to provide a basis for inter-agency coordination and cooperation in microgravity research in the environment of the International Space Station (ISS) era. This will be accomplished through analysis of the interests and goals of each participating agency and identification of mutual interests and program compatibilities. The Plan provides a framework for maximizing the productivity of space-based research for the benefit of our societies.

Rhome, Robert↗

Cassini's Grand Finale: A Mission Planning Retrospective

On September 15, 2017, Cassini plunged deep into Saturn, down to where the atmosphere was sufficiently dense to destroy the spacecraft, making it part of Saturn forever. In the five months leading up to its destruction, Cassini flew between Saturn and its rings 22 times, collecting data from the never before-explored region of the Kronian system. These orbits, the Grand Finale of Cassini, were the culmination of years of planning by the Cassini flight team. This paper looks back upon the mission planning effort in particular, comparing the baseline operational scenarios and contingency plans to the as flown Grand Finale. The bulk of the Grand Finale mission planning effort was focused on the environmental hazards present in the region between Saturn and its rings: the dust and the atmosphere. Dust hazard and atmospheric transit contingency plans were in place to help ensure spacecraft health and maximize science data return. The dust hazard plan gave the operations team the option to turn the spacecraft to a safe attitude during ring-plane crossings had the dust environment proved more threatening than anticipated. The atmospheric transit plan would have made use of an orbital trim maneuver in order to raise or lower periapsis depending on the density of the atmosphere. The proximal environment did have its surprises, though they were good surprises. The dust was significantly less hazardous than predicted. So much so that elements of the contingency plan were leveraged in order to remove a dust hazard protection from the baseline plan, rather than add one to it. While the atmosphere was substantially denser than predicted, it was not dense enough to warrant a periapsis-raise maneuver and actually meant that better in-situ data was gathered. Ultimately, from a mission planning perspective, the Grand Finale went better than expected.

Sturm II, Erick J.↗

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↗

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol (Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

Kanefsky, Bob↗