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At least 577 records · Page 32

Neuro-vestibular and Sensory-motor Challenges Associated with NASA Mission Architectures for Moon and Mars

Data from six-month low Earth orbit space flight missions suggest that that substantial neuro-vestibular/sensory-motor adaptation will take place during six-month transit missions to and from Mars. Could intermittent or continuous artificial gravity be used to offset these effects? To what degree would the effects of adaptation to this rotational cure affect its potential benefits? Also, little information exists regarding the gravity thresholds for maintaining functional performance of complex sensory-motor tasks such as balance control and locomotion. Will sensory-motor coordination systems adapt to 30- 90 days of 1/6 g on the lunar surface or 18 months of 3/8 g on the Martian surface? Would some form of gravity replacement therapy be required on the surface? And, will transitions between 0 g and 1/6 g or 1/3 g present as great a challenge to the vestibular system as transitions between 0 g and 1 g? Concerted research and development efforts will be required to obtain the answers.

Paloski, William H.↗

Effects of Walking Speed and Visual-Target Distance on Toe Trajectory During Swing Phase

After spaceflight, astronauts experience disturbances in their ability to walk and maintain postural stability (Bloomberg, et al., 1997). One of the post-flight neurovestibular assessments requires that the astronaut walk on a treadmill at 1.8 m/sec (4.0 mph), while performing a visual acuity test, set at two different distances ( far and near ). For the first few days after landing, some crewmembers can not maintain the required pace, so a lower speed may be used. The slower velocity must be considered in the kinematic analysis, because Andriacchi, et al. (1977) showed that in clinical populations, changes in gait parameters may be attributable more to slower gait speed than pathology. Studying toe trajectory gives a global view of control of the leg, since it involves coordination of muscles and joints in both the swing and stance legs (Karst, et al., 1999). Winter (1992) and Murray, et al. (1984) reported that toe clearance during overground walking increased slightly as speed increased, but not significantly. Also, toe vertical peaks in both early and late swing phase did increase significantly with increasing speed. During conventional testing of overground locomotion, subjects are usually asked to fix their gaze on the end of the walkway a far target. But target (i.e., visual fixation) distance has been shown to affect head and trunk motion during treadmill walking (Bloomberg, et al., 1992; Peters, et al., in review). Since the head and trunk can not maintain stable gaze without proper coordination with the lower body (Mulavara & Bloomberg, 2003), it would stand to reason that lower body kinematics may be altered as well when target distance is modified. The purpose of this study was to determine changes in toe vertical trajectory during treadmill walking due to changes in walking speed and target distance.

Miller, Chris↗

Neuro-vestibular and Sensory-motor Challenges Associated with NASA Mission Architectures for Moon and Mars

Data from six-month low Earth orbit space flight missions suggest that that substantial neuro-vestibuladsensory-motor adaptation will take place during six-month transit missions to and from Mars. Could intermittent or continuous artificial gravity be used to offset these effects? To what degree would the effects of adaptation to this rotational cure affect its potential benefits? Also, little information exists regarding the gravity thresholds for maintaining functional performance of complex sensory-motor tasks such as balance control and locomotion. Will sensory-motor coordination systems adapt to 30-90 days of 1/6 g on the lunar surface or 18 months of 3/8 g on the Martian surface? Would some form of gravity replacement therapy be required on the surface? And, will transitions between 0 g and 1/6 g or 1/3 g present as great a challenge to the vestibular system as transitions between 0 g and 1 g? Concerted research and development efforts will be required to obtain the answers.

Paloski, William H.↗

Large Unmanned Aircraft System Operations in the National Airspace System - the NASA 2007 Western States Fire Missions

The National Aeronautics and Space Administration (NASA) Dryden Flight Research Center (DFRC) Ikhana (ee-kah-nah) project executed the 2007 Western States Fire Missions over several of the western United States using an MQ-9 unmanned aircraft system (UAS) in partnership with the NASA Ames Research Center, the United States Forest Service, and the National Interagency Fire Center. The missions were intended to supply infrared imagery of wildfires to firefighters on the ground within 10 minutes of data acquisition. For each of the eight missions, the NASA DFRC notified the Federal Aviation Administration (FAA) of specific flight plans within three or fewer days of the flight. The FAA Certificate of Waiver or Authorization (commonly referred to as a COA ) process was used to obtain access to the United States National Airspace System. Significant time and resources were necessary to develop the COA application, perform mission planning, and define and approve emergency landing sites. Unique aspects of flying unmanned aircraft created challenges to mission operations. Close coordination with FAA headquarters and air traffic control resulted in safe and successful missions that assisted firefighters by providing near-real-time imagery of selected wildfires.

Buoni, Gregory P.↗

Resolving Off-Nominal Situations in Schedule-Based Terminal Area Operations: Results from a Human-in-the-Loop Simulation

A recent human-in-the-loop simulation in the Airspace Operations Laboratory (AOL) at NASA's Ames Research Center investigated the robustness of Controller-Managed Spacing (CMS) operations. CMS refers to AOL-developed controller tools and procedures for enabling arrivals to conduct efficient Optimized Profile Descents with sustained high throughput. The simulation provided a rich data set for examining how a traffic management supervisor and terminal-area controller participants used the CMS tools and coordinated to respond to off-nominal events. This paper proposes quantitative measures for characterizing the participants responses. Case studies of go-around events, replicated during the simulation, provide insights into the strategies employed and the role the CMS tools played in supporting them.

Mercer, Joey↗

Cardiac-Activity Measures for Assessing Airport Ramp-Tower Controller's Workload

Heart rate (HR) and heart rate variability (HRV) potentially offer objective, continuous, and non-intrusive measures of human-operator's mental workload. Such measurement capability is attractive for workload assessment in complex laboratory simulations or safety-critical field testing. The present study compares mean HR and HRV data with self-reported subjective workload ratings collected during a high-fidelity human-in-the-loop simulation of airport ramp traffic control operations, which involve complex cognitive and coordination tasks. Mean HR was found to be weakly sensitive to the workload ratings, while HRV was not sensitive or even contradictory to the assumptions. Until more knowledge on stress response mechanisms of the autonomic nervous system is obtained, it is recommended that these cardiac-activity measures be used with other workload assessment tools, such as subjective measures.

Hayashi, Miwa↗

Cardiac-Activity Measures for Assessing Airport Ramp-Tower Controller's Workload

Heart rate (HR) and heart rate variability (HRV) potentially offer objective, continuous, and non-intrusive measures of human-operators mental workload. Such measurement capability is attractive for workload assessment in complex laboratory simulations or safety-critical field testing. The present study compares mean HR and HRV data with self-reported subjective workload ratings collected during a high-fidelity human-in-the-loop simulation of airport ramp traffic control operations, which involve complex cognitive and coordination tasks. Mean HR was found to be weakly sensitive to the workload ratings, while HRV was not sensitive or even contradictory to the assumptions. Until more knowledge on stress response mechanisms of the autonomic nervous system is obtained, it is recommended that these cardiac-activity measures be used with other workload assessment tools, such as subjective measures.

Hayashi, Miwa↗

TPSAS-NF1676L-14864-DND

Objective 1: Develop a research test-bed and database to provide data/proof of concept for Ground Control Station (GCS) NAS operations. Objective 2: Coordinate with standards organizations to develop human factors guidelines for GCS operation in the NAS.

Anna Trujillo↗

TPSAS-NF1676L-14989-DND

Objective 1: Develop a research test-bed and database to provide data/proof of concept for Ground Control Station (GCS) NAS operations. Objective 2: Coordinate with standards organizations to develop human factors guidelines for GCS operation in the NAS. Interest in UAS routine access: 1) Federal government – DHS, NOAA, Commerce, Interior, FBI, DOT 2) Military 3) Local governments – police, fire, port authority 4) Commercial – utilities, news agencies, private security, photographers, hobbyists

Anna Trujillo↗

Conjunction Assessment and Deconfliction Paradigm for Co-located Satellite Constellations with On-Spacecraft “Autonomous” Flight Dynamics Control

Constellations that employ highly-automated satellite flight dynamics can operate safely from a collision avoidance (CA) perspective using current CA screening technology and communication paradigms—except when in proximity to other highly-automated constellations: there is no existing arrangement and concept of operations to allow the low-latency CA screenings, exchange of information, and assignment/acceptance of mitigation responsibility that co-location of highly-automated constellations requires. However, the serendipitous co-location of the NASA Starling mission—an autonomously-controlled technology demonstration constellation—and the SpaceX Starlink constellation has presented an opportunity (indeed, a requirement) to develop and build out a solution for safe operations of two (or more) co-located, highly-automated satellite constellations. Such a solution has been designed and constructed, including the required ground node; and it will be exercised as a dedicated, in-flight safety experiment between the two constellations from January to September 2024. Lessons learned from this experiment are expected to feed the design of the US Department of Commerce’s Tracking Control System for Space (TraCSS) space traffic coordination solution.

conjunction assessment↗

Use of ERTS data for a multidisciplinary analysis of Michigan resources

The author has identified the following significant results. A computerized procedure has been developed to correlate coordinates from topographic maps and/or aerial photographs with ERTS data coordinates. Application to data from other multispectral scanners is anticipated. In the procedure, a map transformation from earth coordinates to ERTS point and line numbers is calculated using selected ground control points and the method of least squares. The map transformation is then applied to the earth coordinates of selected areas to obtain the corresponding ERTS point and line numbers. An optional provision allows moving the boundaries of the plots inwards by variable distances (typically half a resolution element) so the selected pixels will not overlap adjacent features.

Anderson, A. L.↗

Space construction base control system

Aspects of an attitude control system were studied and developed for a large space base that is structurally flexible and whose mass properties change rather dramatically during its orbital lifetime. Topics of discussion include the following: (1) space base orbital pointing and maneuvering; (2) angular momentum sizing of actuators; (3) momentum desaturation selection and sizing; (4) multilevel control technique applied to configuration one; (5) one-dimensional model simulation; (6) N-body discrete coordinate simulation; (7) structural analysis math model formulation; and (8) discussion of control problems and control methods.

Source record↗

Precision Departure Release Capability (PDRC) Technology Description

After takeoff, aircraft must merge into en route (Center) airspace traffic flows which may be subject to constraints that create localized demand-capacity imbalances. When demand exceeds capacity, Traffic Management Coordinators (TMCs) often use tactical departure scheduling to manage the flow of departures into the constrained Center traffic flow. Tactical departure scheduling usually involves use of a Call for Release (CFR) procedure wherein the Tower must call the Center TMC to coordinate a release time prior to allowing the flight to depart. In present-day operations release times are computed by the Center Traffic Management Advisor (TMA) decision support tool based upon manual estimates of aircraft ready time verbally communicated from the Tower to the Center. The TMA-computed release is verbally communicated from the Center back to the Tower where it is relayed to the Local controller as a release window that is typically three minutes wide. The Local controller will manage the departure to meet the coordinated release time window. Manual ready time prediction and verbal release time coordination are labor intensive and prone to inaccuracy. Also, use of release time windows adds uncertainty to the tactical departure process. Analysis of more than one million flights from January 2011 indicates that a significant number of tactically scheduled aircraft missed their en route slot due to ready time prediction uncertainty. Uncertainty in ready time estimates may result in missed opportunities to merge into constrained en route flows and lead to lost throughput. Next Generation Air Transportation System (NextGen) plans call for development of Tower automation systems capable of computing surface trajectory-based ready time estimates. NASA has developed the Precision Departure Release Capability (PDRC) concept that uses this technology to improve tactical departure scheduling by automatically communicating surface trajectory-based ready time predictions to the Center scheduling tool. The PDRC concept also incorporates earlier NASA and FAA research into automation-assisted CFR coordination. The PDRC concept helps reduce uncertainty by automatically communicating coordinated release times with seconds-level precision enabling TMCs to work with target times rather than windows. NASA has developed a PDRC prototype system that integrates the Center's TMA system with a research prototype Tower decision support tool. A two-phase field evaluation was conducted at NASA's North Texas Research Station (NTX) in Dallas-Fort Worth. The field evaluation validated the PDRC concept and demonstrated reduced release time uncertainty while being used for tactical departure scheduling of more than 230 operational flights over 29 weeks of operations. This paper presents the Technology Description. Companion papers include the Final Report and a Concept of Operations.

tactical departure scheduling↗

Precision Departure Release Capability (PDRC) Concept of Operations

After takeoff, aircraft must merge into en route (Center) airspace traffic flows which may be subject to constraints that create localized demandcapacity imbalances. When demand exceeds capacity Traffic Management Coordinators (TMCs) often use tactical departure scheduling to manage the flow of departures into the constrained Center traffic flow. Tactical departure scheduling usually involves use of a Call for Release (CFR) procedure wherein the Tower must call the Center TMC to coordinate a release time prior to allowing the flight to depart. In present-day operations release times are computed by the Center Traffic Management Advisor (TMA) decision support tool based upon manual estimates of aircraft ready time verbally communicated from the Tower to the Center. The TMA-computed release is verbally communicated from the Center back to the Tower where it is relayed to the Local controller as a release window that is typically three minutes wide. The Local controller will manage the departure to meet the coordinated release time window. Manual ready time prediction and verbal release time coordination are labor intensive and prone to inaccuracy. Also, use of release time windows adds uncertainty to the tactical departure process. Analysis of more than one million flights from January 2011 indicates that a significant number of tactically scheduled aircraft missed their en route slot due to ready time prediction uncertainty. Uncertainty in ready time estimates may result in missed opportunities to merge into constrained en route flows and lead to lost throughput. Next Generation Air Transportation System (NextGen) plans call for development of Tower automation systems capable of computing surface trajectory-based ready time estimates. NASA has developed the Precision Departure Release Capability (PDRC) concept that uses this technology to improve tactical departure scheduling by automatically communicating surface trajectory-based ready time predictions to the Center scheduling tool. The PDRC concept also incorporates earlier NASA and FAA research into automation-assisted CFR coordination. The PDRC concept helps reduce uncertainty by automatically communicating coordinated release times with seconds-level precision enabling TMCs to work with target times rather than windows. NASA has developed a PDRC prototype system that integrates the Center's TMA system with a research prototype Tower decision support tool. A two-phase field evaluation was conducted at NASA's North Texas Research Station (NTX) in DallasFort Worth. The field evaluation validated the PDRC concept and demonstrated reduced release time uncertainty while being used for tactical departure scheduling of more than 230 operational flights over 29 weeks of operations. This paper presents the Concept of Operations. Companion papers include the Final Report and a Technology Description. ? SUBJECT:

tactical departure scheduling↗

Precision Departure Release Capability (PDRC) Final Report

After takeoff, aircraft must merge into en route (Center) airspace traffic flows that may be subject to constraints that create localized demand/capacity imbalances. When demand exceeds capacity, Traffic Management Coordinators (TMCs) and Frontline Managers (FLMs) often use tactical departure scheduling to manage the flow of departures into the constrained Center traffic flow. Tactical departure scheduling usually involves a Call for Release (CFR) procedure wherein the Tower must call the Center to coordinate a release time prior to allowing the flight to depart. In present-day operations release times are computed by the Center Traffic Management Advisor (TMA) decision support tool, based upon manual estimates of aircraft ready time verbally communicated from the Tower to the Center. The TMA-computed release time is verbally communicated from the Center back to the Tower where it is relayed to the Local controller as a release window that is typically three minutes wide. The Local controller will manage the departure to meet the coordinated release time window. Manual ready time prediction and verbal release time coordination are labor intensive and prone to inaccuracy. Also, use of release time windows adds uncertainty to the tactical departure process. Analysis of more than one million flights from January 2011 indicates that a significant number of tactically scheduled aircraft missed their en route slot due to ready time prediction uncertainty. Uncertainty in ready time estimates may result in missed opportunities to merge into constrained en route flows and lead to lost throughput. Next Generation Air Transportation System plans call for development of Tower automation systems capable of computing surface trajectory-based ready time estimates. NASA has developed the Precision Departure Release Capability (PDRC) concept that improves tactical departure scheduling by automatically communicating surface trajectory-based ready time predictions and departure runway assignments to the Center scheduling tool. The PDRC concept also incorporates earlier NASA and FAA research into automation-assisted CFR coordination. The PDRC concept reduces uncertainty by automatically communicating coordinated release times with seconds-level precision enabling TMCs and FLMs to work with target times rather than windows. NASA has developed a PDRC prototype system that integrates the Center's TMA system with a research prototype Tower decision support tool. A two-phase field evaluation was conducted at NASA's North Texas Research Station in Dallas/Fort Worth. The field evaluation validated the PDRC concept and demonstrated reduced release time uncertainty while being used for tactical departure scheduling of more than 230 operational flights over 29 weeks of operations. This paper presents research results from the PDRC research activity. Companion papers present the Concept of Operations and a Technology Description.

tactical departure scheduling↗

Precision Departure Release Capability (PDRC): NASA to FAA Research Transition

After takeoff, aircraft must merge into en route (Center) airspace traffic flows which may be subject to constraints that create localized demand-capacity imbalances. When demand exceeds capacity, Traffic Management Coordinators (TMCs) and Frontline Managers (FLMs) often use tactical departure scheduling to manage the flow of departures into the constrained Center traffic flow. Tactical departure scheduling usually involves use of a Call for Release (CFR) procedure wherein the Tower must call the Center to coordinate a release time prior to allowing the flight to depart. In present-day operations release times are computed by the Center Traffic Management Advisor (TMA) decision support tool based upon manual estimates of aircraft ready time verbally communicated from the Tower to the Center. The TMA-computed release time is verbally communicated from the Center back to the Tower where it is relayed to the Local controller as a release window that is typically three minutes wide. The Local controller will manage the departure to meet the coordinated release time window. Manual ready time prediction and verbal release time coordination are labor intensive and prone to inaccuracy. Also, use of release time windows adds uncertainty to the tactical departure process. Analysis of more than one million flights from January 2011 indicates that a significant number of tactically scheduled aircraft missed their en route slot due to ready time prediction uncertainty. Uncertainty in ready time estimates may result in missed opportunities to merge into constrained en route flows and lead to lost throughput. Next Generation Air Transportation System plans call for development of Tower automation systems capable of computing surface trajectory-based ready time estimates. NASA has developed the Precision Departure Release Capability (PDRC) concept that improves tactical departure scheduling by automatically communicating surface trajectory-based ready time predictions and departure runway assignments to the Center scheduling tool. The PDRC concept also incorporates earlier NASA and FAA research into automation-assisted CFR coordination. The PDRC concept reduces uncertainty by automatically communicating coordinated release times with seconds-level precision enabling TMCs and FLMs to work with target times rather than windows. NASA has developed a PDRC prototype system that integrates the Center's TMA system with a research prototype Tower decision support tool. A two-phase field evaluation was conducted at NASA's North Texas Research Station in Dallas-Fort Worth. The field evaluation validated the PDRC concept and demonstrated reduced release time uncertainty while being used for tactical departure scheduling of more than 230 operational flights over 29 weeks of operations.

ATM↗

Robust Coordination for Large Sets of Simple Rovers

The ability to coordinate sets of rovers in an unknown environment is critical to the long-term success of many of NASA;s exploration missions. Such coordination policies must have the ability to adapt in unmodeled or partially modeled domains and must be robust against environmental noise and rover failures. In addition such coordination policies must accommodate a large number of rovers, without excessive and burdensome hand-tuning. In this paper we present a distributed coordination method that addresses these issues in the domain of controlling a set of simple rovers. The application of these methods allows reliable and efficient robotic exploration in dangerous, dynamic, and previously unexplored domains. Most control policies for space missions are directly programmed by engineers or created through the use of planning tools, and are appropriate for single rover missions or missions requiring the coordination of a small number of rovers. Such methods typically require significant amounts of domain knowledge, and are difficult to scale to large numbers of rovers. The method described in this article aims to address cases where a large number of rovers need to coordinate to solve a complex time dependent problem in a noisy environment. In this approach, each rover decomposes a global utility, representing the overall goal of the system, into rover-specific utilities that properly assign credit to the rover s actions. Each rover then has the responsibility to create a control policy that maximizes its own rover-specific utility. We show a method of creating rover-utilities that are "aligned" with the global utility, such that when the rovers maximize their own utility, they also maximize the global utility. In addition we show that our method creates rover-utilities that allow the rovers to create their control policies quickly and reliably. Our distributed learning method allows large sets rovers be used unmodeled domains, while providing robustness against rover failures and changing environments. In experimental simulations we show that our method scales well with large numbers of rovers in addition to being robust against noisy sensor inputs and noisy servo control. The results show that our method is able to scale to large numbers of rovers and achieves up to 400% performance improvement over standard machine learning methods.

Tumer, Kagan↗

Reduction of the elevator illusion from continued hypergravity exposure and visual error-corrective feedback

Ten subjects served as their own controls in two conditions of continuous, centrifugally produced hypergravity (+2 Gz) and a 1-G control condition. Before and after exposure, open-loop measures were obtained of (1) motor control, (2) visual localization, and (3) hand-eye coordination. During exposure in the visual feedback/hypergravity condition, subjects received terminal visual error-corrective feedback from their target pointing, and in the no-visual feedback/hypergravity condition they pointed open loop. As expected, the motor control measures for both experimental conditions revealed very short lived underreaching (the muscle-loading effect) at the outset of hypergravity and an equally transient negative aftereffect on returning to 1 G. The substantial (approximately 17 degrees) initial elevator illusion experienced in both hypergravity conditions declined over the course of the exposure period, whether or not visual feedback was provided. This effect was tentatively attributed to habituation of the otoliths. Visual feedback produced a smaller additional decrement and a postexposure negative after-effect, possible evidence for visual recalibration. Surprisingly, the target-pointing error made during hypergravity in the no-visual-feedback condition was substantially less than that predicted by subjects' elevator illusion. This finding calls into question the neural outflow model as a complete explanation of this illusion.

NASA Program Space Physiology and Countermeasures↗