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At least 469 records · Page 26

Towards Resilient Autonomous Navigation of Drones

Robots and particularly drones are especially useful in exploring extreme environments that pose hazards to humans. To ensure safe operations in these situations, usually perceptually degraded and without good GNSS, it is critical to have a reliable and robust state estimation solution. The main body of literature in robot state estimation focuses on developing complex algorithms favoring accuracy. Typically, these approaches rely on a strong underlying assumption: the main estimation engine will not fail during operation. In contrast, we propose an architecture that pursues robustness in state estimation by considering redundancy and heterogeneity in both sensing and estimation algorithms. The architecture is designed to expect and detect failures and adapt the behavior of the system to ensure safety. To this end, we present HeRO (Heterogeneous Redundant Odometry): a stack of estimation algorithms running in parallel supervised by a resiliency logic. This logic carries out three main functions: a) perform confidence tests both in data quality and algorithm health; b) re-initialize those algorithms that might be malfunctioning; c) generate a smooth state estimate by multiplexing the inputs based on their quality. The state and quality estimates are used by the guidance and control modules to adapt the mobility behaviors of the system. The validation and utility of the approach are shown with real experiments on a ying robot for the use case of autonomous exploration of subterranean environments, with particular results from the STIX event of the DARPA Subterranean Challenge.

Agha-mohammadi, Ali-akbar↗

NASA’s MODIS/VIIRS Global Water Reservoir Product Suite from Moderate Resolution Remote Sensing Data

Global reservoir information can not only benefit local water management but can also improve our understanding of the hydrological cycle. This information includes water area, elevation, and storage; evaporation rate and volume values; and other characteristics. However, operational wall-to-wall reservoir storage and evaporation monitoring information is lacking on a global scale. Here we introduce NASA’s new MODIS/VIIRS Global Water Reservoir product suite based on moderate resolution remote sensing data—the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Visible Infrared Imaging Radiometer Suite (VIIRS). This product consists of 8-day (MxD28C2 and VNP28C2) and monthly (MxD28C3 and VNP28C3) measurements for 164 large reservoirs (MxD stands for the product from both Terra (MOD) or Aqua (MYD) satellites). The 8-day product provides area, elevation, and storage values, which were generated by first extracting water areas from surface reflectance data and then applying the area estimations to the pre-established Area–Elevation (A–E) relationships. These values were then further aggregated to monthly, with the evaporation rate and volume information added. The evaporation rate and volume values were calculated after the Lake Temperature and Evaporation Model (LTEM) using MODIS/VIIRS land surface temperature product and meteorological data from the Global Land Data Assimilation System (GLDAS). Validation results show that the 250 m area classifications from MODIS agree well with the high-resolution classifications from Landsat (R^(2) = 0.99). Validation of elevation and storage products for twelve Indian reservoirs show good agreement in terms of R^(2) values (0.71–0.96 for elevation, and 0.79–0.96 for storage) and normalized root-mean-square error (NRMSE) values (5.08–19.34% for elevation, and 6.39–18.77% for storage). The evaporation rate results for two reservoirs (Lake Nasser and Lake Mead) agree well with in situ measurements (R^(2) values of 0.61 and 0.66, and NRMSE values of 16.25% and 21.76%). Furthermore, preliminary results from the VIIRS reservoir product have shown good consistency with the MODIS based product, confirming the continuity of this 20-year product suite. This new global water reservoir product suite can provide valuable information with regard to water-sources-related studies, applications, management, and hydrological modeling and change analysis such as drought monitoring.

Yao Li↗

Relevant Environment Additive Construction Technology (REACT)

Project Overview This project is focused on developing technologies that enable construction of a Lunar Safe Haven type structure on the moon. A full scale architectural and structural design will be completed based on lunar conditions and Artemis mission needs. A scaled structure will be 3D printed in simulated lunar environments. Technical Approach Polymer bound regolith composite materials will be developed and characterized for lunar additive construction applications. A full scale architectural and structural design will be completed based on the latest scientific data on lunar environments including radiation, meteoroids, thermal conditions, reduced gravity, and moonquakes. The project will culminate with a demonstration of additive construction in simulated lunar vacuum, thermal, regolith, and UV conditions. Results/Summary Preliminary material specifications have been developed and an initial batch has been produced. A first iteration of the architectural and structural designs have been completed. Hardware for 3D printing in simulated lunar conditions is under development. Contributing Partners AI Space Factory – Winner of the NASA 3D Printed Habitat Centennial Challenge Infusion and Transition Plan On-surface construction of infrastructure is a critical capability of the sustainable phase of the Artemis Program and eventual sustainable human presence on Mars. It provides the ability to create protective shelters on-demand using local resources. The 3D-printing technology will achieve TRL 6 in 1g/vacuum tests with thermal/UV exposure in this project. CLPS missions will be pursued for infusion to demonstrate vertical construction with lunar regolith and conditions. Modeling and simulation will be used to define the pilot-scale shelter construction mission for long-term exposure on the lunar surface to validate the system for Artemis operational deployment.

Lunar Construction↗

The Big Plunge at Venus: The DAVINCI Descent Phase

DAVINCI (Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging) was selected as one of two new Discovery missions in summer of 2021 with the primary goals to study how the Venus atmosphere formed and changed over time. DAVINCI does this by making in situ measurements of the atmosphere, taking images below the cloud layer during the descent phase, and imaging the surface and clouds during two flyby science opportunities. The Descent Sphere is neither designed nor required to land on the surface so all critical science data must be taken and transmitted to a relay spacecraft prior to impact. This architecture drives the mission to a carefully-crafted concept of operations; deployments, instrument operations, and communications are choreographed to ensure the right data is gathered at the right altitude given the uncertainties in the trajectory and timeline. A complex flow of analyses and tests throughout development will validate the system’s ability to execute the mission goals. In the end DAVINCI will be ready for its one hour of descent time to meet its driving science goals.

DAVINCI↗

The Big Plunge at Venus: The DAVINCI Descent Phase

DAVINCI (Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging) was selected as one of two new Discovery missions in summer of 2021 with the primary goals are to study how the Venus atmosphere formed and changed over time. DAVINCI does this by making in situ measurements of the atmosphere and taking images below the cloud layer during the descent phase. The probe is neither designed nor required to land on the surface so all critical science data must be taken and transmitted to a relay spacecraft prior to impact. This architecture drives the mission to a carefully-crafted concept of operations; deployments, instrument operations, and communications are choreographed to ensure the right data is gathered at the right altitude given the uncertainties in the trajectory and timeline. A complex flow of analyses and tests throughout development will validate the system’s ability to execute the mission goals. In the end, DAVINCI will be ready for the one opportunity at one hour of descent time to meet its driving science goals.

DAVINCI↗

Guidance, Navigation, and Control for Laser-Based Non-Cooperative Target Detumbling

Orbital debris is a well known and growing problem presenting risks to the future of spaceflight. Many pieces of debris are defunct satellites or rocket upper stages. These large objects could generate an exponentially growing cloud of debris should they be involved in a collision, i.e., Kessler Syndrome. Future orbital debris remediation efforts often propose perturbing the orbit of these large targets to mitigate risk. These plans often involve non-cooperative rendezvous. In the absence of active control, the targets are expected to be tumbling which makes rendezvous a dangerous prospect. In this work we describe a guidance, navigation, and control system for a contactless non-cooperative target detumbling methodology which will significantly increase the safety of non-cooperative rendezvous. An onboard laser generates thrust on the target by ablating its surface material. This thrust is used to control target attitude. Our guidance, navigation, and control system is able to estimate relative pose, target the laser, and maintain formation flight during the detumbling process. The system is validated with Monte Carlo simulation in a variety of scenarios.

Guidance↗

Illustrating the Spatiotemporal Complexity of No2 Columns Using A Multi-Perspective Observing System: Moving Toward Geostationary Product Validation and Applications

As a precursor to secondary pollutants like ozone and PM2.5, nitrogen dioxide (NO2) is crucial to understand when addressing air quality issues. However, due to NO2’s short lifetime during the daytime and complexity of emission sources in urbanized regions, interpreting datasets from ground or satellite perspectives alone are challenged by variance in spatial and temporal resolutions. High resolution airborne mapping (< 1 km) of NO2 column densities across morning, midday, and afternoon add a unique perspective toward interpreting satellite data with respect to ground-measurements. This presentation focuses on the interpretation of spatiotemporal complexity of NO2 columns from the Synergistic TEMPO Air Quality Science Study (STAQS). The mission’s goal is to integrate geostationary observations from Tropospheric Emissions: Monitoring of Pollution (TEMPO) with traditional and enhanced air quality monitoring to improve the understanding of air quality science for increased societal benefit. We will demonstrate the interweaved perspective of NO2 columns from ground-based Pandora spectrometers and satellite-based observations (e.g., TROPOMI) as compared to high spatial resolution airborne observations from the GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator (GCAS). This includes the evaluation of each dataset through comparison to each other to identify potential biases in data products and the impact of heterogeneity on these comparisons. Airborne data will also be used as a proxy for geostationary observations with morning, midday, and afternoon raster maps collected over four cities (Los Angeles, Chicago, Toronto, and New York City). Finally, recent research outcomes will be presented to demonstrate how airborne and geostationary observations can be used to evaluate emission inventories and air quality models.

Laura Judd↗

Characterizing the California Current System through Sea Surface Temperature and Salinity

Characterizing temperature and salinity (T-S) conditions is a standard framework in oceanography to identify and describe deep water masses and their dynamics. At the surface, this practice is hindered by multiple air–sea–land processes impacting T-S properties at shorter time scales than can easily be monitored. Now, however, the unsurpassed spatial and temporal coverage and resolution achieved with satellite sea surface temperature (SST) and salinity (SSS) allow us to use these variables to investigate the variability of surface processes at climate-relevant scales. In this work, we use SSS and SST data, aggregated into domains using a cluster algorithm over a T-S diagram, to describe the surface characteristics of the California Current System (CCS), validating them with in situ data from uncrewed Saildrone vessels. Despite biases and uncertainties in SSS and SST values in highly dynamic coastal areas, this T-S framework has proven useful in describing CCS regional surface properties and their variability in the past and in real time, at novel scales. This analysis also shows the capacity of remote sensing data for investigating variability in land–air–sea interactions not previously possible due to limited in situ data.

Marisol García-Reyes↗

A Tool for Requirements-Based Programming

Absent a general method for mathematically sound, automated transformation of customer requirements into a formal model of the desired system, developers must resort to either manual application of formal methods or to system testing (either manual or automated). While formal methods have afforded numerous successes, they present serious issues, e.g., costs to gear up to apply them (time, expensive staff), and scalability and reproducibility when standards in the field are not settled. The testing path cannot be walked to the ultimate goal, because exhaustive testing is infeasible for all but trivial systems. So system verification remains problematic. System or requirements validation is similarly problematic. The alternatives available today depend on either having a formal model or pursuing enough testing to enable the customer to be certain that system behavior meets requirements. The testing alternative for non-trivial systems always have some system behaviors unconfirmed and therefore is not the answer. To ensure that a formal model is equivalent to the customer s requirements necessitates that the customer somehow fully understands the formal model, which is not realistic. The predominant view that provably correct system development depends on having a formal model of the system leads to a desire for a mathematically sound method to automate the transformation of customer requirements into a formal model. Such a method, an augmentation of requirements-based programming, will be briefly described in this paper, and a prototype tool to support it will be described. The method and tool enable both requirements validation and system verification for the class of systems whose behavior can be described as scenarios. An application of the tool to a prototype automated ground control system for NASA mission is presented.

Rash, James L.↗

Impact of Cross-Axis Structural Dynamics on Validation of Linear Models for Space Launch System

A feasibility study was performed to examine the advisability of incorporating a set of Programmed Test Inputs (PTIs) during the Space Launch System (SLS) vehicle flight. The intent of these inputs is to provide validation to the preflight models for control system stability margins, aerodynamics, and structural dynamics. During October 2009, Ares I-X program was successful in carrying out a series of PTI maneuvers which provided a significant amount of valuable data for post-flight analysis. The resulting data comparisons showed excellent agreement with the preflight linear models across the frequency spectrum of interest. However unlike Ares I-X, the structural dynamics associated with the SLS boost phase configuration are far more complex and highly coupled in all three axes. This presents a challenge when implementing this similar system identification technique to SLS. Preliminary simulation results show noticeable mismatches between PTI validation and analytical linear models in the frequency range of the structural dynamics. An alternate approach was examined which demonstrates the potential for better overall characterization of the system frequency response as well as robustness of the control design.

Pei, Jing↗

System diagnostic builder

The System Diagnostic Builder (SDB) is an automated software verification and validation tool using state-of-the-art Artificial Intelligence (AI) technologies. The SDB is used extensively by project BURKE at NASA-JSC as one component of a software re-engineering toolkit. The SDB is applicable to any government or commercial organization which performs verification and validation tasks. The SDB has an X-window interface, which allows the user to 'train' a set of rules for use in a rule-based evaluator. The interface has a window that allows the user to plot up to five data parameters (attributes) at a time. Using these plots and a mouse, the user can identify and classify a particular behavior of the subject software. Once the user has identified the general behavior patterns of the software, he can train a set of rules to represent his knowledge of that behavior. The training process builds rules and fuzzy sets to use in the evaluator. The fuzzy sets classify those data points not clearly identified as a particular classification. Once an initial set of rules is trained, each additional data set given to the SDB will be used by a machine learning mechanism to refine the rules and fuzzy sets. This is a passive process and, therefore, it does not require any additional operator time. The evaluation component of the SDB can be used to validate a single software system using some number of different data sets, such as a simulator. Moreover, it can be used to validate software systems which have been re-engineered from one language and design methodology to a totally new implementation.

Nieten, Joseph L.↗

Validation of the NASA Electrical Power System – Sizing and Analysis Tool (EPS-SAT)

The electrification of aircraft propulsion systems has opened the design space for engineers by allowing for unique and highly specialized propulsion system and vehicle designs. NASA developed the Electrical Power System – Sizing and Analysis Tool (EPS-SAT) to conduct high-level trade studies and sensitivity studies on the various propulsion system designs that can be implemented in electrified aircraft. The results of these studies would be used to better direct investment dollars and determine strengths and weaknesses of propulsion system designs. In this paper, the results of the EPS-SAT tool were validated with hardware data extracted from the NASA Revolutionary Vertical Lift Technology (RVLT) Advanced Reconfigurable Electric Aircraft Lab (AREAL). Updated performance maps were added to the EPS-SAT library so that high-fidelity results could be calculated.

Patrick A. Hanlon↗

Traffic Management Advisor: Iterative Field Development and Assessment at Multiple Sites

Previous studies have demonstrated the necessity of involving users in the development of automation aids, especially for complex domains such as air traffic control (ATC). Traditional development only demanded a single field test to validate a completed system, but a more iterative combination of development and assessment ensures that the technology meets the requirements of its application domain. Exposure across an adequate spectrum of field users is also required during development, and the use of multiple development sites provides an opportunity to consider individual facility cultures as they relate to implementation strategies. The development of the Center/TRACON Automation System (CTAS) Traffic Management Advisor (TMA) at the Denver and Dallas ATC facilities demonstrates successful iterative development and assessment at multiple field sites. The use of field development changes the nature of assessment. As development progresses, periodic assessments are required to validate that system development is progressing along an appropriate track. In the development of the TMA, assessments were performed based on software in the field, and input from traffic managers was analyzed and incorporated into subsequent releases of the TMA, to be reassessed in the field. This has led to a tool with operational suitability and broad user acceptance. Assessment at multiple sites provides a more generalizable perspective that allows the production of a system that is both generic enough to be used at different sites and tailored enough to be of use at any site. In addition to providing a better understanding of specific facility requirements, the use of multiple assessment sites in the development of TMA has provided an opportunity to consider individual facility operations, procedures and cultures as they relate to development and implementation strategies.

Sanford, Beverly D.↗

A Robust Compositional Architecture for Autonomous Systems

Space exploration applications can benefit greatly from autonomous systems. Great distances, limited communications and high costs make direct operations impossible while mandating operations reliability and efficiency beyond what traditional commanding can provide. Autonomous systems can improve reliability and enhance spacecraft capability significantly. However, there is reluctance to utilizing autonomous systems. In part this is due to general hesitation about new technologies, but a more tangible concern is that of reliability of predictability of autonomous software. In this paper, we describe ongoing work aimed at increasing robustness and predictability of autonomous software, with the ultimate goal of building trust in such systems. The work combines state-of-the-art technologies and capabilities in autonomous systems with advanced validation and synthesis techniques. The focus of this paper is on the autonomous system architecture that has been defined, and on how it enables the application of validation techniques for resulting autonomous systems.

Brat, Guillaume↗