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A comparison of two neural network schemes for navigation

Neural networks have been applied to tasks in several areas of artificial intelligence, including vision, speech, and language. Relatively little work has been done in the area of problem solving. Two approaches to path-finding are presented, both using neural network techniques. Both techniques require a training period. Training under the back propagation (BPL) method was accomplished by presenting representations of current position, goal position pairs as input and appropriate actions as output. The Hebbian/interactive activation (HIA) method uses the Hebbian rule to associate points that are nearby. A path to a goal is found by activating a representation of the goal in the network and processing until the current position is activated above some threshold level. BPL, using back-propagation learning, failed to learn, except in a very trivial fashion, that is equivalent to table lookup techniques. HIA, performed much better, and required storage of fewer weights. In drawing a comparison, it is important to note that back propagation techniques depend critically upon the forms of representation used, and can be sensitive to parameters in the simulations; hence the BPL technique may yet yield strong results.

Munro, Paul↗

ReVise: A Human-AI Interface for Incremental Algorithmic Recourse

The recent adoption of artificial intelligence in socio-technical systems raises concerns about the black-box nature of the resulting decisions in fields such as hiring, finance, admissions, etc. If data subjects—such as job applicants, loan applicants, and students—receive an unfavorable outcome, they may be interested in algorithmic recourse, which involves updating certain features to yield a more favorable result when re-evaluated by algorithmic decision-making. Unfortunately, when individuals do not fully understand the incremental steps needed to change their circumstances, they risk following misguided paths that can lead to significant, long-term adverse consequences. Existing recourse approaches focus exclusively on the final recourse goal but neglect the possible incremental steps to reach the goal with real-life constraints, user preferences, and model artifacts. To address this gap, we formulate a visual analytic workflow for incremental recourse planning in collaboration with AI/ML experts and contribute an interactive visualization interface that helps data subjects efficiently navigate the recourse alternatives and make an informed decision. We also present one of the many usage scenarios, developed during exploratory feedback sessions with twelve graduate students using a real-world dataset, which demonstrates that our approach can be instrumental for data subjects in choosing a suitable recourse path.

algorithmic recourse↗

Geometrical-Based Navigation System Performance Assessment in the Space Service Volume Using a Multiglobal Navigation Satellite System Methodology

NASA is participating in the International Committee on Global Navigation Satellite Systems (GNSS) (ICG)'s efforts towards demonstrating the benefits to the space user in the Space Service Volume (SSV) when a multi-GNSS solution space approach is utilized. The ICG Working Group: Enhancement of GNSS Performance, New Services and Capabilities has started a three phase analysis initiative as an outcome of recommendations at the ICG-10 meeting, in preparation for the ICG-11 meeting. The first phase of that increasing complexity and fidelity analysis initiative is based on a pure geometrically-derived access technique. The first phase of analysis has been completed, and the results are documented in this paper.

Global Positioning System↗

Accelerating catalytic advancements through the precision of high-throughput experiments & calculations

The growing demand for energy-efficient processes to support a sustainable future drives the need for research to rapidly explore chemical and material space through accelerated catalyst discovery initiatives. Recent breakthroughs in high-throughput experimental and computational methods are transforming the catalysis field, surpassing traditional approaches to manipulating variables in catalytic processes. Key advancements in innovation include the integration of machine learning for efficient catalyst screening, high-throughput experimentation, data-driven methodologies employing comprehensive databases, and in situ and in operando techniques for realistic observations. This progress has undoubtedly been intertwined with a collaborative framework across disciplines, reshaping catalyst discovery methods in both industry and academia. This Opinion article presents a multifaceted perspective from coauthors with expertise spanning various stages of the Technology Readiness Level spectrum, highlighting both opportunities and persistent challenges in integrating computational and experimental approaches in catalysis. These challenges span from obtaining high-quality experimental data, scaling simulations to industrially relevant materials and process conditions to navigating the complexity and predictive accuracy of computational models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Equity-Centered Engagement Through Climate Resilience Policy in Massachusetts

Communities who experience disproportionate climate change impacts tend to be excluded from resilience planning (Vale, 2014). Those efforts typically follow top-down processes within established governance practices that are inaccessible to marginalized folks and reinforce inequalities (Malloy & Ashcraft, 2020; Adger, 2003). Such participatory planning processes may offer the public little opportunity to influence the process itself or the outcomes (Smith & McDonough, 2001). They might ignore important public values or alternative ways of knowing which can be critical assets in resilience (Few et al., 2007). Designing communities for climate action and resilience means creating opportunities for everyone to meaningfully shape those decisions and experience related benefits. Having the opportunity to shape one’s community is necessary for human flourishing (Allen, 2016). Resilience planning that shifts power into communities and focuses on social vulnerability can affect how people survive and thrive in a climate changed world. The Massachusetts Municipal Vulnerability Preparedness (MVP) 2.0 program is an attempt to change the status quo in resilience planning by bringing new voices into decision-making power, recognizing their labor, addressing root causes of vulnerability, and investing in social infrastructure. It aspires to build capacity for equity-focused community engagement within teams of municipal staff and community liaisons, and ultimately build social capital and community cohesion. My mixed methods research investigates implementation of this state grant program in several western Massachusetts towns. I am using document review, participant observation, and interviews to understand the MVP 2.0 process as written, how different towns navigate it, and how individuals make sense of their experiences in it. I seek to understand how those experiences explain relationships between engagement approaches, mediating factors, and process outcomes. I am interested in the conditions that allow for community empowerment and how a model like MVP 2.0 can shift conditions that hold systems in place. In a practical sense, our findings will help municipalities reflect on their work during MVP 2.0 and plan for future community engagement. They may be informative for designing future iterations of the MVP program and for other municipalities, offices of community engagement, and practitioners. The findings will also contribute to the participation, resilience, and climate justice literatures, by adding perspectives on equity-centered resilience and community engagement approaches in smaller towns and rural settings. References: Adger, W. N. (2003). Social capital, collective action, and adaptation to climate change. Economic Geography, 79, 387-404. Allen, D. (2016). Toward a connected society. Our compelling interests: The value of diversity for democracy and a prosperous society, 71-105. Few, R., Brown, K., & Tompkins, E. L. (2007). Public participation and climate change adaptation: avoiding the illusion of inclusion. Climate Policy, 7(1), 46–59. Malloy, J. T., & Ashcraft, C. M. (2020). A framework for implementing socially just climate adaptation. Climatic Change, 160(1), 1–14. Smith, P. D., & McDonough, M. H. (2001). Beyond public participation: Fairness in natural resource decision making. Society & natural resources, 14(3), 239-249. Vale, L. J. (2014). The politics of resilient cities: whose resilience and whose city? Building Research & Information, 42(2), 191–201.

Callaham, Shannon↗

Equity-Centered Engagement Through Climate Resilience Policy in Massachusetts

Communities who experience disproportionate climate change impacts tend to be excluded from resilience planning. Those efforts typically follow top-down processes within established governance practices that are inaccessible to marginalized folks and reinforce inequalities. Regenerating the commons includes creating opportunities for everyone to meaningfully shape community resilience decisions and experience related benefits. Resilience planning that shifts power into communities and focuses on social vulnerability can affect how people survive and thrive in a climate changed world. The Massachusetts Municipal Vulnerability Preparedness (MVP) 2.0 program is an attempt to change the status quo in resilience planning by bringing new voices into decision-making power, recognizing their labor, addressing root causes of vulnerability, and investing in social infrastructure. It aspires to build capacity for equity-focused community engagement within teams of municipal staff and community liaisons, and ultimately build social capital and community cohesion. My research investigates implementation of this state grant program in several western Massachusetts towns. I am using document review, participant observation, and interviews to understand the MVP 2.0 process as written, how different towns navigate it, and how individuals make sense of their experiences in it. I seek to understand how those experiences explain relationships between engagement approaches, mediating factors, and process outcomes. I am interested in the conditions that allow for community empowerment and how a model like MVP 2.0 can shift conditions that hold systems in place. In a practical sense, our findings will help municipalities reflect on their work during MVP 2.0 and plan for future community engagement. They may be informative for designing future iterations of the MVP program and for other municipalities or offices of community engagement. The findings will also contribute to the participation, resilience, and climate justice literatures, by adding perspectives on equity-centered resilience and community engagement approaches in smaller towns and rural settings.

Callaham, Shannon↗

Investigating the Influence of River Geomorphology on Human Presence Using Night Light Data: A Case Study in the Indus Basin

Human settlements have historically thrived near rivers due to enhanced navigation and trade, and the availability of water supply and resources. The use of night light data, representing economic activities, provides a novel approach to studying the interactions between human activity and rivers over time. Here, we use the Defense Meteorological Satellite Program (DMSP) stable night light data from 2000 to 2013 as a proxy for human presence and activities to quantify the statistical relationships between night light presence and intensity in the Indus Basin, Asia. We test how these data are affected by proximity to trunk channels and by channel type (single/multi-thread) in the study area. We find that night light presence is enhanced by 26% within a 0 to 5 km proximity range of the Indus River and its tributaries, relative to the basin as a whole. We interpret this to represent increased human presence and activity within this zone. However, the mean intensity is lower near the river and higher away from the river, signifying denser settlements, such as towns and cities, which are preferentially located away from the Indus and its tributaries. Moreover, the enhancement of lit pixels signifying human presence and activities is increased by 18% near single-thread sections of the Indus River, compared to segments of the Indus displaying multi-thread morphologies. We suggest that this is due to the enhanced stability of single-threaded channels, relative to mobile multi-threaded channel reaches. This study demonstrates how night lights are an important tool in studying the relationship between human presence and river dynamics in large catchments such as the Indus, and we suggest that these data will have an important role in assessing differential flood spatial and social vulnerability at a regional scale.

Environmental Sciences & Ecology↗

Simulation of a weather radar display for over-water airborne radar approaches

Airborne radar approach (ARA) concepts are being investigated as a part of NASA's Rotorcraft All-Weather Operations Research Program on advanced guidance and navigation methods. This research is being conducted using both piloted simulations and flight test evaluations. For the piloted simulations, a mathematical model of the airborne radar was developed for over-water ARAs to offshore platforms. This simulated flight scenario requires radar simulation of point targets, such as oil rigs and ships, distributed sea clutter, and transponder beacon replies. Radar theory, weather radar characteristics, and empirical data derived from in-flight radar photographs are combined to model a civil weather/mapping radar typical of those used in offshore rotorcraft operations. The resulting radar simulation is realistic and provides the needed simulation capability for ongoing ARA research.

Clary, G. R.↗

Enabling Autonomous Rover Science through Dynamic Planning and Scheduling

This paper describes how dynamic planning and scheduling techniques can be used onboard a rover to autonomously adjust rover activities in support of science goals. These goals could be identified by scientists on the ground or could be identified by onboard data-analysis software. Several different types of dynamic decisions are described, including the handling of opportunistic science goals identified during rover traverses, preserving high priority science targets when resources, such as power, are unexpectedly over-subscribed, and dynamically adding additional, ground-specified science targets when rover actions are executed more quickly than expected. After describing our specific system approach, we discuss some of the particular challenges we have examined to support autonomous rover decision-making. These include interaction with rover navigation and path-planning software and handling large amounts of uncertainty in state and resource estimations.

planning↗

Guidance and Navigation Design for a Martian Sample Return Ascent Vehicle

This paper focuses on the work being performed at the NASA Marshall Space Flight Center (MSFC) in support of Mars Ascent Vehicles (MAVs). Specifically, the analysis presented is in support of Martian sample return architectures. In or-der to assess vehicle sensitivities, a detailed simulation tool, (MAV Analysis Tool in Simscape) MANTIS, was implemented using the MATLAB/Simulink Sim-scape architecture. High fidelity navigation sensor models and guidance algorithms were included in order to facilitate sensor requirement development and flight algorithm selection. This work focuses on the performance of the integrated system and the coupling of navigation and guidance capabilities. The architecture trades are heavily dependent on the ascent flight profile chosen. This work assesses both open- and closed-loop guidance algorithms to capture their relative performance and the resulting requirements on sensor capability to support preliminary vehicle design. The analysis builds on previous work that focused on navigation performance for initialization and ascent flight of crewed vehicle. The results provide insight into the coupling between sensor requirements and ascent guidance approach. The analysis provides data to support requirements for hard-ware selection and testing. Additional discussion is also included focusing on other system constraints that affect hardware selection and operational constraints.

Anzalone, Evan↗

Strategic Deconfliction Performance: Results and Analysis from the NASA UTM Technical Capability Level 4 Demonstration

Unmanned Aircraft System (UAS) Traffic Management (UTM) refers to the service-based, cooperative approach to the management of small UAS in the National Airspace System that is safe, scalable, and fair. UTM provides the means to manage the airspace in a complementary manner that does not burden the current air traffic control workforce or infrastructure but allows the Air Navigation Service Provider to maintain its regulatory and operational authority of the airspace. A key feature of UTM is the ability to provide operators the means to strategically deconflict operations from others in the airspace through the digital exchange of information via supporting services. Through this approach, the four-dimensional operation volumes that encompass the intent of operators in a given area are discoverable and can be used for airspace awareness as well as planning conflict free operations that account for and avoid other operations. In certain cases, it is also possible to negotiate volume intersections for shared airspace use without the need to re-plan. In the NASA UTM concept, strategic deconfliction is the first layer of three in the overall conflict management model. The three layers of the conflict management model, which follow the International Civil Aviation Organization’s scheme [ICAO 2005] are: strategic conflict management, separate provision, and collision avoidance. In UTM, the strategic layer mostly occurs prior to departure, but is applicable to en route operations with sufficient planning horizon. The initial requirements for a strategic deconfliction capability within UTM are defined in a NASA publication [Rios 2018]. Within the concept and implementation of service-provided strategic deconfliction is the notion of priority. It is understood that there are instances in which an operation requires a priority designation within the UTM system and special handling accordingly to provide situation awareness and facilitate appropriate responses from other airspace users. Examples of situations requiring priority designation include: when an operator declares an emergency due to problems with the vehicle or its immediate surroundings; operations that are in support of certain organizations (e.g., public safety and first responders); or special missions that also require priority use of airspace (e.g., emergency medical deliveries). UAS Volume Reservations (UVRs) also relate to the topic of priority in the sense that the airspace that the volume encompasses has a different status or classification in which unassociated operations must vacate if inside, or avoid if outside, through strategic deconfliction with the volume. Operations that are specially permitted to access the UVR area are typically assigned priority status given the nature of their mission and their associated credentials. The ability to perform strategic deconfliction, handle certain operations with a priority distinction, and establish UVRs that are communicated throughout the UTM system, is predicated on an architecture that has been established through an evolutionary process in response to close collaboration with stakeholders from government and industry. Another important and influential aspect of these capabilities and architecture is the live, distributed flight tests that have been conducted across the Technical Capability Levels (TCLs) that culminated with a set of complex tests performed as part of TCL4 [Rios 2020]. The TCL4 flight test involved two FAA-designated UAS test sites building teams to collaborate with NASA’s UTM Project on the execution of several detailed, small UAS scenarios in urban environments.

conflict management↗

Cramer-Rao Lower Bound for SoOp-R-Based Root-Zone Soil Moisture Remote Sensing

Signals of opportunity (SoOp) reflectometry (SoOp-R) is a maturing field for geophysical remote sensing as evidenced by the growing number of airborne and spaceborne experiments. As this approach receives more attention, it is worth analyzing SoOp-R’s capabilities to retrieve subsurface soil moisture (SM) by leveraging communication and navigation satellite transmitters. In this research, the CRLB is used to identify the effects of variable SoOp-R parameters on the best achievable estimation error for root-zone soil moisture (RZSM). This study investigates the use of multiple frequency, polarization, and incidence angle measurement configurations on a two-layered dielectric profile. The results also detail the effects of variable SM conditions on the capability of SoOp-R systems to predict subsurface SM. The most prevalent observation is the importance of using at least two frequencies to limit uncertainties from subsurface SM estimates. If at least two frequencies are used, the CRLB of a profile is retrievable within the root-zone depending on the surface SM content as well as the number of independent measurements of the profile. For a depth of 30 cm, it is observed that a CRLB corresponding to 4% RZSM estimation accuracy is achievable with as few as 2 dual-frequency-based SoOp-R measurements. For this depth, increasing number of measurements provided by polarization and incidence angle allow for sensing of increasingly wet SM profile structures. This study, overall, details a methodology by which SoOp-R receiver system can be designed to achieve a desired CRLB using a trade-off study between the available measurements and SM profile.

Signals of Opportunity (SoOp)↗

ELEET- Formulating a Multi-Element, Inter-agency Error Budget for Robust Earth Entry of Returned Mars Samples

The operational segment of a potential Mars Sample Return campaign could end with final delivery of the Earth Entry System to the surface of Earth, punctuating an impressive international collaboration on multiple flight elements over many years. A comprehensive error budget approach is presented to characterize the high-dimensional technical challenge of this concept, including inputs from interdisciplinary stakeholders. Effects considered include interplanetary navigation, spacecraft attitude and maneuver control, and entry environment, culminating in figures of merit such as landing range accuracy. Broad tradespace exploration confirms some intuitions while challenging others, and a set of solutions are identified that are mutually agreeable to NASA and ESA.

Lobbia, Marcus↗

Advancement of Deep Learning and Geometric Methods for Active Terrain Relative Navigation

To enhance NASA’s precision landing capabilities, in conjunction with the development of a novel active terrain relative navigation (ATRN) and terrain mapping system, denoted SHERIF, this work performed a comparative analysis between both deep-learning (DL) based and geometric approaches to hazard detection (HD) and safe-site-identification (SSI) through hardware-in-the loop testing on the Six degree-of-freedom Tendon Actuated Robot (STAR). The Standalone Hazard Evaluation and Refinement using Instrument Findings (SHERIF) system is capable of ingesting sensor data at an asynchronous rate, stitching successive terrain scans together to yield a high-resolution digital elevation map (DEM), performing absolute and relative localization using novel 3D feature extraction and matching methods, and HD/SSI activities. The DL-based HD/SSI algorithm provides a modular alternative to classical geometric approaches which have performance times that scale with map resolution. As the adoption of AI solutions become more prevalent for autonomous system decision making, it is prudent to explore the utility of such solutions in applications where they traditionally excel, such as image classification. Along with the development of a DL-based HD system, this work performed the first comparative analysis between DL and geometric approaches to HD/SSI using real sensor data from real-time testing in a relevant environment.

Davis Adams↗

Safe Maritime Navigation with COLREGS Using Velocity Obstacles

This paper presents a motion planning algorithm for Unmanned Surface Vehicles (USVs) to navigate safely in dynamic, cluttered environments. The proposed algorithm not only addresses Hazard Avoidance (HA) for stationary and moving hazards but also applies the International Regulations for Preventing Collisions at Sea (known as COLREGs). The COLREG rules specify, for example, which vessel is responsible for giving way to the other and to which side of the "stand-on" vessel to maneuver. The three primary COLREG rules were considered in this paper: crossing, overtaking, and head-on situations. For USVs to be safely deployed in environments with other traffic boats, it is imperative that the USV's navigation algorithm obey COLREGs. Note also that if other boats disregard their responsibility under COLREGs, the USV will still apply its HA algorithms to avoid a collision. The proposed approach is based on Velocity Obstacles, which generates a cone-shaped obstacle in the velocity space. Because Velocity Obstacles also specify which side of the obstacle the vehicle will pass during the avoidance maneuver, COLREGs are encoded in the velocity space in a natural way. The algorithm is demonstrated via both simulation and on-water tests.

velocity obstacles↗

Capability Gaps Assessment and Identification of Critical Technology Elements for Mars Transit Habitat

The Habitation Systems Development Office (HP40) at NASA Marshall Space Flight Center supports systems engineering, integration, and project management for next generation space habitats. For in space operations and eventual transport of humans to Mars, NASA will rely on a Mars Transit Habitat (TH). The TH will be designed for an up to 1,200-day Mars mission and will carry all food and supplies needed to support four crew for this duration. In the current concept of operations, Mars TH transfers to near rectilinear halo orbit (NRHO) following launch and docks at Gateway as a visiting vehicle. While there, the TH will complete system shakedown testing and a series of analog missions which will grow from 3 to 6+ months in duration TH also augments Gateway’s habitation capabilities beyond 60-days. Proposed Gateway-TH missions will far exceed the longest duration cislunar human missions to date. These shakedown missions will also be the first operational readiness tests of Mars TH’s long-duration deep space systems, and of the split crew (two crew on the surface, two crew in space) operations that are vital to the approach for the first human Mars mission. Once shakedown missions are complete, Mars TH departs Gateway to aggregate with the Mars propulsion system in NRHO before onboarding the crew and final supplies in Earth orbit via a co-manifested Orion-logistics module. Orion and the LM return to Earth prior to the now aggregated Deep Space Transport vehicle’s journey to Mars. Development of the Mars TH requires significant technology development and maturation. Each year the agency performs a capability gaps assessment, where gaps developed by subject matter experts (SMEs) in various engineering/science disciplines are linked to architectural elements in formulation and prioritized. A gap captures the difference between the current state-of-the-art and the maturity of the capability that is needed to enable or enhance a mission as it is currently envisioned in the government reference architecture. HP40 conducted a gap analysis for Mars TH which will be summarized in this poster. Gaps classified as enabling (which means the mission cannot achieve success without gap closure) were subsequently used to identify critical technology elements (CTEs) for Mars TH. This identification of CTEs was also informed by an examination of the product breakdown structure for Mars TH and focused conversations with SMEs in specific technology areas. CTEs identified for Mars TH to date include the following (note this is not a comprehensive list – CTEs listed represent those in MSFC’s capability areas): inflatable softgoods for habitation; enhanced CO2 recovery; life support systems with greater levels of reliability and maintainability; autonomous guidance, navigation, command and control; and radiators for the Mars TH application. The habitation systems development team is currently delving deeper into each CTE to assess technology approaches being pursued, their maturity, and the degree of difficulty in maturation to meet projected Mars TH timelines. This poster will summarize work to date on the identification of enabling capability gaps linked to Mars TH and provide insight into the associated CTEs and technology maturation efforts.

technology development↗

Autonomous sputter synthesis of thin film nitrides with composition controlled by Bayesian optimization of optical plasma emission

Autonomous experimentation has emerged as an efficient approach to accelerate the pace of material discovery. Although instruments for autonomous synthesis have become popular in molecular and polymer science, solution processing of hybrid materials, and nanoparticles, examples of autonomous tools for physical vapor deposition are scarce yet important for the semiconductor industry. Here, we report the design and implementation of an autonomous workflow for sputter deposition of thin films with controlled composition, leveraging a highly automated sputtering reactor custom-controlled by Python, optical emission spectroscopy (OES), and a Bayesian optimization algorithm. We modeled film composition, measured by x-ray fluorescence, as a linear function of plasma emission lines monitored during co-sputtering from elemental Zn and Ti targets in an N 2 and Ar atmosphere. A Bayesian control algorithm, informed by OES, navigates the space of sputtering power to fabricate films with user-defined compositions by minimizing the absolute error between desired and measured optical emission signals. We validated our approach by autonomously fabricating Zn x Ti 1-x N y films that deviate from the targeted cation composition by a relative ±3.5%, even for 15 nm thin films, demonstrating that the proposed approach can reliably synthesize thin films with a specific composition and minimal human interference. Moreover, the proposed method can be extended to more difficult synthesis experiments where plasma intensity lines depend non-linearly on pressure, or the elemental sticking coefficients strongly depend on the substrate temperature.

36 MATERIALS SCIENCE↗

Single-Command Approach and Instrument Placement by a Robot on a Target

AUTOAPPROACH is a computer program that enables a mobile robot to approach a target autonomously, starting from a distance of as much as 10 m, in response to a single command. AUTOAPPROACH is used in conjunction with (1) software that analyzes images acquired by stereoscopic cameras aboard the robot and (2) navigation and path-planning software that utilizes odometer readings along with the output of the image-analysis software. Intended originally for application to an instrumented, wheeled robot (rover) in scientific exploration of Mars, AUTOAPPROACH could be adapted to terrestrial applications, notably including the robotic removal of land mines and other unexploded ordnance. A human operator generates the approach command by selecting the target in images acquired by the robot cameras. The approach path consists of multiple legs. Feature points are derived from images that contain the target and are thereafter tracked to correct odometric errors and iteratively refine estimates of the position and orientation of the robot relative to the target on successive legs. The approach is terminated when the robot attains the position and orientation required for placing a scientific instrument at the target. The workspace of the robot arm is then autonomously checked for self/terrain collisions prior to the deployment of the scientific instrument onto the target.

Huntsberger, Terrance↗