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At least 379 records · Page 21

An intelligent training system for space shuttle flight controllers

An autonomous intelligent training system which integrates expert system technology with training/teaching methodologies is described. The system was designed to train Mission Control Center (MCC) Flight Dynamics Officers (FDOs) to deploy a certain type of satellite from the Space Shuttle. The Payload-assist module Deploys/Intelligent Computer-Aided Training (PD/ICAT) system consists of five components: a user interface, a domain expert, a training session manager, a trainee model, and a training scenario generator. The interface provides the trainee with information of the characteristics of the current training session and with on-line help. The domain expert (Dep1Ex for Deploy Expert) contains the rules and procedural knowledge needed by the FDO to carry out the satellite deploy. The Dep1Ex also contains mal-rules which permit the identification and diagnosis of common errors made by the trainee. The training session manager (TSM) examines the actions of the trainee and compares them with the actions of Dep1Ex in order to determine appropriate responses. A trainee model is developed for each individual using the system. The model includes a history of the trainee's interactions with the training system and provides evaluative data on the trainee's current skill level. A training scenario generator (TSG) designs appropriate training exercises for each trainee based on the trainee model and the training goals. All of the expert system components of PD/ICAT communicate via a common blackboard. The PD/ICAT is currently being tested. Ultimately, this project will serve as a vehicle for developing a general architecture for intelligent training systems together with a software environment for creating such systems.

Loftin, R. Bowen↗

On-demand Command and Control of ASTERIA with Cloud-based Ground Station Services

ASTERIA (Arcsecond Space Telescope Enabling Research in Astrophysics) was a 6-unit CubeSat technology demonstration mission that deployed from the International Space Station on November 20th, 2017. After successfully completing its 90-day primary mission that demonstrated arcsecond-level line-of-sight pointing and focal plane thermal stability for exoplanet detection, it entered an extended mission performing onboard software demonstrations to mature technology both in space and on the ground. One of the technologies was a completely cloud-based ground system leveraging Amazon Web Services (AWS) Ground Station service.Announced in December 2018 and launched in May 2019, AWS Ground Station is a fully managed ground station service that aims to reduce the overhead associated with developing and maintaining ground system infrastructure throughout the mission lifecycle. AWS Ground Station makes available the suite of features required for any ground system in support of low-Earth orbit (LEO) and medium-Earth Orbit (MEO) satellite operations on-demand and without setting up or maintaining long-term contracts. Charges are incurred on a per-minute basis for antenna usage during scheduled tracks. Support is available for S-band uplink and downlink, along with X-band narrowband and wideband downlink. Missions that use the service may reserve tracks with any licensed AWS Ground Station antennas located across each service region and have direct access to any AWS services in support of mission operations.The cloud-based architecture built around the AWS Ground Station service greatly enhanced ASTERIA mission operations by enabling end-to-end pass automation, on-demand contact scheduling and contingency planning, along with more efficient data downlink through station availability and station-to-station handovers. It incorporated open-source software, particularly NASA's AMMOS Instrument Toolkit (AIT) and Open Mission Control Technologies (OpenMCT), along with the AWS application programming interfaces (API) to the Ground Station, Elastic Compute Cloud (EC2) and Simple Storage Service (S3) services. After showcasing operability in August 2019, the team continued using and improving this novel ground system architecture until the end of mission in December 2019. This paper describes the cloud-based ground system, how it was designed, tested, and evaluated with an in-orbit spacecraft, the operational capabilities that it enabled, along with lessons learned and recommendations for future missions.

Fesq, Lorraine↗

On-demand Command and Control of ASTERIA with Cloud-based Ground Station Services

ASTERIA (Arcsecond Space Telescope Enabling Research in Astrophysics) was a 6-unit CubeSat technology demonstration mission that deployed from the International Space Station on November 20th, 2017. After successfully completing its 90-day primary mission that demonstrated arcsecond-level line-of-sight pointing and focal plane thermal stability for exoplanet detection, it entered an extended mission performing onboard software demonstrations to mature technology both in space and on the ground. One of the technologies was a completely cloud-based ground system leveraging Amazon Web Services (AWS) Ground Station service. Announced in December 2018 and launched in May 2019, AWS Ground Station is a fully managed ground station service that aims to reduce the overhead associated with developing and maintaining ground system infrastructure throughout the mission lifecycle. AWS Ground Station makes available the suite of features required for any ground system in support of low-Earth orbit (LEO) and medium-Earth Orbit (MEO) satellite operations on-demand and without setting up or maintaining long-term contracts. Charges are incurred on a per-minute basis for antenna usage during scheduled tracks. Support is available for S-band uplink and downlink, along with X-band narrowband and wideband downlink. Missions that use the service may reserve tracks with any licensed AWS Ground Station antennas located across each service region and have direct access to any AWS services in support of mission operations. The cloud-based architecture built around the AWS Ground Station service greatly enhanced ASTERIA mission operations by enabling end-to-end pass automation, on-demand contact scheduling and contingency planning, along with more efficient data downlink through station availability and station-tostation handovers. It incorporated open-source software, particularly NASA's AMMOS Instrument Toolkit (AIT) and Open Mission Control Technologies (OpenMCT), along with the AWS application programming interfaces (API) to the Ground Station, Elastic Compute Cloud (EC2) and Simple Storage Service (S3) services. After showcasing operability in August 2019, the team continued using and improving this novel ground system architecture until the end of mission in December 2019. This paper describes the cloud-based ground system, how it was designed, tested, and evaluated with an inorbit spacecraft, the operational capabilities that it enabled, along with lessons learned and recommendations for future missions.

Fesq, Lorraine↗

STS retrieval of satellites

The Space Transportation System (STS) provides the capability to retrieve satellites from space. This capability was demonstrated on flights STS 41-C and STS 51-A, and will be demonstrated again on a future flight with the retrieval of the Long Duration Exposure Facility (LDEF). This paper describes the activity required to ensure a successful retrieval from initial flight planning to actual flight operations. Attention is given to retrieval hardware necessary for success and manifest. Discussion of flight design to meet all constraints placed on the manifested cargo is included. Flightcrew and flight control team training are addressed. Flight rules, techniques, and procedures development are described and examples given. Mission Control Center (MCC) and Payload Operations Control Center (POCC) operations for integrated testing and actual flight support will be presented.

Bruce, T. N.↗

An Innovative Approach to Modeling VIPER Rover Software Life Cycle Cost

NASA’s “Volatiles Investigating Polar Exploration Rover” (VIPER) will be the first robotic mission to prospect for water ice near the south pole of the Moon in late 2023 on a 100-Earth-day mission. The information that the VIPER rover provides will help improve understanding of the composition, distribution, and accessibility of Lunar polar volatiles and will help determine how the Moon’s resources can support future human space exploration. VIPER, however, represents a radical departure from the way that NASA has traditionally developed planetary robotic missions. A key consequence of these differences is that estimating the cost of VIPER’s rover software is challenging and complex.For example, VIPER is being developed using management procedures typically applied to NASA research and technology projects, rather than space flight programs. In addition, key portions of the rover’s software are being designed as ground software to run on mission control computers (rather than on-board the rover as flight software as with prior planetary missions) taking advantage of continuous, interactive data communications between the Moon and Earth and higher performance computing available on the ground. Moreover, the rover’s software is being engineered using Agile software development practices and incorporates a significant amount of open-source, rather than following traditional (spiral, waterfall, etc.) development methods and in-house code. In this paper, we present an innovative process to estimate the life cycle cost of VIPER’s rover software. We first describe how we modeled the architecture and code counts for three software elements: Rover Flight Software (RFSW), Rover Ground Software (RGSW), and Rover Simulation Software (RSIM). We then discuss key challenges and unique aspects of our approach, such as the lack of Lunar rover analogies, the need to integrate and test large open source software, and the strategies developed to account for use of non-space flight management practices and the impact of the COVID-19 pandemic. We conclude with a summary of our results, including cumulative distribution, nearest neighbors and cluster analysis, as well as heuristics used to confirm the reasonableness of the cost estimate.

Utz, Hans↗

Next Generation Flight Controller Trainer System

The Next Generation Flight Controller Trainer (NGFCT) is a relatively inexpensive system of hardware and software that provides high-fidelity training for spaceshuttle flight controllers. NGFCT provides simulations into which are integrated the behaviors of emulated space-shuttle vehicle onboard general-purpose computers (GPCs), mission-control center (MCC) displays, and space-shuttle systems as represented by high-fidelity shuttle mission simulator (SMS) mathematical models. The emulated GPC computers enable the execution of onboard binary flight-specific software. The SMS models include representations of system malfunctions that can be easily invoked. The NGFCT software has a flexible design that enables independent updating of its GPC, SMS, and MCC components.

Arnold, Scott↗

NASA's Lunar Polar Ice Prospector, RESOLVE: Mission Rehearsal in Apollo Valley

After the completion of the Apollo Program, space agencies didn't visit the moon for many years. But then in the 90's, the Clementine and Lunar Prospector missions returned and showed evidence of water ice at the poles. Then in 2009 the Lunar Crater Observation and Sensing Satellite indisputably showed that the Cabeus crater contained water ice and other useful volatiles. Furthermore, instruments aboard the Lunar Reconnaissance Orbiter (LRO) show evidence that the water ice may also be present in areas that receive several days of continuous sunlight each month. However, before we can factor this resource into our mission designs, we must understand the distribution and quantity of ice or other volatiles at the poles and whether it can be reasonably harvested for use as propellant or mission consumables. NASA, in partnership with the Canadian Space Agency (CSA), has been developing a payload to answer these questions. The payload is named RESOLVE. RESOLVE is on a development path that will deliver a tested flight design by the end of 2014. The team has developed a Design Reference Mission using LRO data that has RESOLVE landing near Cabeus Crater in May of2016. One of the toughest obstacles for RESOLVE's solar powered mission is its tight timeline. RESOLVE must be able to complete its objectives in the 5-7 days of available sunlight. The RESOLVE team must be able to work around obstacles to the mission timeline in real time. They can't afford to take a day off to replan as other planetary missions have done. To insure that this mission can be executed as planned, a prototype version of RESOLVE was developed this year and tested at a lunar analog site on Hawaii, known as Apollo Valley, which was once used to train the Apollo astronauts. The RESOLVE team planned the mission with the same type of orbital imagery that would be available from LRO. The simulation team prepositioned a Lander in Apollo Valley with RESOLVE on top mounted on its CSA rover. Then the mission simulation began as the operations team's consoles came alive with data and images. They executed the mission just like the real mission with lunar communications delays and limited bandwidth and a realistic remote mission control room. This paper will describe the RESOLVE payload in detail and describe the results of the mission simulation in Hawaii.

Larson, William E.↗

STS-78 Flight Day 2

On this second day of the STS-78 flight, mission controllers wake the flight crew, Cmdr. Terence T. Henricks, Pilot Kevin R. Kregel, Payload Cmdr. Susan J. Helms, Mission Specialists Richard M. Linnehan, Charles E. Brady, Jr., and Payload Specialists Jean-Jacques Favier, Ph.D. and Robert B. Thirsk, M.D., with 'Free Falling,' a song by Tom Petty. Crew members are then shown working with various neurological and cardiovascular experiments inside the Spacelab.

Source record↗

HSI in NASA: From Research to Implementation

As NASA plans to send human explorers beyond low Earth orbit, onward to Mars and other destinations in the solar system, there will be new challenges to address in terms of HSI. These exploration missions will be quite different from the current and past missions such as Apollo, Shuttle, and International Space Station. The exploration crew will be more autonomous from ground mission control with delayed, and at times, no communication. They will have limited to no resupply for much longer mission durations. Systems to deliver and support extended human habitation at these destinations are extremely complex and unique, presenting new opportunities to employ HSI practices. In order to have an effective and affordable HSI implementation, both research and programmatic efforts are required. Currently, the HSI-related research at NASA is primarily in the area of space human factors and habitability. The purpose is to provide human health and performance countermeasures, knowledge, technologies, and tools to enable safe, reliable, and productive human space exploration beyond low Earth orbit, and update standards, requirements, and processes to verify and validate these requirements. In addition, HSI teams are actively engaged in technology development and demonstration efforts to influence the mission architecture and next-generation vehicle design. Finally, appropriate HSI references have been added to NASA' s systems engineering documentation, and an HSI Practitioner's Guide has been published to help design engineers consider HSI early and continuously in the acquisition process. These current and planned HSI-related activities at NASA will be discussed in this panel.

Whitmore, Mihriban↗

Validation of Self-Scheduling Countermeasures in NASA's HERA Campaign 6

Enhancing crew capabilities for planning and scheduling activities is critical for periods of increased crew autonomy in future long-duration missions where communication delays preclude real-time ground support from Earth. Our study focuses on how to empower astronauts to manage their timelines independently from the experts in the mission control center (MCC). Our objective was to evaluate the impact of scheduling countermeasures on crew scheduling performance, workload, and usability in an analog mission environment. The study involved 16 crew members across four missions in the Limited Autonomy phase of Human Exploration Research Analog (HERA) Campaign 6. Crew members used Playbook to schedule one operational day for the entire crew. Half the participants accessed scheduling aids, and we compared their performance to a control group with no aids. Performance, workload, and usability were assessed using time on task, violation counts, NASA Task Load Index (NASA-TLX), and System Usability Scale (SUS). Participants using scheduling aids completed sessions 20% faster and committed 33% fewer violations. While these differences were not statistically significant due to the study’s operational limitations, trends indicate that scheduling aids may reduce errors and improve efficiency. These results can inform the design of scheduling tools to enhance astronauts’ autonomy in long-duration space missions, contributing to improved crew performance and reduced reliance on ground support.

space robotics↗

Validation of Self-Scheduling Countermeasures in NASA's HERA Campaign 6

Enhancing crew capabilities for planning and scheduling activities is critical for periods of increased crew autonomy in future long-duration missions where communication delays preclude real-time ground support from Earth. Our study focuses on how to empower astronauts to manage their timelines independently from the experts in the mission control center (MCC). Our objective was to evaluate the impact of scheduling countermeasures on crew scheduling performance, workload, and usability in an analog mission environment. The study involved 16 crew members across four missions in the Limited Autonomy phase of Human Exploration Research Analog (HERA) Campaign 6. Crew members used Playbook to schedule one operational day for the entire crew. Half the participants accessed scheduling aids, and we compared their performance to a control group with no aids. Performance, workload, and usability were assessed using time on task, violation counts, NASA Task Load Index (NASA-TLX), and System Usability Scale (SUS). Participants using scheduling aids completed sessions 20% faster and committed 33% fewer violations. While these differences were not statistically significant due to the study’s operational limitations, trends indicate that scheduling aids may reduce errors and improve efficiency. These results can inform the design of scheduling tools to enhance astronauts’ autonomy in long-duration space missions, contributing to improved crew performance and reduced reliance on ground support.

space robotics↗

NASA/ESA CV-990 Spacelab Simulation (ASSESS 2)

Cost effective techniques for addressing management and operational activities on Spacelab were identified and analyzed during a ten day NASA-ESA cooperative mission with payload and flight responsibilities handled by the organization assigned for early Spacelabs. Topics discussed include: (1) management concepts and interface relationships; (2) experiment selection; (3) hardware development; (4) payload integration and checkout; (5) selection and training of mission specialists and payload specialists; (6) mission control center/payload operations control center interactions with ground and flight problems; (7) real time interaction during flight between principal investigators and the mission specialist/payload specialist flight crew; and (8) retrieval of scientific data and its analysis.

Source record↗

SPOT Program

A Spacecraft Position Optimal Tracking (SPOT) program was developed to process Global Positioning System (GPS) data, sent via telemetry from a spacecraft, to generate accurate navigation estimates of the vehicle position and velocity (state vector) using a Kalman filter. This program uses the GPS onboard receiver measurements to sequentially calculate the vehicle state vectors and provide this information to ground flight controllers. It is the first real-time ground-based shuttle navigation application using onboard sensors. The program is compact, portable, self-contained, and can run on a variety of UNIX or Linux computers. The program has a modular objec-toriented design that supports application-specific plugins such as data corruption remediation pre-processing and remote graphics display. The Kalman filter is extensible to additional sensor types or force models. The Kalman filter design is also strong against data dropouts because it uses physical models from state and covariance propagation in the absence of data. The design of this program separates the functionalities of SPOT into six different executable processes. This allows for the individual processes to be connected in an a la carte manner, making the feature set and executable complexity of SPOT adaptable to the needs of the user. Also, these processes need not be executed on the same workstation. This allows for communications between SPOT processes executing on the same Local Area Network (LAN). Thus, SPOT can be executed in a distributed sense with the capability for a team of flight controllers to efficiently share the same trajectory information currently being computed by the program. SPOT is used in the Mission Control Center (MCC) for Space Shuttle Program (SSP) and International Space Station Program (ISSP) operations, and can also be used as a post -flight analysis tool. It is primarily used for situational awareness, and for contingency situations.

Smith, Jason T.↗

NASA HRP Plans for Collaboration at the IBMP Ground-Based Experimental Facility (NEK)

NASA and IBMP are planning research collaborations using the IBMP Ground-based Experimental Facility (NEK). The NEK offers unique capabilities to study the effects of isolation on behavioral health and performance as it relates to spaceflight. The NEK is comprised of multiple interconnected modules that range in size from 50-250m(sup3). Modules can be included or excluded in a given mission allowing for flexibility of platform design. The NEK complex includes a Mission Control Center for communications and monitoring of crew members. In an effort to begin these collaborations, a 2-week mission is planned for 2017. In this mission, scientific studies will be conducted to assess facility capabilities in preparation for longer duration missions. A second follow-on 2-week mission may be planned for early in 2018. In future years, long duration missions of 4, 8 and 12 months are being considered. Missions will include scenarios that simulate for example, transit to and from asteroids, the moon, or other interplanetary travel. Mission operations will be structured to include stressors such as, high workloads, communication delays, and sleep deprivation. Studies completed at the NEK will support International Space Station expeditions, and future exploration missions. Topics studied will include communication, crew autonomy, cultural diversity, human factors, and medical capabilities.

Cromwell, Ronita L.↗

Interactive Exploration Robots: Human-Robotic Collaboration and Interactions

For decades, NASA has employed different operational approaches for human and robotic missions. Human spaceflight missions to the Moon and in low Earth orbit have relied upon near-continuous communication with minimal time delays. During these missions, astronauts and mission control communicate interactively to perform tasks and resolve problems in real-time. In contrast, deep-space robotic missions are designed for operations in the presence of significant communication delay - from tens of minutes to hours. Consequently, robotic missions typically employ meticulously scripted and validated command sequences that are intermittently uplinked to the robot for independent execution over long periods. Over the next few years, however, we will see increasing use of robots that blend these two operational approaches. These interactive exploration robots will be remotely operated by humans on Earth or from a spacecraft. These robots will be used to support astronauts on the International Space Station (ISS), to conduct new missions to the Moon, and potentially to enable remote exploration of planetary surfaces in real-time. In this talk, I will discuss the technical challenges associated with building and operating robots in this manner, along with lessons learned from research conducted with the ISS and in the field.

Fong, Terry↗

Teams in Space: Knowledge Gained, but More to Explore

NASA’s Human Research Program oversees the Team Risk (i.e., Risk of Performance and Behavioral Health Decrements due to Inadequate Cooperation, Coordination, Communication and Psychosocial Adaptation within a Team). Research in this area informs all aspects of an astronaut’s career, from hiring to training to mission support, and works to address new challenges related to lunar and Mars missions. NASA’s astronaut selection process creates an astronaut corps of highly qualified, team-oriented individuals, which allows mission planners much flexibility in composing small crews for specific missions. These crews are further developed and supported through extensive training, including team skills training, and countermeasures available to the crew throughout the mission. However, in the high consequence environment of long-duration missions, team composition is complex and is not a one-time concern to be addressed pre-mission. Team factors such as team cohesion, dyadic relationships, and shared team cognition are likely to change dynamically in response to each interaction and event experienced by the individuals and the team as a whole. Thus, monitoring and optimizing team composition at a more micro level (e.g., per task) is one way to support team functioning and performance. Spaceflight teams research also includes the multi-team system of Mission Control and coordination between space-to-ground, adding another avenue in which risk might be introduced, particularly under exploration missions that experience significant communication delays. Spaceflight teams research has recently experienced a concentrated flurry of analog research over the past decade, shedding light on the many unique challenges and potential solutions to mitigate the team risk in long-duration exploration missions. However, questions still remain about how to, for example, create unobtrusive operational measures and how to advance interdisciplinary teams research and countermeasure development. We present an overview of the challenges facing teams in space, our current knowledge, and the next steps for research and spaceflight operations.

Lauren Blackwell Landon↗

Smart Habitat: Identifying Technological Countermeasures to Address Health and Performance Risks during Long-Duration Exploration Missions

During proposed long-duration Exploration Missions, crews must become increasingly autonomous, as they will be unable to rely on consistent input and guidance from ground-based mission control operations. While it is known that smart technologies will play a crucial role in future long-duration Exploration Missions, it is not known which manner of devices and systems may best mitigate the expected risks to crew. The purpose of this project was to identify both current and emerging technologies which may act as health and performance countermeasures on long-duration Exploration Missions.

Ryan A. Lange↗

Representing operations procedures using temporal dependency networks

DSN Link Monitor & Control (LMC) operations consist primarily of executing procedures to configure, calibrate, test, and operate a communications link between an interplanetary spacecraft and its mission control center. Currently the LMC operators are responsible for integrating procedures into an end-to-end series of steps. The research presented in this paper is investigating new ways of specifying operations procedures that incorporate the insight of operations, engineering, and science personnel to improve mission operations. The paper describes the rationale for using Temporal Dependency Networks (TDN's) to represent the procedures, a description of how the data is acquired, and the knowledge engineering effort required to represent operations procedures. Results of operational tests of this concept, as implemented in the LMC Operator Assistant Prototype (LMCOA), are also presented.

Fayyad, Kristina E.↗