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At least 1,747 records · Page 97

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NASA NTRSDate not supplied

Assessment of Sensor Data Accuracy within Gazebo/ROS for High-Precision Autonomous In-Space Robotic Operations

Modeling high-precision in-space servicing, assembly, and manufacturing operations in a simulated environment is a critical step in the development of robotic systems that will be used to autonomously assemble large-scale structures in space. Limited facility size and high costs for manufacturing prototypes make it challenging to conduct full-scale operational testing under appropriate environmental conditions; therefore, testing in a modular, high-fidelity simulation environment is necessary for verification and validation of technology and architecture designs prior to launch. Several modeling and simulation environments exist both within NASA and industry that can be used to test robotic system design and operations, including the widely used commercial tool Gazebo integrated with Robotic Operating System software. Because the performance of autonomous robotic systems relies heavily on the quality of sensor input data, this paper focuses on assessing the accuracy of pose data from an optical sensor model in the Gazebo environment against the behavior of real hardware. The results of the tests will help developers using Gazebo for large-scale, high-precision simulation to account for modeling inaccuracies within their robotic control system algorithms.

simulation↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

DOE OSTI2022

Security Architecture for Microgrid Integration

The purpose of this document is to present cyber security risk considerations and mitigations for community microgrids. The mitigations discussed herein specifically focus on cyber security technical requirements for the De-centralized Autonomous Community Controller (DAC) as part of the SECURE project’s technology development effort. These requirements also consider the associated security implementation challenges involved with the decentralized characteristics of microgrids where upstream communications to utility security management functions are lost. These security recommendations and technical requirements may be used by microgrid implementers and technology vendors to specify the security design of the microgrid systems and their components.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2011

The Next Generation of Mars-GRAM and Its Role in the Autonomous Aerobraking Development Plan

The Mars Global Reference Atmospheric Model (Mars-GRAM) is an engineering-level atmospheric model widely used for diverse mission applications. Mars-GRAM 2010 is currently being used to develop the onboard atmospheric density estimator that is part of the Autonomous Aerobraking Development Plan. In previous versions, Mars-GRAM was less than realistic when used for sensitivity studies for Thermal Emission Spectrometer (TES) MapYear=0 and large optical depth values, such as tau=3. A comparison analysis has been completed between Mars-GRAM, TES and data from the Planetary Data System (PDS) resulting in updated coefficients for the functions relating density, latitude, and longitude of the sun. The adjustment factors are expressed as a function of height (z), Latitude (Lat) and areocentric solar longitude (Ls). The latest release of Mars-GRAM 2010 includes these adjustment factors that alter the in-put data from MGCM and MTGCM for the Mapping Year 0 (user-controlled dust) case. The greatest adjustment occurs at large optical depths such as tau greater than 1. The addition of the adjustment factors has led to better correspondence to TES Limb data from 0-60 km as well as better agreement with MGS, ODY and MRO data at approximately 90-135 km. Improved simulations utilizing Mars-GRAM 2010 are vital to developing the onboard atmospheric density estimator for the Autonomous Aerobraking Development Plan. Mars-GRAM 2010 was not the only planetary GRAM utilized during phase 1 of this plan; Titan-GRAM and Venus-GRAM were used to generate density data sets for Aerobraking Design Reference Missions. These data sets included altitude profiles (both vertical and along a trajectory), GRAM perturbations (tides, gravity waves, etc.) and provided density and scale height values for analysis by other Autonomous Aero-braking team members.

Justh, Hilary L.↗

NASA NTRS1999

Feasibility of Decentralized Linear-Quadratic-Gaussian Control of Autonomous Distributed Spacecraft

A distributed satellite formation, modeled as an arbitrary number of fully connected nodes in a network, could be controlled using a decentralized controller framework that distributes operations in parallel over the network. For such problems, a solution that minimizes data transmission requirements, in the context of linear-quadratic-Gaussian (LQG) control theory, was given by Speyer. This approach is advantageous because it is non-hierarchical, detected failures gracefully degrade system performance, fewer local computations are required than for a centralized controller, and it is optimal with respect to the standard LQG cost function. Disadvantages of the approach are the need for a fully connected communications network, the total operations performed over all the nodes are greater than for a centralized controller, and the approach is formulated for linear time-invariant systems. To investigate the feasibility of the decentralized approach to satellite formation flying, a simple centralized LQG design for a spacecraft orbit control problem is adapted to the decentralized framework. The simple design uses a fixed reference trajectory (an equatorial, Keplerian, circular orbit), and by appropriate choice of coordinates and measurements is formulated as a linear time-invariant system.

Carpenter, J. Russell↗

NASA NTRS1999

Feasibility of Decentralized Linear-Quadratic-Gaussian Control of Autonomous Distributed Spacecraft

Carpenter, J. Russell↗

NASA NTRSDate not supplied

An Oculometric Standard to Assess the Performance of the Ocular System for Long Duration Spaceflight

Changes in the human brain, due to spaceflight, have been a challenge to the space program since its inception; a challenge that is becoming more acute as extended International Space Station (ISS) missions become routine, a return to crewed lunar exploration is about to begin, and a multi-year crewed trip to Mars is being planned. Determining the extent to which neurophysiological adaptations may adversely impact performance in operational tasks, assessing the full-time course of these changes, and identifying/mitigating any potential long-term health consequences are crucial steps required to enable safe crew-autonomous, long-duration, deep-space missions. Vision is the predominant perceptual sense used to guide cognition and motor control in humans. Thus, it is critical for the success of any future, long-duration mission to understand how long-term exposure to microgravity and to other stressors of spaceflight and their interactions, impact visual function. This is an especially challenging task given the small and disparate samples from which we have been and will be able to collect human performance data. NASA has recently been carefully tracking spaceflight-induced ophthalmic changes, driven in large part by the fluid shifts related to microgravity. In particular, a recent study of Optical Coherence Tomography (OCT) postflight measures revealed that more than two-thirds of US crew members experience significant increases in retinal thickness after 6month or longer ISS missions. Space Associated Neuro-ocular Syndrome (SANS) also includes visual acuity decrements and other ocular structural changes that could adversely impact in-flight performance as missions become longer. However, the impact of spaceflight on the visual system is not limited to the retina. Recent comparisons of pre-and post-flight brain images have revealed structural changes throughout the brain that implicate visual, visuomotor, and visual-cognitive pathways, consistent with observed functional impacts (e.g., decreased speed/accuracy/timing of fine goal-oriented movements). Current limitations on inflight testing make it very difficult to determine when and under what conditions SANS and other disruptions of human neurological subsystems arise. Currently, one cannot anticipate the time course and extent of impairment and recovery. This study addresses this knowledge gap by creating an integrated framework of the relevant existing literature on visual and oculomotor function during spaceflight with an eye towards complementing current structural measures of visuomotor impairment with new oculometric standard measures. Using eye-movement based visual function assessment and diagnostics would provide a valuable enhancement of crew health and performance monitoring in support of deepspace exploration.

Vision↗

DOE OSTI2017

Real-Time Alpine Measurement System Using Wireless Sensor Networks

Monitoring the snow pack is crucial for many stakeholders, whether for hydro-power optimization, water management or flood control. Traditional forecasting relies on regression methods, which often results in snow melt runoff predictions of low accuracy in non-average years. Existing ground-based real-time measurement systems do not cover enough physiographic variability and are mostly installed at low elevations. We present the hardware and software design of a state-of-the-art distributedWireless Sensor Network (WSN)-based autonomous measurement system with real-time remote data transmission that gathers data of snow depth, air temperature, air relative humidity, soil moisture, soil temperature, and solar radiation in physiographically representative locations. Elevation, aspect, slope and vegetation are used to select network locations, and distribute sensors throughout a given network location, since they govern snow pack variability at various scales. Three WSNs were installed in the Sierra Nevada of Northern California throughout the North Fork of the Feather River, upstream of the Oroville dam and multiple powerhouses along the river. The WSNs gathered hydrologic variables and network health statistics throughout the 2017 water year, one of northern Sierra’s wettest years on record. These networks leverage an ultra-low-power wireless technology to interconnect their components and offer recovery features, resilience to data loss due to weather and wildlife disturbances and real-time topological visualizations of the network health. Data show considerable spatial variability of snow depth, even within a 1 km 2 network location. In conclusion, combined with existing systems, these WSNs can better detect precipitation timing and phase in, monitor sub-daily dynamics of infiltration and surface runoff during precipitation or snow melt, and inform hydro power managers about actual ablation and end-of-season date across the landscape.

47 OTHER INSTRUMENTATION↗

NASA NTRS1993

Health monitoring of Japanese payload specialist: Autonomic nervous and cardiovascular responses under reduced gravity condition (L-0)

In addition to health monitoring of the Japanese Payload Specialists (PS) during the flight, this investigation also focuses on the changes of cardiovascular hemodynamics during flight which will be conducted under the science collaboration with the Lower Body Negative Pressure (LBNP) Experiment of NASA. For the Japanese, this is an opportunity to examine firsthand the effects of microgravity of human physiology. We are particularly interested in the adaption process and how it relates to space motion sickness and cardiovascular deconditioning. By comparing data from our own experiment to data collected by others, we hope to understand the processes involved and find ways to avoid these problems for future Japanese astronauts onboard Space Station Freedom and other Japanese space ventures. The primary objective of this experiment is to monitor the health condition of Japanese Payload Specialists to maintain a good health status during and after space flight. The second purpose is to investigate the autonomic nervous system's response to space motion sickness. To achieve this, the function of the autonomic nervous system will be monitored using non-invasive techniques. Data obtained will be employed to evaluate the role of autonomic nervous system in space motion sickness and to predict susceptibility to space motion sickness. The third objective is evaluation of the adaption process of the cardiovascular system to microgravity. By observation of the hemodynamics using an echocardiogram we will gain insight on cardiovascular deconditioning. The last objective is to create a data base for use in the health care of Japanese astronauts by obtaining control data in experiment L-O in the SL-J mission.

Sekiguchi, Chiharu↗

NASA NTRS1998

Model Based Autonomy for Robust Mars Operations

Space missions have historically relied upon a large ground staff, numbering in the hundreds for complex missions, to maintain routine operations. When an anomaly occurs, this small army of engineers attempts to identify and work around the problem. A piloted Mars mission, with its multiyear duration, cost pressures, half-hour communication delays and two-week blackouts cannot be closely controlled by a battalion of engineers on Earth. Flight crew involvement in routine system operations must also be minimized to maximize science return. It also may be unrealistic to require the crew have the expertise in each mission subsystem needed to diagnose a system failure and effect a timely repair, as engineers did for Apollo 13. Enter model-based autonomy, which allows complex systems to autonomously maintain operation despite failures or anomalous conditions, contributing to safe, robust, and minimally supervised operation of spacecraft, life support, In Situ Resource Utilization (ISRU) and power systems. Autonomous reasoning is central to the approach. A reasoning algorithm uses a logical or mathematical model of a system to infer how to operate the system, diagnose failures and generate appropriate behavior to repair or reconfigure the system in response. The 'plug and play' nature of the models enables low cost development of autonomy for multiple platforms. Declarative, reusable models capture relevant aspects of the behavior of simple devices (e.g. valves or thrusters). Reasoning algorithms combine device models to create a model of the system-wide interactions and behavior of a complex, unique artifact such as a spacecraft. Rather than requiring engineers to all possible interactions and failures at design time or perform analysis during the mission, the reasoning engine generates the appropriate response to the current situation, taking into account its system-wide knowledge, the current state, and even sensor failures or unexpected behavior.

Kurien, James A.↗

NASA NTRS2005

Maintaining Situation Awareness with Autonomous Airborne Observation Platforms

Unmanned Aerial Vehicles (UAVs) offer tremendous potential as intelligence, surveillance and reconnaissance (ISR) platforms for early detection of security threats and for acquisition and maintenance of situation awareness in crisis conditions. However, using their capabilities effectively requires addressing a range of practical and theoretical problems. The paper will describe progress by the "Autonomous Rotorcraft Project," a collaborative effort between NASA and the U.S. Army to develop a practical, flexible capability for UAV-based ISR. Important facets of the project include optimization methods for allocating scarce aircraft resources to observe numerous, distinct sites of interest; intelligent flight automation software than integrates high-level plan generation capabilities with executive control, failure response and flight control functions; a system architecture supporting reconfiguration of onboard sensors to address different kinds of threats; and an advanced prototype vehicle designed to allow large-scale production at low cost. The paper will also address human interaction issues including an empirical method for determining how to allocate roles and responsibilities between flight automation and human operations.

Freed, Michael↗

NASA NTRS2011

Integration of the Reconfigurable Self-Healing eDNA Architecture in an Embedded System

In this work we describe the first real world case study for the self-healing eDNA (electronic DNA) architecture by implementing the control and data processing of a Fourier Transform Spectrometer (FTS) on an eDNA prototype. For this purpose the eDNA prototype has been ported from a Xilinx Virtex 5 FPGA to an embedded system consisting of a PowerPC and a Xilinx Virtex 5 FPGA. The FTS instrument features a novel liquid crystal waveguide, which consequently eliminates all moving parts from the instrument. The addition of the eDNA architecture to do the control and data processing has resulted in a highly fault-tolerant FTS instrument. The case study has shown that the early stage prototype of the autonomous self-healing eDNA architecture is expensive in terms of execution time.

Computer architecture↗

NASA NTRS2013

NASA Technology Evaluation for Environmental Risk Mitigation Remediation Technology Collaboration Development

NASA is committed to finding solutions to agency cleanup problems that are better, cheaper, and more effective than the status quo. Unfortunately, some potential solutions involve innovative technologies for which NASA remediation managers may not have a high level of understanding or confidence. Since 2004, NASA's Stennis Space Center (SSC) in Mississippi has been pumping groundwater contaminated with trichloroethylene (TCE) and other halogenated volatile organic compounds (HVOC) from their cleanup location designated "Area G" through extraction wells to an aboveground treatment system. Over time, however, the effectiveness of this treatment strategy has diminished and an alternative approach is needed. In 2012, professionals from NASA's Principal Center for Technology Evaluation for Environmental Risk Mitigation (TEERM) introduced SSC managers to an innovative technology for enhancing the performance of SSC's existing pump and treat system. The technology, generally referred to as in situ chemical oxidation (ISCO), involves slowly and continuously injecting a strong but safe chemical oxidant into the groundwater. Treatment is enhanced by a "surfactant-type effect" which causes residual contamination from saturated soil to be released into the dissolved-phase where it can be readily oxidized. Any dissolved-phase contamination that was not oxidized can be collected by the extraction well network and treated aboveground. SSC was not familiar with the technology so to increase their confidence, TEERM identified a contractor who was willing to demonstrate their product and process at a significantly reduced price. An initial, small-scale demonstration of ISCO began at sse in March 2012 and completed in August 2012. This successful demonstration was followed by three larger-scale ISCO demonstrations between August and December 2012. The contractor's innovative Continuous Injection System (CIS) incorporated "green" and sustainable technologies and practices. A slow injection rate was maintained autonomously by the CIS, eliminating the need for multiple mobilizations of personnel and powered equipment. The CIS was calibrated to deliver only as much reagent as the formation would accept without "short circuiting", minimizing material waste. Public utility water pressure was used to mix, dilute, and inject the reagent. NASA personnel were trained to operate and maintain the system and remote monitoring and injection control capabilities were developed, further reducing the need for contractor mobilizations to the site. An integrated solar photovoltaic panel was used to power the control valves and web monitoring telemetry. SSC provided hydrogen peroxide for the process using their existing supplier for the aboveground pump and treat systems. The only consumable required from the contractor was their proprietary activator to catalyze SSC's peroxide.

Romeo, James↗

NASA NTRS2015

Towards an Open, Distributed Software Architecture for UxS Operations

To address the growing need to evaluate, test, and certify an ever expanding ecosystem of UxS platforms in preparation of cultural integration, NASA Langley Research Center's Autonomy Incubator (AI) has taken on the challenge of developing a software framework in which UxS platforms developed by third parties can be integrated into a single system which provides evaluation and testing, mission planning and operation, and out-of-the-box autonomy and data fusion capabilities. This software framework, named AEON (Autonomous Entity Operations Network), has two main goals. The first goal is the development of a cross-platform, extensible, onboard software system that provides autonomy at the mission execution and course-planning level, a highly configurable data fusion framework sensitive to the platform's available sensor hardware, and plug-and-play compatibility with a wide array of computer systems, sensors, software, and controls hardware. The second goal is the development of a ground control system that acts as a test-bed for integration of the proposed heterogeneous fleet, and allows for complex mission planning, tracking, and debugging capabilities. The ground control system should also be highly extensible and allow plug-and-play interoperability with third party software systems. In order to achieve these goals, this paper proposes an open, distributed software architecture which utilizes at its core the Data Distribution Service (DDS) standards, established by the Object Management Group (OMG), for inter-process communication and data flow. The design decisions proposed herein leverage the advantages of existing robotics software architectures and the DDS standards to develop software that is scalable, high-performance, fault tolerant, modular, and readily interoperable with external platforms and software.

Cross, Charles D.↗

NASA NTRS2018

Pre-Flight Training of Autonomic Responses for Mitigating the Effects of Spatial Disorientation During Spaceflight

The National Aeronautics and Space Administration (NASA) has identified a potential risk of spatial disorientation, motion sickness, and degraded performance to astronauts during re-entry and landing of the proposed Orion crew vehicle. The purpose of this study was to determine if a physiological training procedure, Autogenic-Feedback Training Exercise (AFTE), can mitigate these adverse effects. Fourteen men and six women were assigned to two groups (AFTE, no-treatment Control) matched for motion sickness susceptibility and gender. All subjects received a standard rotating chair test to determine motion sickness susceptibility; three training sessions on a manual performance task; and four exposures in the rotating chair (Orion tests) simulating angular accelerations of the crew vehicle during re-entry. AFTE subjects received 2 hours of training before Orion tests 2, 3, and 4. Motion sickness symptoms, task performance, and physiological measures were recorded on all subjects. Results showed that the AFTE group had significantly lower symptom scores when compared to Controls on test 2 (p=.05), test 3 (p=.03), and test 4 (p=.02). Although there were no significant group differences on task performance, trends showed that AFTE subjects were less impaired than Controls. Heart rate change scores (20 revolutions per minute minus baseline) of AFTE subjects indicated significantly less reactivity on Test 4 compared to Test 1 (10.09 versus 16.59, p=.02), while Controls did not change significantly across tests. Results of this study indicate that AFTE may be an effective countermeasure for mitigating spatial dis-orientation and motion sickness in astronauts.

Orion↗

NASA NTRS2015

Interfacing and Verifying ALHAT Safe Precision Landing Systems with the Morpheus Vehicle

The NASA Autonomous precision Landing and Hazard Avoidance Technology (ALHAT) project developed a suite of prototype sensors to enable autonomous and safe precision landing of robotic or crewed vehicles under any terrain lighting conditions. Development of the ALHAT sensor suite was a cross-NASA effort, culminating in integration and testing on-board a variety of terrestrial vehicles toward infusion into future spaceflight applications. Terrestrial tests were conducted on specialized test gantries, moving trucks, helicopter flights, and a flight test onboard the NASA Morpheus free-flying, rocket-propulsive flight-test vehicle. To accomplish these tests, a tedious integration process was developed and followed, which included both command and telemetry interfacing, as well as sensor alignment and calibration verification to ensure valid test data to analyze ALHAT and Guidance, Navigation and Control (GNC) performance. This was especially true for the flight test campaign of ALHAT onboard Morpheus. For interfacing of ALHAT sensors to the Morpheus flight system, an adaptable command and telemetry architecture was developed to allow for the evolution of per-sensor Interface Control Design/Documents (ICDs). Additionally, individual-sensor and on-vehicle verification testing was developed to ensure functional operation of the ALHAT sensors onboard the vehicle, as well as precision-measurement validity for each ALHAT sensor when integrated within the Morpheus GNC system. This paper provides some insight into the interface development and the integrated-systems verification that were a part of the build-up toward success of the ALHAT and Morpheus flight test campaigns in 2014. These campaigns provided valuable performance data that is refining the path toward spaceflight infusion of the ALHAT sensor suite.

Carson, John M., III↗

DOE OSTI2018

sUAS Support for Mars 2020

The release of airborne radioactive material presents a health risk hazard to many individuals, including emergency responders and the public. Characterizing the unknown radioactive dangers produced during such incidents is essential. An advantage to utilizing unmanned aerial systems in this effort is the reduction of risk to personnel otherwise tasked with characterization, as well as more quickly obtaining data points during cloud immersion. By pairing a continuous air monitor (CAM) and detector with a drone, quantification of unknown material in the plume can be determined, and thus the extent of dose to people in the area can be estimated. A small, low-flow air sampler with a Geiger-Mueller counter may be characterized using experimental measurements of point sources representing a cloud of material and modelled using the Monte Carlo N-Particle Transport Code (MCNP), a software package for simulating nuclear processes, to find the usefulness and advantages of the system for detection of nuclides of concern in various nuclear plume scenarios. The flying time of small-unmanned aircraft systems (sUASs) is limited; thus, the minimum detectable activity and concentration rates possible must be determined over the system’s window of operation. While the activity concentrations corresponding to external and internal doses of concern can be detected with certainty for 90 Sr and 137 Cs in a plume, those corresponding to 238 Pu are more difficult to detect. The central principle of employing the sUAS is that the cockpit does not have an operator onboard the aircraft; therefore, control of the aircraft must take place by other means. With a sUAS, command and control can be separated into three distinct methods: (1) ground control or remote piloting, (2) semi-autonomous control, and (3) autonomous control. The isotope 238 Pu is used in the space industry, providing long-lived heat generation for fuel in outer space (NASA 2014). Due to the inherent risks with rocket launches to get objects into space, monitoring for release of these hazardous substances is a major undertaking. The current means is through employment of environmental CAMs. It is conceivable, however, that drone monitoring for release of 238 Pu in the event of a space launch mishap would give a greater chance of detection of plutonium particulate, because the particulate’s diffusion in air upon settling to the ground would make the probability of collecting a particle on a filter in a CAM very low.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Formation and reconfiguration of tight multi-lane platoons

Advances in vehicular communication technologies are expected to facilitate cooperative driving in the future. Connected and Automated Vehicles (CAVs) are able to collaboratively plan and execute driving maneuvers by sharing their perceptual knowledge and future plans. In this paper, an architecture for autonomous navigation of tight multi-lane platoons traveling on public roads is presented. Using the proposed approach, CAVs are able to form single or multi-lane platoons of various geometrical configurations. They are able to reshape and adjust their configurations according to changes in the environment. The proposed architecture consists of two main components: an offline motion planner system and an online hierarchical control system. The motion planner uses an optimization-based approach for cooperative formation and reconfiguration in tight spaces. A constrained optimization scheme is used to plan smooth, dynamically feasible and collision-free trajectories for all the vehicles within the platoon. The paper addresses online computation limitations by employing a family of maneuvers precomputed offline and stored on a look-up table on the vehicles. The online hierarchical control system is composed of three levels: a traffic operation system (TOS), a decision-maker, and a path-follower. The TOS determines the desired platoon reconfiguration. The decision-maker checks the feasibility of the reconfiguration plan based on real-time information about the surrounding traffic. The reconfiguration maneuver is executed by a low-level path-following feedback controller in real-time. The effectiveness of the approach is demonstrated through simulations of three case studies: (1) formation reconfiguration (2) obstacle avoidance, and (3) benchmarking against behavior-based planning in which the desired formation is achieved using a sequence of motion primitives.

42 ENGINEERING↗