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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Plan Execution Interchange Language (PLEXIL)

Plan execution is a cornerstone of spacecraft operations, irrespective of whether the plans to be executed are generated on board the spacecraft or on the ground. Plan execution frameworks vary greatly, due to both different capabilities of the execution systems, and relations to associated decision-making frameworks. The latter dependency has made the reuse of execution and planning frameworks more difficult, and has all but precluded information sharing between different execution and decision-making systems. As a step in the direction of addressing some of these issues, a general plan execution language, called the Plan Execution Interchange Language (PLEXIL), is being developed. PLEXIL is capable of expressing concepts used by many high-level automated planners and hence provides an interface to multiple planners. PLEXIL includes a domain description that specifies command types, expansions, constraints, etc., as well as feedback to the higher-level decision-making capabilities. This document describes the grammar and semantics of PLEXIL. It includes a graphical depiction of this grammar and illustrative rover scenarios. It also outlines ongoing work on implementing a universal execution system, based on PLEXIL, using state-of-the-art rover functional interfaces and planners as test cases.

Estlin, Tara↗
NASA NTRS2009

Rewriting Logic Semantics of a Plan Execution Language

The Plan Execution Interchange Language (PLEXIL) is a synchronous language developed by NASA to support autonomous spacecraft operations. In this paper, we propose a rewriting logic semantics of PLEXIL in Maude, a high-performance logical engine. The rewriting logic semantics is by itself a formal interpreter of the language and can be used as a semantic benchmark for the implementation of PLEXIL executives. The implementation in Maude has the additional benefit of making available to PLEXIL designers and developers all the formal analysis and verification tools provided by Maude. The formalization of the PLEXIL semantics in rewriting logic poses an interesting challenge due to the synchronous nature of the language and the prioritized rules defining its semantics. To overcome this difficulty, we propose a general procedure for simulating synchronous set relations in rewriting logic that is sound and, for deterministic relations, complete. We also report on the finding of two issues at the design level of the original PLEXIL semantics that were identified with the help of the executable specification in Maude.

Dowek, Gilles↗
NASA NTRS2011

The Planning Execution Monitoring Architecture

The Planning Execution Monitoring (PEM) architecture is a design concept for developing autonomous cockpit command and control software. The PEM architecture is designed to reduce the operations costs in the space transportation system through the use of automation while improving safety and operability of the system. Specifically, the PEM autonomous framework enables automatic performance of many vehicle operations that would typically be performed by a human. Also, this framework supports varying levels of autonomous control, ranging from fully automatic to fully manual control. The PEM autonomous framework interfaces with the core flight software to perform flight procedures. It can either assist human operators in performing procedures or autonomously execute routine cockpit procedures based on the operational context. Most importantly, the PEM autonomous framework promotes and simplifies the capture, verification, and validation of the flight operations knowledge. Through a hierarchical decomposition of the domain knowledge, the vehicle command and control capabilities are divided into manageable functional "chunks" that can be captured and verified separately. These functional units, each of which has the responsibility to manage part of the vehicle command and control, are modular, re-usable, and extensible. Also, the functional units are self-contained and have the ability to plan and execute the necessary steps for accomplishing a task based upon the current mission state and available resources. The PEM architecture has potential for application outside the realm of spaceflight, including management of complex industrial processes, nuclear control, and control of complex vehicles such as submarines or unmanned air vehicles.

Wang, Lui↗
NASA NTRS2003

Identifying Executable Plans

Generating plans for execution imposes a different set of requirements on the planning process than those imposed by planning alone. In highly unpredictable execution environments, a fully-grounded plan may become inconsistent frequently when the world fails to behave as expected. Intelligent execution permits making decisions when the most up-to-date information is available, ensuring fewer failures. Planning should acknowledge the capabilities of the execution system, both to ensure robust execution in the face of uncertainty, which also relieves the planner of the burden of making premature commitments. We present Plan Identification Functions (PIFs), which formalize what it means for a plan to be executable, md are used in conjunction with a complete model of system behavior to halt the planning process when an executable plan is found. We describe the implementation of plan identification functions for a temporal, constraint-based planner. This particular implementation allows the description of many different plan identification functions. characteristics crf the ~xec~~tieonfvii r~nm-enft,h e best plan to hand to the execution system will contain more or less commitment and information.

Bedrax-Weiss, Tania↗
NASA NTRS1993

Combining qualitative and quantitative spatial and temporal information in a hierarchical structure: Approximate reasoning for plan execution monitoring

The problem of plan generation (PG) and the problem of plan execution monitoring (PEM), including updating, queries, and resource-bounded replanning, have different reasoning and representation requirements. PEM requires the integration of qualitative and quantitative information. PEM is the receiving of data about the world in which a plan or agent is executing. The problem is to quickly determine the relevance of the data, the consistency of the data with respect to the expected effects, and if execution should continue. Only spatial and temporal aspects of the plan are addressed for relevance in this work. Current temporal reasoning systems are deficient in computational aspects or expressiveness. This work presents a hybrid qualitative and quantitative system that is fully expressive in its assertion language while offering certain computational efficiencies. In order to proceed, methods incorporating approximate reasoning using hierarchies, notions of locality, constraint expansion, and absolute parameters need be used and are shown to be useful for the anytime nature of PEM.

Hoebel, Louis J.↗
NASA NTRS2018

Plan Execution Interchange Language (PLEXIL) Software User's Manual

Plan Execution Interchange Language (PLEXIL) is a Core Flight System (or Core Flight Software) (cFS) based application, developed by the Autonomy Operating System project at NASA. cFS is open-source, reusable flight software, also developed by NASA and targeted to space missions. PLEXIL runs within the cFS framework, and is a wrapper integrating the open source PLEXIL Executive into the cFE (core Flight Executive) infrastructure. Software features include: Executes PLEXIL plans stored on local file system; Can be event-driven or clock-driven; and, Intended for "soft real time" discrete control.

Fry, Charles R.↗
NASA NTRS1988

Diagnosing faults in autonomous robot plan execution

A major requirement for an autonomous robot is the capability to diagnose faults during plan execution in an uncertain environment. Many diagnostic researches concentrate only on hardware failures within an autonomous robot. Taking a different approach, the implementation of a Telerobot Diagnostic System that addresses, in addition to the hardware failures, failures caused by unexpected event changes in the environment or failures due to plan errors, is described. One feature of the system is the utilization of task-plan knowledge and context information to deduce fault symptoms. This forward deduction provides valuable information on past activities and the current expectations of a robotic event, both of which can guide the plan-execution inference process. The inference process adopts a model-based technique to recreate the plan-execution process and to confirm fault-source hypotheses. This technique allows the system to diagnose multiple faults due to either unexpected plan failures or hardware errors. This research initiates a major effort to investigate relationships between hardware faults and plan errors, relationships which were not addressed in the past. The results of this research will provide a clear understanding of how to generate a better task planner for an autonomous robot and how to recover the robot from faults in a critical environment.

Lam, Raymond K.↗
NASA NTRS1989

Diagnosing faults in autonomous robot plan execution

A major requirement for an autonomous robot is the capability to diagnose faults during plan execution in an uncertain environment. Many diagnostic researches concentrate only on hardware failures within an autonomous robot. Taking a different approach, the implementation of a Telerobot Diagnostic System that addresses, in addition to the hardware failures, failures caused by unexpected event changes in the environment or failures due to plan errors, is described. One feature of the system is the utilization of task-plan knowledge and context information to deduce fault symptoms. This forward deduction provides valuable information on past activities and the current expectations of a robotic event, both of which can guide the plan-execution inference process. The inference process adopts a model-based technique to recreate the plan-execution process and to confirm fault-source hypotheses. This technique allows the system to diagnose multiple faults due to either unexpected plan failures or hardware errors. This research initiates a major effort to investigate relationships between hardware faults and plan errors, relationships which were not addressed in the past. The results of this research will provide a clear understanding of how to generate a better task planner for an autonomous robot and how to recover the robot from faults in a critical environment.

Lam, Raymond K.↗
NASA NTRS1989

Integrating planning, execution, and learning

To achieve the goal of building an autonomous agent, the usually disjoint capabilities of planning, execution, and learning must be used together. An architecture, called MAX, within which cognitive capabilities can be purposefully and intelligently integrated is described. The architecture supports the codification of capabilities as explicit knowledge that can be reasoned about. In addition, specific problem solving, learning, and integration knowledge is developed.

Kuokka, Daniel R.↗
NASA NTRS2019

Overview of the PLEXIL Plan Execution Technology and its Applications in Autonomous Piloting Projects at NASA

Automated planning is a key Artificial Intelligence technology enabling Unmanned Aerial Systems (UAS) and the eminent reality of Urban Air Mobility (UAM). It produces plans, which formalize procedures often performed by humans. Plans differ from other kinds of computer programs in their ability to react and interact with a dynamically changing environment. Aviation plans must encode the procedural knowledge, reasoning capability, and capacity for multi-tasking held by competent human pilots. Correct execution of these plans (performed by software called an executive) in the dynamic airspace environment is vital to the success of each automated flight, and the safety of the vehicle and all things in its path. In the early 2000s NASA developed a plan representation language and executive called PLEXIL (Plan Execution Interchange Language) that has successfully been applied in several NASA aviation and UAS projects. Autonomy Operating System (AOS), Cockpit Hierarchical Automated Planning and Execution (CHAP-E), and ICAROUS are all projects that have used PLEXIL to help encode and automatically execute flight procedures, some normally performed by human pilots. AOS also automates a subset of pilot/Air Traffic Control communication towards enabling UAS entry into the National Airspace. PLEXIL has been open-source software since 2008 and has seen usage in a wide range of prototypical autonomy applications in academia, government, and industry. In this presentation, we describe PLEXIL and highlight its significant accomplishments in the aviation domain.

Dalal, Michael↗
NASA NTRSDate not supplied

The 7 Year Evolution of EOS CA Support for Planning & Executing Risk Mitigation Maneuvers

This presentation will discuss the evolution of Collision Avoidance (CA) support for planning and executing Risk Mitigation Maneuvers (RMMs) for the Earth Observing System (EOS) Aqua, Aura, and Terra satellites within the seven-year period of January 2015 through December 2021. Several enhancements were implemented by the EOS team to expedite and improve the RMM planning and execution process, including updates to High Interest Event (HIE) analysis, maneuver preparation, maneuver ephemeris generation, conjunction event data screening, and maneuver commanding. As of 2022, these advancements allow the EOS team to plan and execute an RMM within 5 hours of identification with an accurate and low-risk solution. This represents a vast improvement from the 30 hours required to turn around an RMM back in 2015. In addition, the current process is substantially less error prone. Details of this progression and the specific aspects of each supporting component are explicated in the content of the presentation.

Syed Hasan↗
NASA NTRS1989

Parallel plan execution with self-processing networks

A critical issue for space operations is how to develop and apply advanced automation techniques to reduce the cost and complexity of working in space. In this context, it is important to examine how recent advances in self-processing networks can be applied for planning and scheduling tasks. For this reason, the feasibility of applying self-processing network models to a variety of planning and control problems relevant to spacecraft activities is being explored. Goals are to demonstrate that self-processing methods are applicable to these problems, and that MIRRORS/II, a general purpose software environment for implementing self-processing models, is sufficiently robust to support development of a wide range of application prototypes. Using MIRRORS/II and marker passing modelling techniques, a model of the execution of a Spaceworld plan was implemented. This is a simplified model of the Voyager spacecraft which photographed Jupiter, Saturn, and their satellites. It is shown that plan execution, a task usually solved using traditional artificial intelligence (AI) techniques, can be accomplished using a self-processing network. The fact that self-processing networks were applied to other space-related tasks, in addition to the one discussed here, demonstrates the general applicability of this approach to planning and control problems relevant to spacecraft activities. It is also demonstrated that MIRRORS/II is a powerful environment for the development and evaluation of self-processing systems.

Dautrechy, C. Lynne↗
NASA NTRS1989

Parallel plan execution with self-processing networks

A critical issue for space operations is how to develop and apply advanced automation techniques to reduce the cost and complexity of working in space. In this context, it is important to examine how recent advances in self-processing networks can be applied for planning and scheduling tasks. For this reason, the feasibility of applying self-processing network models to a variety of planning and control problems relevant to spacecraft activities is being explored. Goals are to demonstrate that self-processing methods are applicable to these problems, and that MIRRORS/II, a general purpose software environment for implementing self-processing models, is sufficiently robust to support development of a wide range of application prototypes. Using MIRRORS/II and marker passing modelling techniques, a model of the execution of a Spaceworld plan was implemented. This is a simplified model of the Voyager spacecraft which photographed Jupiter, Saturn, and their satellites. It is shown that plan execution, a task usually solved using traditional artificial intelligence (AI) techniques, can be accomplished using a self-processing network. The fact that self-processing networks were applied to other space-related tasks, in addition to the one discussed here, demonstrates the general applicability of this approach to planning and control problems relevant to spacecraft activities. It is also demonstrated that MIRRORS/II is a powerful environment for the development and evaluation of self-processing systems.

D'Autrechy, C. Lynne↗
NASA NTRS2006

Adjustably Autonomous Multi-agent Plan Execution with an Internal Spacecraft Free-Flying Robot Prototype

We present an multi-agent model-based autonomy architecture with monitoring, planning, diagnosis, and execution elements. We discuss an internal spacecraft free-flying robot prototype controlled by an implementation of this architecture and a ground test facility used for development. In addition, we discuss a simplified environment control life support system for the spacecraft domain also controlled by an implementation of this architecture. We discuss adjustable autonomy and how it applies to this architecture. We describe an interface that provides the user situation awareness of both autonomous systems and enables the user to dynamically edit the plans prior to and during execution as well as control these agents at various levels of autonomy. This interface also permits the agents to query the user or request the user to perform tasks to help achieve the commanded goals. We conclude by describing a scenario where these two agents and a human interact to cooperatively detect, diagnose and recover from a simulated spacecraft fault.

Dorais, Gregory A.↗
NASA NTRS2018

Playbook for UAS: UX of Goal-Oriented Planning & Execution

We are evaluating the tool Playbook, a mission planning and scheduling tool used for analog missions and research experiments at NASA. We are adapting Playbook to support an unmanned aerial vehicle (UAV) demonstration that will simulate a "search and recover" mission. To support this demonstration, we need to test this software and its usability with human subjects. Playbook will be used to plan, edit, and monitor simulated UAV swarms, and we are interested in evaluating these capabilities. Allocation of roles and responsibilities between human-automation systems is key to promoting productive cooperation between these two agents. When guiding swarms the user should not be concerned with moving waypoints, adjusting heading and altitude or any other small actions that traditional pilots control. Providing situational awareness through sensor data including radar, heat, live camera feed, and topographic information are key when managing multiple UAVs together. First responders need a good picture of disaster areas in order to make informed decisions. These sensors can initiate movements in the mission that indicate when the human should take control of single aircraft.

UAV swarms↗
NASA NTRS1999

EOS Science Plan and EOS Science Plan Executive Summary

Remote sensing of aerosol properties from space is reviewed both for present and planned national and international satellite sensors. Techniques that are being used to enhance our ability to characterize the global distribution of aerosol properties include well-calibrated multispectral radiometers, multispectral polarimeters, and multi-angle spectroradiometers. Though most of these sensor systems rely primarily on visible to mid-infrared spectral channels, the availability of thermal channels to aid in cloud screening is an important additional piece of information that is not always incorporated into the sensor design. In this paper, we describe the various satellite sensor systems being developed by Europe, Japan, and the U.S., and highlight the advantages and disadvantages of each of these systems for aerosol applications. An important underlying theme is that the remote sensing of aerosol properties, especially aerosol size distribution and single scattering albedo, is exceedingly difficult. As a consequence, no one sensor system is capable of providing totally unambiguous information, and hence a careful intercomparison of derived products from different sensors, together with a comprehensive network of ground-based sunphotometer and sky radiometer systems, are required to advance our quantitative understanding of global aerosol characteristics.

King, Michael D.↗
NASA NTRS2010

Assessment of Scheduling and Plan Execution of Apollo 14 Lunar Surface Operations

Although over forty years have passed since first landing on the Moon, there is not yet a comprehensive, quantitative assessment of Apollo extravehicular activities (EVAs). Quantitatively evaluating lunar EVAs will provide a better understanding of the challenges involved with surface operations. This first evaluation of a surface EVA centers on comparing the planned and the as-ran timeline, specifically collecting data on discrepancies between durations that were estimated versus executed. Differences were summarized by task categories in order to gain insight as to the type of surface operation activities that were most challenging. One Apollo 14 EVA was assessed utilizing the described methodology. Selected metrics and task categorizations were effective, and limitations to this process were identified.

Marquez, Jessica J.↗