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The MAP Autonomous Mission Control System

The Microwave Anisotropy Probe (MAP) mission is the second mission in NASA's Office of Space Science low-cost, Medium-class Explorers (MIDEX) program. The Explorers Program is designed to accomplish frequent, low cost, high quality space science investigations utilizing innovative, streamlined, efficient management, design and operations approaches. The MAP spacecraft will produce an accurate full-sky map of the cosmic microwave background temperature fluctuations with high sensitivity and angular resolution. The MAP spacecraft is planned for launch in early 2001, and will be staffed by only single-shift operations. During the rest of the time the spacecraft must be operated autonomously, with personnel available only on an on-call basis. Four (4) innovations will work cooperatively to enable a significant reduction in operations costs for the MAP spacecraft. First, the use of a common ground system for Spacecraft Integration and Test (I&T) as well as Operations. Second, the use of Finite State Modeling for intelligent autonomy. Third, the integration of a graphical planning engine to drive the autonomous systems without an intermediate manual step. And fourth, the ability for distributed operations via Web and pager access.

Breed, Juile↗

Autonomous Science Analyses of Digital Images for Mars Sample Return and Beyond

To adequately explore high priority landing sites, scientists require rovers with greater mobility. Therefore, future Mars missions will involve rovers capable of traversing tens of kilometers (vs. tens of meters traversed by Mars Pathfinder's Sojourner). However, the current process by which scientists interact with a rover does not scale to such distances. A single science objective is achieved through many iterations of a basic command cycle: (1) all data must be transmitted to Earth and analyzed; (2) from this data, new targets are selected and the necessary information from the appropriate instruments are requested; (3) new commands are then uplinked and executed by the spacecraft and (4) the resulting data are returned to Earth, starting the process again. Experience with rover tests on Earth shows that this time intensive process cannot be substantially shortened given the limited data downlink bandwidth and command cycle opportunities of real missions. Sending complete multicolor panoramas at several waypoints, for example, is out of the question for a single downlink opportunity. As a result, long traverses requiring many science command cycles would likely require many weeks, months or even years, perhaps exceeding rover design life or other constraints. Autonomous onboard science analyses can address these problems in two ways. First, it will allow the rover to transmit only "interesting" images, defined as those likely to have higher science content. Second, the rover will be able to anticipate future commands, for example acquiring and returning spectra of "interesting" rocks along with the images in which they were detected. Such approaches, coupled with appropriate navigational software, address both the data volume and command cycle bottlenecks that limit both rover mobility and science yield. We are developing algorithms to enable such intelligent decision making by autonomous spacecraft. Reflecting the ultimate level of ability we aim for, this program has been dubbed the "Grad Student on Mars Project". We envision, for example, an appropriately intelligent Athena-like rover at the Pathfinder landing site might be able to traverse over the ridge towards "Twin Peaks" to obtain better information on the stratigraphy of these "streamlined islands" or of the size, composition and morphology of boulders located on them. Along the traverse, the intelligent rover would collect and analyze images and obtain spectra of geologically interesting features or regions. The intelligent rover might also traverse further up Arcs Vallis, and find additional paleoflood stage indicators such as slackwater deposits. Recognizing additional regions where boulders are imbricated, noting changes in their size, distribution, morphology, composition and the associated changes in channel geometry would yield important information on the outflow channel's paleoflood history, Representative images and associated supporting data from these locations could be downlinked to Earth along with the data requested by scientists from the previous uplink opportunity. Our initial work has focused on recognizing geologically interesting portions of images. Here we summarize some of the algorithms to date.

Gulick, V. C.↗

Using Model-Based Reasoning for Autonomous Instrument Operation - Lessons Learned From IMAGE/LENA

Model-based reasoning has been applied as an autonomous control strategy on the Low Energy Neutral Atom (LENA) instrument currently flying on board the Imager for Magnetosphere-to-Aurora Global Exploration (IMAGE) spacecraft. Explicit models of instrument subsystem responses have been constructed and are used to dynamically adapt the instrument to the spacecraft's environment. These functions are cast as part of a Virtual Principal Investigator (VPI) that autonomously monitors and controls the instrument. In the VPI's current implementation, LENA's command uplink volume has been decreased significantly from its previous volume; typically, no uplinks are required for operations. This work demonstrates that a model-based approach can be used to enhance science instrument effectiveness. The components of LENA are common in space science instrumentation, and lessons learned by modeling this system may be applied to other instruments. Future work involves the extension of these methods to cover more aspects of LENA operation and the generalization to other space science instrumentation.

Johnson, Michael A.↗

RADX34: A Future-X Demonstration of Autonomous Robust Abort Technologies on the X-34

The Charles Stark Draper Laboratory, Inc. has been conducting the RADX-34 Future-X Pathfinder Flight Demonstration experiment under the direction of the NASA Marshall Space Flight Center. The Future-X experiment will use the X-34 to demonstrate autonomous abort technologies needed for the next generation of reusable launch vehicles. This project will involve integration of real-time abort mission planning algorithms with the existing guidance and control to provide abort coverage for the low-Mach flights of the X-34. This paper describes the design and capability of the abort planner three months prior to the conclusion of its development. The mission planner described herein is able to respond to loss of thrust, determine which runways can be reached within the vehicle constraints, and designate an appropriate landing site. This project, when complete, will mark the first step in the development of the Next Generation of Guidance and Control (NGGC) autonomous algorithms. NGGC algorithms will help ensure the second generation of reusable launch vehicles will meet their cost, safety and reliability requirements.

Aron, Edward C.↗

RIACS Workshop on the Verification and Validation of Autonomous and Adaptive Systems

The long-term future of space exploration at NASA is dependent on the full exploitation of autonomous and adaptive systems: careful monitoring of missions from earth, as is the norm now, will be infeasible due to the sheer number of proposed missions and the communication lag for deep-space missions. Mission managers are however worried about the reliability of these more intelligent systems. The main focus of the workshop was to address these worries and hence we invited NASA engineers working on autonomous and adaptive systems and researchers interested in the verification and validation (V&V) of software systems. The dual purpose of the meeting was to: (1) make NASA engineers aware of the V&V techniques they could be using; and (2) make the V&V community aware of the complexity of the systems NASA is developing.

Pecheur, Charles↗

Autonomic Responses to Microgravity

The purpose of this report is to describe how changes in autonomic nervous system responses may be used as an index of individual differences in adaptational capacity to space flight. During two separate Spacelab missions, six crewmembers wore an ambulatory monitoring system which enabled continuous recording of their physiological responses for up to twelve hours a day for 3 to 5 mission days. The responses recorded were electrocardiography, respiration wave form, skin conductance level, hand temperature, blood flow to the hands and triaxial accelerations of the head and upper body. Three of these subjects had been given training, before the mission, in voluntary control of these autonomic responses as a means of facilitating adaptation to space. Three of these subjects served as Controls, i.e., did not receive this training but took anti-motion sickness medication. Nearly 300 hours of flight data are summarized. These data were examined using time-series analyses, spectral analyses of heart rate variability, and analyses of variance. Information was obtained on responses to space motion sickness, inflight medications, circadian rhythm, workload and fatigue. Preliminary assessment was made on the effectiveness of self-regulation training as a means of facilitating adaptation, with recommendations for future flights.

Toscano, W. B.↗

Learning Sequences of Actions in Collectives of Autonomous Agents

In this paper we focus on the problem of designing a collective of autonomous agents that individually learn sequences of actions such that the resultant sequence of joint actions achieves a predetermined global objective. We are particularly interested in instances of this problem where centralized control is either impossible or impractical. For single agent systems in similar domains, machine learning methods (e.g., reinforcement learners) have been successfully used. However, applying such solutions directly to multi-agent systems often proves problematic, as agents may work at cross-purposes, or have difficulty in evaluating their contribution to achievement of the global objective, or both. Accordingly, the crucial design step in multiagent systems centers on determining the private objectives of each agent so that as the agents strive for those objectives, the system reaches a good global solution. In this work we consider a version of this problem involving multiple autonomous agents in a grid world. We use concepts from collective intelligence to design goals for the agents that are 'aligned' with the global goal, and are 'learnable' in that agents can readily see how their behavior affects their utility. We show that reinforcement learning agents using those goals outperform both 'natural' extensions of single agent algorithms and global reinforcement, learning solutions based on 'team games'.

Turner, Kagan↗

IDEA: Planning at the Core of Autonomous Reactive Agents

Several successful autonomous systems are separated into technologically diverse functional layers operating at different levels of abstraction. This diversity makes them difficult to implement and validate. In this paper, we present IDEA (Intelligent Distributed Execution Architecture), a unified planning and execution framework. In IDEA a layered system can be implemented as separate agents, one per layer, each representing its interactions with the world in a model. At all levels, the model representation primitives and their semantics is the same. Moreover, each agent relies on a single model, plan database, plan runner and on a variety of planners, both reactive and deliberative. The framework allows the specification of agents that operate, within a guaranteed reaction time and supports flexible specification of reactive vs. deliberative agent behavior. Within the IDEA framework we are working to fully duplicate the functionalities of the DS1 Remote Agent and extend it to domains of higher complexity than autonomous spacecraft control.

Muscettola, Nicola↗

Advances in Robotic, Human, and Autonomous Systems for Missions of Space Exploration

Space exploration missions are evolving toward more complex architectures involving more capable robotic systems, new levels of human and robotic interaction, and increasingly autonomous systems. How this evolving mix of advanced capabilities will be utilized in the design of new missions is a subject of much current interest. Cost and risk constraints also play a key role in the development of new missions, resulting in a complex interplay of a broad range of factors in the mission development and planning of new missions. This paper will discuss how human, robotic, and autonomous systems could be used in advanced space exploration missions. In particular, a recently completed survey of the state of the art and the potential future of robotic systems, as well as new experiments utilizing human and robotic approaches will be described. Finally, there will be a discussion of how best to utilize these various approaches for meeting space exploration goals.

Gross, Anthony R.↗

Demonstration of a Spoken Dialogue Interface for Planning Activities of a Semi-autonomous Robot

Planning and scheduling in the face of uncertainty and change pushes the capabilities of both planning and dialogue technologies by requiring complex negotiation to arrive at a workable plan. Planning for use of semi-autonomous robots involves negotiation among multiple participants with competing scientific and engineering goals to co-construct a complex plan. In NASA applications this plan construction is done under severe time pressure so having a dialogue interface to the plan construction tools can aid rapid completion of the process. But, this will put significant demands on spoken dialogue technology, particularly in the areas of dialogue management and generation. The dialogue interface will need to be able to handle the complex dialogue strategies that occur in negotiation dialogues, including hypotheticals and revisions, and the generation component will require an ability to summarize complex plans. This demonstration will describe a work in progress towards building a spoken dialogue interface to the EUROPA planner for the purposes of planning and scheduling the activities of a semi-autonomous robot. A prototype interface has been built for planning the schedule of the Personal Satellite Assistant (PSA), a mobile robot designed for micro-gravity environments that is intended for use on the Space Shuttle and International Space Station. The spoken dialogue interface gives the user the capability to ask for a description of the plan, ask specific questions about the plan, and update or modify the plan. We anticipate that a spoken dialogue interface to the planner will provide a natural augmentation or alternative to the visualization interface, in situations in which the user needs very targeted information about the plan, in situations where natural language can express complex ideas more concisely than GUI actions, or in situations in which a graphical user interface is not appropriate.

Dowding, John↗

Multiple Autonomous Discrete Event Controllers for Constellations

The Multiple Autonomous Discrete Event Controllers for Constellations (MADECC) project is an effort within the National Aeronautics and Space Administration Goddard Space Flight Center's (NASA/GSFC) Information Systems Division to develop autonomous positioning and attitude control for constellation satellites. It will be accomplished using traditional control theory and advanced coordination algorithms developed by the Johns Hopkins University Applied Physics Laboratory (JHU/APL). This capability will be demonstrated in the discrete event control test-bed located at JHU/APL. This project will be modeled for the Leonardo constellation mission, but is intended to be adaptable to any constellation mission. To develop a common software architecture. the controllers will only model very high-level responses. For instance, after determining that a maneuver must be made. the MADECC system will output B (Delta)V (velocity change) value. Lower level systems must then decide which thrusters to fire and for how long to achieve that (Delta)V.

Esposito, Timothy C.↗

Pilot Interactions in an Over-Constrained Conflict Scenario as Studied in a Piloted Simulation of Autonomous Aircraft Operations

Feasibility and safety of autonomous aircraft operations were studied in a multi-piloted simulation of overconstrained traffic conflicts to determine the need for, and utility of, priority flight rules to maintain safety in this extraordinary and potentially hazardous situation. An overconstrained traffic conflict is one in which the separation assurance objective is incompatible with other objectives. In addition, a proposed scheme for implementing priority flight rules by staggering the alerting time between the two aircraft in conflict was tested for effectiveness. The feasibility study was conducted through a simulation in the Air Traffic Operations Laboratory at the NASA Langley Research Center. This research activity is a continuation of the Distributed Air-Ground Traffic Management feasibility analysis reported in the 4th USA/Europe Air Traffic Management R&D Seminar in December 2001 (paper #48). The over-constrained conflict scenario studied here consisted of two piloted aircraft that were assigned an identical en-route waypoint arrival time and altitude crossing restriction. The simulation results indicated that the pilots safely resolved the conflict without the need for a priority flight rule system. Occurrences of unnecessary maneuvering near the common waypoint were traced to false conflict alerts, generated as the result of including waypoint constraint information in the broadcast data link message issued from each aircraft. This result suggests that, in the conservative interests of safety, broadcast intent information should be based on the commanded trajectory and not on the Flight Management System flight plan, to which the aircraft may not actually adhere. The use of priority flight rules had no effect on the percentage of the aircraft population meeting completely predictable which aircraft in a given pair would meet the constraints and which aircraft would make the first maneuver to yield right-of-way. Therefore, the proposed scheme for implementing priority flight rules through staggering the alerting time between the two aircraft was completely effective. The data and observations from this experiment, together with results from the previously reported study, support the feasibility of autonomous aircraft operations.

Wing, David J.↗

Airborne Conflict Management within Confined Airspace in a Piloted Simulation of DAG-TM Autonomous Aircraft Operations

A human-in-the-loop experiment was performed at the NASA Langley Research Center to study the feasibility of Distributed Air/Ground Traffic Management (DAG-TM) autonomous aircraft operations in highly constrained airspace. The airspace was constrained by a pair of special use airspace (SUA) regions on either side of the pilot s planned route. The available airspace was further varied by changing the separation standard for lateral separation between 3 nm and 5 nm. The pilot had to maneuver through the corridor between the SUA s, avoid other traffic and meet flow management constraints. Traffic flow management (TFM) constraints were imposed as a required time of arrival and crossing altitude at an en route fix. This is a follow-up study to work presented at the 4th USA/Europe Air Traffic Management R&D Seminar in December 2001. Nearly all of the pilots were able to meet their TFM constraints while maintaining adequate separation from other traffic. In only 3 out of 59 runs were the pilots unable to meet their required time of arrival. Two loss of separation cases are studied and it is found that the pilots need conflict prevention information presented in a clearer manner. No degradation of performance or safety was seen between the wide and narrow corridors. Although this was not a thorough study of the consequences of reducing the en route lateral separation, nothing was found that would refute the feasibility of reducing the separation requirement from 5 nm to 3 nm. The creation of additional, second-generation conflicts is also investigated. Two resolution methods were offered to the pilots: strategic and tactical. The strategic method is a closed-loop alteration to the Flight Management System (FMS) active route that considers other traffic as well as TFM constraints. The tactical resolutions are short-term resolutions that leave avoiding other traffic conflicts and meeting the TFM constraints to the pilot. Those that made use of the strategic tools avoided additional conflicts, whereas, those making tactical maneuvers often caused additional conflicts. Many of these second-generation conflicts could be avoided by improved conflict prevention tools that clearly present to the pilot which maneuver choices will result in a conflict-free path. These results, together with previously reported studies, continue to support the feasibility of autonomous aircraft operations.

Barmore, Bryan↗

F/A-18 Performance Benefits Measured During the Autonomous Formation Flight Project

The Autonomous Formation Flight (AFF) project at the NASA Dryden Flight Research Center (Edwards, California) investigated performance benefits resulting from formation flight, such as reduced aerodynamic drag and fuel consumption. To obtain data on performance benefits, a trailing F/A-18 airplane flew within the wing tip-shed vortex of a leading F/A-18 airplane. The pilot of the trail airplane used advanced station-keeping technology to aid in positioning the trail airplane at precise locations behind the lead airplane. The specially instrumented trail airplane was able to obtain accurate fuel flow measurements and to calculate engine thrust and vehicle drag. A maneuver technique developed for this test provided a direct comparison of performance values while flying in and out of the vortex. Based on performance within the vortex as a function of changes in vertical, lateral, and longitudinal positioning, these tests explored design-drivers for autonomous stationkeeping control systems. Observations showed significant performance improvements over a large range of trail positions tested. Calculations revealed maximum drag reductions of over 20 percent, and demonstrated maximum reductions in fuel flow of just over 18 percent.

Vachon, M. Jake↗

Simulation-Based Verification of Autonomous Controllers via Livingstone PathFinder

AI software is often used as a means for providing greater autonomy to automated systems, capable of coping with harsh and unpredictable environments. Due in part to the enormous space of possible situations that they aim to addrs, autonomous systems pose a serious challenge to traditional test-based verification approaches. Efficient verification approaches need to be perfected before these systems can reliably control critical applications. This publication describes Livingstone PathFinder (LPF), a verification tool for autonomous control software. LPF applies state space exploration algorithms to an instrumented testbed, consisting of the controller embedded in a simulated operating environment. Although LPF has focused on NASA s Livingstone model-based diagnosis system applications, the architecture is modular and adaptable to other systems. This article presents different facets of LPF and experimental results from applying the software to a Livingstone model of the main propulsion feed subsystem for a prototype space vehicle.

Lindsey, A. E.↗

Autonomous Sciencecraft Experiment (ASE) Operations on EO-1 in 2004

The Autonomous Sciencecraft Experiment (ASE) has been selected for flight demonstration by NASAs New Millennium Program (NMP) as part of the Space Technology 6 (ST6) mission. NASA has identified the development of an autonomously operating spacecraft as a necessity for an expanded program of missions exploring the Solar System. The versatile ASE spacecraft command and control software, image formation software, and science processing software will be uploaded to the Earth Observer 1 (EO-1) spacecraft in early 2004 to detect surface modification related to volcanism, ice formation and retreat, and flooding.

Davies, A. G.↗