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At least 1,333 records · Page 74

Autonomous hazard detection and avoidance

During GFY 91, Draper Laboratory was awarded a task by NASA-JSC under contract number NAS9-18426 to study and evaluate the potential for achieving safe autonomous landings on Mars using an on-board autonomous hazard detection and avoidance (AHDA) system. This report describes the results of that study. The AHDA task had four objectives: to demonstrate, via a closed-loop simulation, the ability to autonomously select safe landing sites and the ability to maneuver to the selected site; to identify key issues in the development of AHDA systems; to produce strawman designs for AHDA sensors and algorithms; and to perform initial trade studies leading to better understanding of the effect of sensor/terrain/viewing parameters on AHDA algorithm performance. This report summarizes the progress made during the first year, with primary emphasis on describing the tools developed for simulating a closed-loop AHDA landing. Some cursory performance evaluation results are also presented.

Pien, Homer↗

Terrain Model Registration for Single Cycle Instrument Placement

This paper presents an efficient and robust method for registration of terrain models created using stereo vision on a planetary rover. Our approach projects two surface models into a virtual depth map, rendering the models as they would be seen from a single range sensor. Correspondence is established based on which points project to the same location in the virtual range sensor. A robust norm of the deviations in observed depth is used as the objective function, and the algorithm searches for the rigid transformation which minimizes the norm. An initial coarse search is done using rover pose information from odometry and orientation sensing. A fine search is done using Levenberg-Marquardt. Our method enables a planetary rover to keep track of designated science targets as it moves, and to hand off targets from one set of stereo cameras to another. These capabilities are essential for the rover to autonomously approach a science target and place an instrument in contact in a single command cycle.

Deans, Matthew↗

Baroreflex-mediated heart rate and vascular resistance responses 24 h after maximal exercise

INTRODUCTION: Plasma volume, heart rate (HR) variability, and stimulus-response relationships for baroreflex control of forearm vascular resistance (FVR) and HR were studied in eight healthy men after and without performing a bout of maximal exercise to test the hypotheses that acute expansion of plasma volume is associated with 1) reduction in baroreflex-mediated HR response, and 2) altered operational range for central venous pressure (CVP). METHODS: The relationship between stimulus (DeltaCVP) and vasoconstrictive reflex response (DeltaFVR) during unloading of cardiopulmonary baroreceptors was assessed with lower-body negative pressure (LBNP, 0, -5, -10, -15, -20 mm Hg). The relationship between stimulus (Deltamean arterial pressure (MAP)) and cardiac reflex response (DeltaHR) during loading of arterial baroreceptors was assessed with steady-state infusion of phenylephrine (PE) designed to increase MAP by 15 mm Hg alone and during application of LBNP (PE+LBNP) and neck pressure (PE+LBNP+NP). Measurements of vascular volume and autonomic baroreflex responses were conducted on two different test days, each separated by at least 1 wk. On one day, baroreflex response was tested 24 h after graded cycle exercise to volitional exhaustion. On another day, measurement of baroreflex response was repeated with no exercise (control). The order of exercise and control treatments was counterbalanced. RESULTS: Baseline CVP was elevated (P = 0.04) from a control value of 10.5 +/- 0.4 to 12.3 +/- 0.4 mm Hg 24 h after exercise. Average DeltaFVR/DeltaCVP during LBNP was not different (P = 0.942) between the exercise (-1.35 +/- 0.32 pru x mm Hg-1) and control (-1.32 +/- 0.36 pru x mm Hg-1) conditions. However, maximal exercise caused a shift along the reflex response relationship to a higher CVP and lower FVR. HR baroreflex response (DeltaHR/DeltaMAP) to PE+LBNP+NP was lower (P = 0.015) after maximal exercise (-0.43 +/- 0.15 beats x min-1 x mm Hg-1) compared with the control condition (-0.83 +/- 0.14 beats x min-1 x mm Hg-1). CONCLUSION: Expansion of vascular volume after acute exercise is associated with altered operational range for CVP and reduced HR response to arterial baroreceptor stimulation.

Non-NASA Center↗

Anti-Collision Function Design and Performances of the CNES Formation Flying Experiment on the PRISMA Mission

Within the framework of a partnership agreement, EADS ASTRIUM has worked since June 2006 for the CNES formation flying experiment on the PRISMA mission. EADS ASTRIUM is responsible for the anti-collision function. This responsibility covers the design and the development of the function as a Matlab/Simulink library, as well as its functional validation and performance assessment. PRISMA is a technology in-orbit testbed mission from the Swedish National Space Board, mainly devoted to formation flying demonstration. PRISMA is made of two micro-satellites that will be launched in 2009 on a quasi-circular SSO at about 700 km of altitude. The CNES FFIORD experiment embedded on PRISMA aims at flight validating an FFRF sensor designed for formation control, and assessing its performances, in preparation to future formation flying missions such as Simbol X; FFIORD aims as well at validating various typical autonomous rendezvous and formation guidance and control algorithms. This paper presents the principles of the collision avoidance function developed by EADS ASTRIUM for FFIORD; three kinds of maneuvers were implemented and are presented in this paper with their performances.

Cayeux, P.↗

XMbodyinfo

XMbodyinfo was designed to evaluate potential reference trajectories, providing a proficient way to assess the quality of all satellite body flybys for a Cassini type mission tour. It is autonomous and will generate a variety of ORS (optical remote sensing) and FPW (fields, particles, and waves) plots that aid in the evaluation, qualification, selection, and improvement of a potential tour.

Roumeliotis, Chris↗

Real-Time Wireless Data Acquisition System

Current and future aerospace requirements demand the creation of a new breed of sensing devices, with emphasis on reduced weight, power consumption, and physical size. This new generation of sensors must possess a high degree of intelligence to provide critical data efficiently and in real-time. Intelligence will include self-calibration, self-health assessment, and pre-processing of raw data at the sensor level. Most of these features are already incorporated in the Wireless Sensors Network (SensorNet(TradeMark)), developed by the Instrumentation Group at Kennedy Space Center (KSC). A system based on the SensorNet(TradeMark) architecture consists of data collection point(s) called Central Stations (CS) and intelligent sensors called Remote Stations (RS) where one or more CSs can be accommodated depending on the specific application. The CS's major function is to establish communications with the Remote Stations and to poll each RS for data and health information. The CS also collects, stores and distributes these data to the appropriate systems requiring the information. The system has the ability to perform point-to-point, multi-point and relay mode communications with an autonomous self-diagnosis of each communications link. Upon detection of a communication failure, the system automatically reconfigures to establish new communication paths. These communication paths are automatically and autonomously selected as the best paths by the system based on the existing operating environment. The data acquisition system currently under development at KSC consists of the SensorNet(TradeMark) wireless sensors as the remote stations and the central station called the Radio Frequency Health Node (RFHN). The RFF1N is the central station which remotely communicates with the SensorNet(TradeMark) sensors to control them and to receive data. The system's salient feature is the ability to provide deterministic sensor data with accurate time stamps for both time critical and non-time critical applications. Current wireless standards such as Zigbee(TradeMark) and Bluetooth(Registered TradeMark) do not have these capabilities and can not meet the needs that are provided by the SensorNet technology. Additionally, the system has the ability to automatically reconfigure the wireless communication link to a secondary frequency if interference is encountered and can autonomously search for a sensor that was perceived to be lost using the relay capabilities of the sensors and the secondary frequency. The RFHN and the SensorNet designs are based on modular architectures that allow for future increases in capability and the ability to expand or upgrade with relative ease. The RFHN and SensorNet sensors .can also perform data processing which forms a distributed processing architecture allowing the system to pass along information rather than just sending "raw data points" to the next higher level system. With a relatively small size, weight and power consumption, this system has the potential for both spacecraft and aircraft applications as well as ground applications that require time critical data.

Valencia, Emilio J.↗

Testing a Run-Time Assurance Framework Coupled with Integrated Risk Mitigation Capabilities for Autonomous Urban UAS Flights

The In-Time Aviation Safety Management System (IASMS) Concept of Operations (ConOps) envisions new capabilities to monitor, assess, and mitigate flight safety risks. Systems will be tailored to mission type, vehicle/equipage type, operational environment, and safety risk tolerance. Within an IASMS framework, several capabilities may be implemented spanning three operational phases (pre-flight, in-flight, and post-flight/off-line); and consisting of lower level functions and information services which may reside onboard the aircraft, on third-party server(s), and/or on ground/operator station(s). Each capability will be designed to produce and disseminate safety-relevant information; perform detection, diagnosis, and prediction of unsafe situations; and/or execute mitigation actions when hazardous events warrant such changes. This paper focuses on recent testing of airborne capabilities that demonstrate inflight aspects of the overarching concept for autonomous unmanned aircraft systems (UAS) operations in urban environments. A flight test architecture is described that applies run-time assurance principles (e.g., executes independent of the unassured autopilot), real-time risk assessment, and a technique to execute contingencies if necessary either automatically or via pilot intervention. Several tests using small UAS were conducted to verify the assured in-flight risk mitigation capability. The paper draws significantly from a larger NASA technical report and recent prior conference papers, providing additional details. Data is analyzed for two representative flights to illustrate the performance for various sequential and simultaneous hazards used during testing. During each automated flight, several hazards are encountered at various points along the flight path. At each point, the hazard is mitigated by the system, with the vehicle then continuing to subsequent points. The paper concludes with lessons-learned regarding relevant aspects of the overarching IASMS concept and how it may be updated and further advanced in the future.

population activity↗

Advanced Automation for Ion Trap Mass Spectrometry-New Opportunities for Real-Time Autonomous Analysis

The utility of MS/MS for both target compound analysis and the structure elucidation of unknowns has been described in a number of references. A broader acceptance of this technique has not yet been realized as it requires large, complex, and costly instrumentation which has not been competitive with more conventional techniques. Recent advancements in ion trap mass spectrometry promise to change this situation. Although the ion trap's small size, sensitivity, and ability to perform multiple stages of mass spectrometry have made it eminently suitable for on-line, real-time monitoring applications, advance automation techniques are required to make these capabilities more accessible to non-experts. Towards this end we have developed custom software for the design and implementation of MS/MS experiments. This software allows the user to take full advantage of the ion trap's versatility with respect to ionization techniques, scan proxies, and ion accumulation/ejection methods. Additionally, expert system software has been developed for autonomous target compound analysis. This software has been linked to ion trap control software and a commercial data system to bring all of the steps in the analysis cycle under control of the expert system. These software development efforts and their utilization for a number of trace analysis applications will be described.

Palmer, Peter T.↗

Trade-off Analysis of Operational Technologies to Advance Cyber Resilience through Automated and Autonomous Response to Threats

The advancement of cyber resilience requires a preliminary stage of characterizing the trade-off space of mitigation options and how these might affect the stability and determinism of an operational technology (OT). This first step will set the stage for the proper cyber-secure and cyber-resilient design and confirm the affects that can be considered and approved by the OT and the security groups. To provide a baseline for this discussion, this paper provides a consideration of the cyberphysical interactions, possible mitigation steps against certain attacks and their corresponding affects that lend to the security design planning and evaluation process. As an integral part of the proposed scheme this work introduces the concept of systemwide fuzzer, i.e., a tool that manipulates the system state in an effort to determine mitigation response sequences that minimize detriments and maximize benefit in accordance with specified operational requirements.

97 MATHEMATICS AND COMPUTING↗

Integrated Dispatching and Charging Management of an Autonomous Electric Vehicle Ride-Hailing Fleet

Electrification and autonomous driving are two important trends in transportation systems. The convergence of these two technologies will introduce opportunities to improve transportation systems' operation and energy efficiency. One potential application is the commercial ride-hailing fleet with autonomous electric vehicles (AEVs). In order to harvest promising benefits from introducing AEVs into ride-hailing fleets, some unavoidable challenges will need to be resolved to ensure the fleets operates functionally and efficiently. This paper discusses the challenges of dispatching AEVs and their interactions with charging infrastructure. An integrated decision making framework for dispatching and charging has been designed using a system optimization approach to study the AEVs' management within the period when they drop off passengers and pick up the next passengers. Its potential fleet-wide benefits have been illustrated by comparing operations under a heuristic approach. A simulation platform has been designed to test different decision making strategies for the ride-hailing AEV fleets operational performance. Using this platform, detailed case studies have been performed with different fleet sizes, dispatching strategies, and charging infrastructure network settings. Comprehensive analyses from various aspects have been conducted to understand the AEVs' fleet operation performance, (e.g., zero occupancy vehicle miles traveled, successfully served ratio of ride-hailing requests, fleet vehicle charging downtime, and charging infrastructure utilization). Results have provided a deep understandings on operation's dynamics under various fleet system configurations and also have demonstrated advantages of the optimization-based approach for the AEV fleet management. Studies in this paper inform better designs on the future of sophisticated management strategies and charging infrastructure to support ride-hailing AEV fleet operation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Fabrication and Testing of DOE Standard Canister Closure Leak Test Assembly

DOE manages over 300 types of SNF, most of which are located at the INL site. “Road-ready dry storage” is a management concept where SNF is packaged into dry, sealed canisters, which are then placed in on-site storage in anticipation of later removal. The Idaho Cleanup Project and INL are collaborating on the Road-Ready Capability Demonstration Project, which will develop and demonstrate the designs, technology, processes, and regulatory framework for packaging DOE SNF for road-ready dry storage. In support of establishing a large-scale road-ready dry storage program at the INL site, the demonstration will package a select amount of DOE-managed SNF into DOE Standard Canisters. The closure process for the DOE Standard Canisters will include fuel and basket loading, welding, inspection, leak testing, and if needed, repair. As a follow-up to previous discussion on the design of the DOE Closure Leak Test Assembly, this report describes recent fabrication and testing efforts performed at INL. DOE Standard Canisters are sealed by two sequential gas tungsten arc welds. Both are performed by remotely operated and semi-autonomous welding systems. The first weld is a circumferential pipe weld that completes assembly of the canister body and lid assembly. The second and final closure weld connects the vent plug to the vent port with an identical butt joint to the circumferential pipe weld. After the second weld is performed on the vent port, these welds are helium leak tested using an inside-out technique. In addition to the commercially available vacuum and leak detector systems, the DOE Standard Canister Closure Leak Test Assembly was designed for both remote and manual operation. This report describes fabrication and performance testing associated with the inside-out technique. INL staff designed and tested systems to accomplish these tasks. Hardware fabrication occurred at INL facilities. Forthcoming work includes design optimization, integration to existing systems, and implementation to packaging demonstration operations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Bootstrapping Multi-Agent Unmanned Aerial Vehicle (UAV) System Integration Using Ground-Based Assets: Lessons Learned

The highly dynamic nature of UAVs imposes significant challenges when conducting initial testing ranging from safety risks posed by high-capacity lithium batteries and spinning propellers to rigorous timing demands on controllers and the consequences of failures mid-air. Flight testing of a single vehicle is time and labor intensive due to these challenges and more, and the complexity increases exponentially with the number of vehicles. While simulations and hardware-in-the-loop bench testing can provide adequate environments for preliminary validation, differences in system deployment architecture, software interfaces, and hardware infrastructure between simulation and a fleet of real UAVs create a sizable gap that must be navigated carefully during system integration. In support of the Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) project, which had the goal of establishing a basis of certification of trust and trustworthiness in multi-agent autonomous systems, this gap was tackled from two directions. First, a novel mixed-reality simulation environment was engineered to blur the transition from simulation to flight hardware. Second, a fleet of Unmanned Surface Vehicles (USVs) was developed as a test and evaluation platform that more closely represented the final aerial fleet while eliminating many of the risks associated with air vehicles. This paper delves into the second element, analyzing the efficacy of the USV platform in performing system integration testing for the UAV system. In this paper we present the USV fleet and its role in reducing the aforementioned gaps in deployment architecture, software interfaces, and hardware infrastructure when moving from simulation to flight. An overview of the hardware and software onboard the vehicles will be provided along with supporting infrastructure. The system integration process will be documented including results in supporting both the overarching design reference mission (DRM) of ATTRACTOR and individual research efforts conducted during the project. Finally, we will discuss some of the practical lessons learned regarding the testing, deployment, and operation of multi-agent autonomous systems.

Matthew P Vaughan↗

NASA's Autonomous Formation Flying Technology Demonstration, Earth Observing-1(EO-1)

NASA's first autonomous formation flying mission, the New Millennium Program's (NMP) Earth Observing-1 (EO-1) spacecraft, recently completed its principal goal of demonstrating advanced formation control technology. This paper provides an overview of the evolution of an onboard system that was developed originally as a ground mission planning and operations tool. We discuss the Goddard Space Flight Center s formation flying algorithm, the onboard flight design and its implementation, the interface and functionality of the onboard system, and the implementation of a Kalman filter based GPS data smoother. A number of safeguards that allow the incremental phasing in of autonomy and alleviate the potential for mission-impacting anomalies from the on- board autonomous system are discussed. A comparison of the maneuvers planned onboard using the EO-1 autonomous control system to those from the operational ground-based maneuver planning system is presented to quantify our success. The maneuvers discussed encompass reactionary and routine formation maintenance. Definitive orbital data is presented that verifies all formation flying requirements.

Folta, David↗

Monitoring Agents for Assisting NASA Engineers with Shuttle Ground Processing

The Spaceport Processing Systems Branch at NASA Kennedy Space Center has designed, developed, and deployed a rule-based agent to monitor the Space Shuttle's ground processing telemetry stream. The NASA Engineering Shuttle Telemetry Agent increases situational awareness for system and hardware engineers during ground processing of the Shuttle's subsystems. The agent provides autonomous monitoring of the telemetry stream and automatically alerts system engineers when user defined conditions are satisfied. Efficiency and safety are improved through increased automation. Sandia National Labs' Java Expert System Shell is employed as the agent's rule engine. The shell's predicate logic lends itself well to capturing the heuristics and specifying the engineering rules within this domain. The declarative paradigm of the rule-based agent yields a highly modular and scalable design spanning multiple subsystems of the Shuttle. Several hundred monitoring rules have been written thus far with corresponding notifications sent to Shuttle engineers. This chapter discusses the rule-based telemetry agent used for Space Shuttle ground processing. We present the problem domain along with design and development considerations such as information modeling, knowledge capture, and the deployment of the product. We also present ongoing work with other condition monitoring agents.

Semmel, Glenn S.↗

Illuminating the Material World: Autonomous Microscopy to Understand Order, Disorder, and Everything In Between

Artificial intelligence (AI) holds immense promise for revolutionizing microscopy, yet its widespread adoption has been hindered by challenges ranging from user inexperience to limited model transferability and difficulties in operationalizing machine learning. This presentation showcases our approach to developing practical autonomy for materials discovery, aiming to accelerate the integration of AI into everyday microscopy workflows. As shown in Fig. 1, I will focus on three key areas: understanding order-disorder transitions, quantifying point defects, and achieving truly device-scale microscopy. First, I will demonstrate the power of multi-modal knowledge graphs for integrating diverse microscopy data. By combining imaging, spectroscopy, and diffraction data, these graphs provide a holistic view of material behavior, capturing the intricate relationships between different modalities [1,2]. I will present a case study on how these models illuminate the structural and chemical changes associated with irradiation in oxide thin films, revealing critical insights for designing materials for extreme environments like spaceflight and nuclear energy. Specifically, I will show how multi-modal analysis clarifies the evolution of order-disorder transitions under irradiation, a key factor influencing material performance in these applications. Next, I will address the challenge of quantifying point defects in 2D materials. We demonstrate the application of computer vision and transfer learning to accurately identify and classify various defect types, such as vacancies and substitutional atoms, and to quantify their concentrations. This information is crucial for understanding and tailoring the properties of 2D materials for applications in electronics, optoelectronics, and catalysis. For example, I will show how our models can characterize the topological distribution of point defects in MXene transition metal carbides, providing valuable insights for optimizing their performance in energy storage and separation science. Finally, I will discuss our progress toward autonomous device-scale microscopy [3,4]. We are fundamentally redesigning electron microscopes around the principles of machine reasoning, enabling automation beyond basic tasks like sample navigation and data acquisition to include sophisticated experimental design. This approach paves the way for truly reproducible and massively scaled analysis campaigns. I will emphasize the importance of autonomous microscopy platforms for high-throughput materials discovery and characterization, facilitating the rapid screening of materials for a broad range of applications and accelerating the development of next-generation technologies.

36 MATERIALS SCIENCE↗

An intelligent energy router for managing behind-the-meter resources and assets

With increase in distributed energy resources (DERs) and smart loads, each energy resource and load need a separate power conversion system leading to complex coordination and interaction, reduced energy conversion efficiency, coordinating compliance to grid standards (IEEE 1547) from multiple sources, reduced security. Also, multiple vendors with legacy system designs and proprietary communications interfaces result in redundancy and increase in cost of power electronics systems. This paper presents an energy router concept for buildings applications which provides autonomous power flow between sources and loads with a novel agent-based software interface.

Chinthavali, Madhu Sudhan↗

Real-Time Ecodriving Control in Electrified Connected and Autonomous Vehicles Using Approximate Dynamic Programing

Connected and automated vehicles (CAVs), particularly those with a hybrid electric powertrain, have the potential to significantly improve vehicle energy savings in real-world driving conditions. In particular, the ecodriving problem seeks to design optimal speed and power usage profiles based on available information from connectivity and advanced mapping features to minimize the fuel consumption over an itinerary. This paper presents a hierarchical multilayer model predictive control (MPC) approach for improving the fuel economy of a 48 V mild-hybrid powertrain in a connected vehicle environment. Approximate dynamic programing (DP) is used to solve the receding horizon optimal control problem, whose terminal cost is approximated with the base policy obtained from the long-term optimization. The controller was tested virtually (with deterministic and Monte Carlo simulation) across multiple real-world routes, demonstrating energy savings of more than 20%. The controller was then deployed on a test vehicle equipped with a rapid prototyping embedded controller. In-vehicle testing confirm the energy savings obtained in simulation and demonstrate the real-time ability of the controller.

Automation & Control Systems↗

Real-time kinematic (RTK) Drone-collected Data and Processed Models of Port Arthur Coastal Neighborhood and Pleasure Island Golf Course, June 2024

The Southeast Texas Urban Integrated field lab’s Co-design team captured aerial photos in the Port Arthur Coastal Neighborhood Community and the Golf Course on Pleasure Island, Texas, in June 2024. Aerial photos taken were through autonomous flight, and models were processed through the DroneDeploy engine. All aerial photos are in .JPG format and contained in zipped files for each area. The processed data package includes 3D models, geospatial data, mappings, and point clouds. Please be aware that DTM, Elevation toolbox, Point Cloud, and Orthomosaic use EPSG: 6588. And 3D Model uses EPSG: 3857.For using these data:- The Adobe Suite gives you great software to open .Tif files.- You can use LASUtility (Windows), ESRI ArcGIS Pro (Windows), or Blaze3D (Windows, Linux) to open a LAS file and view the data it contains.- Open an .OBJ file with a large number of free and commercial applications. Some examples include Microsoft 3D Builder, Apple Preview, Blender, and Autodesk.- You may use ArcGIS, Merkaartor, Blender (with the Google Earth Importer plug-in), Global Mapper, and Marble to open .KML files.- The .tfw world file is a text file used to georeference the GeoTIFF raster images, like the orthomosaic and the DSM. You need suitable software like ArcView to open a .TFW file.This dataset provides researchers with sufficient geometric data and the status quo of the land surface at the locations mentioned above. This dataset will support researchers' decision-making processes under uncertainties.

2D mapping↗