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At least 649 records · Page 36

Working and Learning with Knowledge in the Lobes of a Humanoid's Mind

Humanoid class robots must have sufficient dexterity to assist people and work in an environment designed for human comfort and productivity. This dexterity, in particular the ability to use tools, requires a cognitive understanding of self and the world that exceeds contemporary robotics. Our hypothesis is that the sense-think-act paradigm that has proven so successful for autonomous robots is missing one or more key elements that will be needed for humanoids to meet their full potential as autonomous human assistants. This key ingredient is knowledge. The presented work includes experiments conducted on the Robonaut system, a NASA and the Defense Advanced research Projects Agency (DARPA) joint project, and includes collaborative efforts with a DARPA Mobile Autonomous Robot Software technical program team of researchers at NASA, MIT, USC, NRL, UMass and Vanderbilt. The paper reports on results in the areas of human-robot interaction (human tracking, gesture recognition, natural language, supervised control), perception (stereo vision, object identification, object pose estimation), autonomous grasping (tactile sensing, grasp reflex, grasp stability) and learning (human instruction, task level sequences, and sensorimotor association).

Ambrose, Robert↗

The Ocean Colour Climate Change Initiative: II. Spatial and Temporal Homogeneity of Satellite Data Retrieval Due to Systematic Effects in Atmospheric Correction Processors

The established procedure to access the quality of atmospheric correction processors and their underlying algorithms is the comparison of satellite data products with related in-situ measurements. Although this approach addresses the accuracy of derived geophysical properties in a straight forward fashion, it is also limited in its ability to catch systematic sensor and processor dependent behaviour of satellite products along the scan-line, which might impair the usefulness of the data in spatial analyses. The Ocean Colour Climate Change Initiative (OC-CCI) aims to create an ocean colour dataset on a global scale to meet the demands of the ecosystem modelling community. The need for products with increasing spatial and temporal resolution that also show as little systematic and random errors as possible, increases. Due to cloud cover, even temporal means can be influenced by along-scanline artefacts if the observations are not balanced and effects cannot be cancelled out mutually. These effects can arise from a multitude of results which are not easily separated, if at all. Among the sources of artefacts, there are some sensor-specific calibration issues which should lead to similar responses in all processors, as well as processor-specific features which correspond with the individual choices in the algorithms. A set of methods is proposed and applied to MERIS data over two regions of interest in the North Atlantic and the South Pacific Gyre. The normalised water leaving reflectance products of four atmospheric correction processors, which have also been evaluated in match-up analysis, is analysed in order to find and interpret systematic effects across track. These results are summed up with a semi-objective ranking and are used as a complement to the match-up analysis in the decision for the best Atmospheric Correction (AC) processor. Although the need for discussion remains concerning the absolutes by which to judge an AC processor, this example demonstrates clearly, that relying on the match-up analysis alone can lead to misjudgement.

Ocean Colour↗

Objective Assessment Method for RNAV STAR Adherence

Flight crews and air traffic controllers have reported many safety concerns regarding area navigation standard terminal arrival routes (RNAV STARs). Specifically, optimized profile descents (OPDs). However, our information sources to quantify these issues are limited to subjective reporting and time consuming case-by-case investigations. This work is a preliminary study into the objective performance of instrument procedures and provides a framework to track procedural concepts and assess design specifications. We created a tool and analysis methods for gauging aircraft adherence as it relates to RNAV STARs. This information is vital for comprehensive understanding of how our air traffic behaves. In this study, we mined the performance of 24 major US airports over the preceding three years. Overlaying 4D radar track data onto RNAV STAR routes provided a comparison between aircraft flight paths and the waypoint positions and altitude restrictions. NASA Ames Supercomputing resources were utilized to perform the data mining and processing. We assessed STARs by lateral transition path (full-lateral), vertical restrictions (full-lateral/full-vertical), and skipped waypoints (skips). In addition, we graphed frequencies of aircraft altitudes relative to the altitude restrictions. Full-lateral adherence was always greater than Full-lateral/ full- vertical, as it is a subset, but the difference between the rates was not consistent. Full-lateral/full-vertical adherence medians of the 2016 procedures ranged from 0% in KDEN (Denver) to 21% in KMEM (Memphis). Waypoint skips ranged from 0% to nearly 100% for specific waypoints. Altitudes restrictions were sometimes missed by systematic amounts in 1,000 ft. increments from the restriction, creating multi-modal distributions. Other times, altitude misses looked to be more normally distributed around the restriction. This tool may aid in providing acceptability metrics as well as risk assessment information.

Stewart, Michael↗

RNAV STAR Procedural Adherence

Flight crews and air traffic controllers have reported many safety concerns regarding area navigation standard terminal arrival routes (RNAV STARs). However, our information sources to quantify these issues are limited to subjective reporting and time consuming case-by-case investigations. This work is a preliminary study into the objective performance of instrument procedures and provides a framework to track procedural concepts and assess design functionality. We created a tool and analysis methods for gauging aircraft adherence as it relates to RNAV STARs. This information is vital for comprehensive understanding of how our air traffic behaves. In this exploratory archival study, we mined the performance of 24 major US airports over the preceding three years. Overlaying radar track data on top of RNAV STAR routes provided a comparison between aircraft flight paths and the waypoint positions and altitude restrictions. NASA Ames Supercomputing resources were utilized to perform the data mining and processing. We assessed STARs by lateral transition path (full-lateral), vertical restrictions (full-lateralfull-vertical), and skipped waypoints (skips). In addition, we graphed aircraft altitudes relative to the altitude restrictions and their occurrence rates. Full-lateral adherence was generally greater than Full-lateralfull-vertical, but the difference between the rates was not always consistent. Full-lateralfull-vertical adherence medians of the 2016 procedures ranged from 0 in KDEN (Denver) to 21 in KMEM (Memphis). Waypoint skips ranged from 0 to nearly 100 for specific waypoints. Altitudes restrictions were sometimes missed by systematic amounts in 1000 ft. increments from the restriction, creating multi-modal distributions. Other times, altitude misses looked to be more normally distributed around the restriction. This tool may aid in providing acceptability metrics as well as risk assessment information.

rnav↗

Evaluating Lunar Descent and Landing Performance From a Near Rectilinear Halo Orbit Using Linear Covariance Resetting Techniques

Upcoming lunar programs are striving the achieve precision landing in a safe and robust manner. Various elements impact this mission objective ranging from on-orbit operations with ground station tracking to incorporating relative sensors with hazard detection and avoidance (HDA) to support the final approach and landing phase. Modeling the impacts of ground tracking, trajectory replanning, relative navigation sensors, and particularly a potential HDA system on the integrated closed-loop GN\&C system performance poses a unique challenge due to the complexity and interaction with multiple facets of the vehicle including the trajectory design, sensing hardware, navigation system, guidance and targeting, and the overall mission concept of operations. This paper outlines techniques to systematically analyze and compare the performance impacts of ground tracking and replanning and an HDA system where the onboard navigation errors are reset or uploaded from an external source and the vehicle's reference trajectory is regenerated requiring the system dispersions to also be reset to reflect this in-flight profile adjustment. To illustrate the application of these general techniques for analyzing the performance impacts due to incorporating these resetting events, they are demonstrated with a human lunar descent and landing scenario starting from a near rectilinear halo orbit (NRHO) until the vehicle precisely reaches its predetermined landing site on the lunar surface. Performance metrics such as inertial and relative navigation errors, trajectory dispersions, footprint dispersions, and propellant usage are provided.

GN&C↗

BioSentinel: NASA’s First Deep Space Biological Mission

Since Apollo 17 in 1972, NASA has sent no humans or other biological organisms outside of Earth’s protective magnetosphere. NASA’s current Artemis program plans to put astronauts back on the Moon and eventually land human missions on Mars. One of the major challenges to long-duration crewed travel and habitation in deep space is an in-depth understanding of the biological effects of space radiation, often convoluted by the impact of reduced gravity. Such missions will require significant countermeasures, likely both technological and biomedical, to protect organisms from chronic radiation exposure. Small satellite missions like CubeSats can inform these countermeasures by investigating model organisms in relevant space environments. The BioSentinel mission is comprised of four segments developed at NASA Ames Research Center: a 6U CubeSat (1U = 10-cm cube), an ISS payload launched in December 2021 and two ground units, one for the mission’s CubeSat and one for the ISS payload. The last three segments have been operational since January 2022 and serve as experimental controls. BioSentinel’s 6U CubeSat is planned to launch as a secondary payload on the Artemis-1 rocket. It will be deployed on a lunar fly-by trajectory and into a heliocentric orbit. BioSentinel will be the first interplanetary satellite to study the biological response to space radiation outside Low Earth Orbit (LEO) in almost 50 years. BioSentinel is a complete, autonomous spacecraft capable of conducting experiments in deep space. Its 4U BioSensor payload is a fully automated and adaptable platform that can perform biological measurements with a range of microorganisms in multiple space environments, including the ISS, free flyers, and other platforms like the Lunar Gateway and lander vehicles. Once it reaches its orbit, BioSentinel’s CubeSat will measure the DNA damage response to ambient radiation in a model organism, the budding yeast Saccharomyces cerevisiae, which will be compared to information provided by an onboard radiation sensor and to data obtained in LEO (on ISS) and on Earth. Once in interplanetary space, fluidic cards containing desiccated yeast will be activated by growth medium addition at different time points throughout the mission. Growth and metabolic activity will be tracked continuously via optical measurements. This paper describes BioSentinel’s objectives, science, data management, and preliminary results from the ISS and ISS ground control segments.

BioSentinel↗

BioSentinel: NASA’s First Deep Space Biological Mission

Since Apollo 17 in 1972, NASA has sent no humans or other biological organisms outside of Earth’s protective magnetosphere. NASA’s current Artemis program plans to put astronauts back on the Moon and eventually land human missions on Mars. One of the major challenges to long-duration crewed travel and habitation in deep space is an in-depth understanding of the biological effects of space radiation, often convoluted by the impact of reduced gravity. Such missions will require significant countermeasures, likely both technological and biomedical, to protect organisms from chronic radiation exposure. Small satellite missions like CubeSats can inform these countermeasures by investigating model organisms in relevant space environments. The BioSentinel mission is comprised of four segments developed at NASA Ames Research Center: a 6U CubeSat (1U = 10-cm cube), an ISS payload launched in December 2021 and two ground units, one for the mission’s CubeSat and one for the ISS payload. The last three segments have been operational since January 2022 and serve as experimental controls. BioSentinel’s 6U CubeSat is planned to launch as a secondary payload on the Artemis-1 rocket. It will be deployed on a lunar fly-by trajectory and into a heliocentric orbit. BioSentinel will be the first interplanetary satellite to study the biological response to space radiation outside Low Earth Orbit (LEO) in almost 50 years. BioSentinel is a complete, autonomous spacecraft capable of conducting experiments in deep space. Its 4U BioSensor payload is a fully automated and adaptable platform that can perform biological measurements with a range of microorganisms in multiple space environments, including the ISS, free flyers, and other platforms like the Lunar Gateway and lander vehicles. Once it reaches its orbit, BioSentinel’s CubeSat will measure the DNA damage response to ambient radiation in a model organism, the budding yeast Saccharomyces cerevisiae, which will be compared to information provided by an onboard radiation sensor and to data obtained in LEO (on ISS) and on Earth. Once in interplanetary space, fluidic cards containing desiccated yeast will be activated by growth medium addition at different time points throughout the mission. Growth and metabolic activity will be tracked continuously via optical measurements. This paper describes BioSentinel’s objectives, science, data management, and preliminary results from the ISS segment.

BioSentinel↗

ELECTRON SHOWER RECONSTRUCTION IN THE ICARUS EXPERIMENT

This dissertation presents a study in the field of neutrino physics. Neutrinos are fundamental particles that are electrically neutral and have extremely small mass, allowing them to traverse matter with very little interaction. Because of this property, neutrinos are exceptionally difficult to detect. Nevertheless, understanding their behavior is essential for addressing fundamental questions about the origin of the Universe and the properties of matter. This work focuses on the reconstruction of electron showers produced by interactions of electron neutrinos (𝜈𝑒) in the ICARUS experiment, located at the Fermi National Accelerator Laboratory in the United States. ICARUS employs a liquid argon time projection chamber detector, which is capable of recording with high precision the tracks left by particles produced in neutrino interactions. The main objective of this research is to improve the reconstruction algorithms and techniques used to identify and characterize these electron showers, enhancing metrics such as completeness, defined as the fraction of correctly reconstructed signals, and purity, which quantifies how much of the reconstructed signal truly belongs to the candidate event. These improvements are crucial for reducing false positives and increasing the accuracy of electron photon discrimination. Consequently, this work directly contributes to improved neutrino oscillation analyses and to a deeper understanding of neutrino properties.

Salmoria, Gabrieli [Parana Tech. Fed. U., Toledo]↗

A stochastic optimal feedforward and feedback control methodology for superagility

A new control design methodology is developed: Stochastic Optimal Feedforward and Feedback Technology (SOFFT). Traditional design techniques optimize a single cost function (which expresses the design objectives) to obtain both the feedforward and feedback control laws. This approach places conflicting demands on the control law such as fast tracking versus noise atttenuation/disturbance rejection. In the SOFFT approach, two cost functions are defined. The feedforward control law is designed to optimize one cost function, the feedback optimizes the other. By separating the design objectives and decoupling the feedforward and feedback design processes, both objectives can be achieved fully. A new measure of command tracking performance, Z-plots, is also developed. By analyzing these plots at off-nominal conditions, the sensitivity or robustness of the system in tracking commands can be predicted. Z-plots provide an important tool for designing robust control systems. The Variable-Gain SOFFT methodology was used to design a flight control system for the F/A-18 aircraft. It is shown that SOFFT can be used to expand the operating regime and provide greater performance (flying/handling qualities) throughout the extended flight regime. This work was performed under the NASA SBIR program. ICS plans to market the software developed as a new module in its commercial CACSD software package: ACET.

Halyo, Nesim↗

Cybersecurity Workforce Training for SMR Integration into Distribution Grids: A Competency Framework and Containerized Hands-On Lab for the SMR/DER/Microgrid Boundary

Small modular reactors (SMRs) and microreactors are entering the U.S. distribution grid as synchronous generation on feeders designed for loads and inverter-based distributed energy resources (DERs). No existing cybersecurity training program addresses this intersection of nuclear operations, DER management, and operational technology security. As subcontractor to Iowa State University on the CyDERMS Center, Argonne analyzed the relevant standards and training landscape, translated the resulting gaps into a twelve-objective competency framework across distribution-operator and graduate-analyst role tracks, and built a containerized training lab using a ∼400-bus composite grid model behind a realistically simulated Modbus TCP SCADA stack. The analysis isolates the balance-of-plant / energy-management-system (BOP/EMS) boundary as the critical jurisdictional seam where, as of March 2026, neither NRC nor NERC CIP cleanly claims cybersecurity responsibility for distribution-connected SMRs. The framework maps each objective across NIST CSF 2.0, ISA/IEC 62443, NIST NICE Task–Knowledge–Skill statements, and NRC RG 5.71 awareness-and-training controls. The training lab implements operator-recognition assessment scenarios spanning grid-side disturbances and telemetry-layer anomalies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Analysis of navigation performance for the Earth Observing System (EOS) using the TDRSS Onboard Navigation System (TONS)

Use of the Tracking and Data Relay Satellite System (TDRSS) Onboard Navigation System (TONS) was proposed as an alternative to the Global Positioning System (GPS) for supporting the Earth Observing System (EOS) mission. The results are presented of EOS navigation performance evaluation with respect to TONS based orbit, time, and frequency determination (OD/TD/FD). Two TONS modes are considered: one uses scheduled TDRSS forward link service to derive one way Doppler tracking data for OD/FD support (TONS-I); the other uses an unscheduled navigation beacon service (proposed for Advanced TDRSS) to obtain pseudorange and Doppler data for OD/TD/FD support (TONS-II). Key objectives of the analysis were to evaluate nominal performance and potential sensitivities, such as suboptimal tracking geometry, tracking contact scheduling, and modeling parameter selection. OD/TD/FD performance predictions are presented based on covariance and simulation analyses. EOS navigation scenarios and the contributions of principal error sources impacting performance are also described. The results indicate that a TONS mode can be configured to meet current and proposed EOS position accuracy requirements of 100 and 50 m, respectively.

Elrod, B.↗

Magnetospheric multiprobes: Investigations and instrumentation

The multiprobe scientific objectives are to: (1) determine the spatial structure of plasma phenomena such as the aurora, convection reversals, and ion troughs; (2) separate spatial and temporal variations in these phenomena; (3) determine field aligned current densities; (4) perform multiple point analysis of particle beams, wave fields, and plasma clouds that are injected into the ionosphere and magnetosphere by Spacelab active experiment facilities. Trade studies described include: instrument accommodations, power, attitude determination, electric field antennas, storage and ejection, thermal control, tracking communications, command and data management, payload and mission specialist support, functional objectives, and orbital analysis.

Burch, J. L.↗

End-to-End Pipeline for Trigger Detection on Hit and Track Graphs

There has been a surge of interest in applying deep learning in particle and nuclear physics to replace labor-intensive offline data analysis with automated online machine learning tasks. This paper details a novel AI-enabled triggering solution for physics experiments in Relativistic Heavy Ion Collider and future Electron-Ion Collider. The triggering system consists of a comprehensive end-to-end pipeline based on Graph Neural Networks that classifies trigger events versus background events, makes online decisions to retain signal data, and enables efficient data acquisition. Here, the triggering system first starts with the coordinates of pixel hits lit up by passing particles in the detector, applies three stages of event processing (hits clustering, track reconstruction, and trigger detection), and labels all processed events with the binary tag of trigger versus background events. By switching among different objective functions, we train the Graph Neural Networks in the pipeline to solve multiple tasks: the edge-level track reconstruction problem, the edge-level track adjacency matrix prediction, and the graph-level trigger detection problem. We propose a novel method to treat the events as track-graphs instead of hit-graphs. This method focuses on intertrack relations and is driven by underlying physics processing. As a result, it attains a solid performance (around 72% accuracy) for trigger detection and outperforms the baseline method using hit-graphs by 2% higher accuracy.

97 MATHEMATICS AND COMPUTING↗

Hydrated Interplanetary Dust Particles: Implications for Oxygen Reservoirs in the Outer Solar System

A re-evaluation of solar energetic particle (SEP) track densities in interplanetary dust particles (IDPs) show that many are derived from outer solar system parent bodies such as Kuiper belt objects (KBOs) or beyond. Kuiper belt objects are widely believed to represent the frozen remnants from the birth of the solar system. The population of track-rich IDPs include members from both the anhydrous chondritic-porous and hydrated chondritic-smooth classes and earlier work suggested that the hydrated IDPs may represent anhydrous IDP material that was aqueously altered. We are performing systematic studies of the mineralogy, chemistry and isotopic compositions of track-rich IDPs to gain a fuller understanding of the origin and evolution of KBOs. Here, we focus on the identification of hydrated Kuiper belt dust particles that allows for the direct evaluation of their O isotopic compositions and the implications for the oxygen isotopic composition of outer solar system ices.

L. P. Keller↗

On Harmonizing Today’s Regulated Tariffs and Future Dynamic Electricity Pricing

A novel method for harmonizing the advantages of dynamic retail electricity pricing with the protections of regulated electricity tariffs is discussed and demonstrated. The method socializes and protects customers from long-term locational price variability that is unfair to those customers who are, by no fault of their own, served at congested locations on a distribution system. However, the method preserves short-term (e.g., diurnal) price variability that might induce helpful, mitigative responses from retail electricity customers. Because the method causes actual price recovery to track a customer class’s approved, regulated price recovery, the method may remove regulators’ objections to dynamic electricity pricing and thereby hasten adoption of market-based retail electricity pricing and transactive energy systems.

Consumer protection, Demand response, Market resea↗

Intelligent Process Visualization through Nuclear Operation Process Modeling, Reasoning, and Object Detection from Field Videos (Final Report)

This report is a deliverable for the “Final Report” task of DOE NEET Project 19-16790, "Context-Aware Safety Information Display for Nuclear Field Workers." This project's overall goal is to test the hypothesis that integrating computer vision and process reasoning methods will enable proactive visualization of the safe operation and maintenance processes of Nuclear Power Plants (NPP) for field workers. Augmented Reality (AR) glasses adopting such proactive safety information visualization techniques can significantly increase personnel safety and reduce the NPP’s operating costs. The current practice of monitoring NPPs requires workers to switch between digital models, data, and physical workspaces in identifying relevant but potentially occluded objects and in assessing the risks of operation and maintenance processes. On the other hand, frequently changed field conditions require field workers to report to supervisors for real-time guidance. Such guidance is essential to ensure that changing conditions will not invalidate or endanger the work order and other ongoing processes that may jeopardize NPP operations. Additionally, incorrect recognition of equipment objects can result in communication errors and safety problems. AR techniques can assist engineers in viewing the physical workspaces with objects labeled with detailed operation procedures and safety reminders during field operations. The project team developed an “Intelligent Context-Aware Safety Information Display” (ICAD) for supporting Nuclear Power Plant (NPP) field workers in achieving safe and efficient execution of a series of operational tasks in uncertain and changing workspaces of an NPP. Before designing the ICAD-AR prototype, the project team synthesized NPP operational knowledge models through literature review studies, surveys, interviews with domain experts, and knowledge modeling. The project team conducted an extensive study of the operational procedures of various NPPs, and digital technologies that can support the safe and efficient execution of those procedures in different NPP operational contexts. This literature review helped the project team conduct surveys and interviews with nuclear engineers and field workers to identify three categories of information. The NPP knowledge modeling efforts reveal that the three categories of information identified have different levels of importance in a typical procedure of carrying out a series of tasks to achieve a specific NPP operation goal (e.g., shutdown, mode changes). These three categories of information include 1) Workspace dynamics – the changing spatial arrangements of workspaces, tools, protection equipment, and supporting materials, 2) Workflow prognostics – the dynamic dependencies between different parts of an NPP that functionally support and influence each other in terms of safety and efficiency, and 3) Hazards – objects and spaces that contain hazardous materials or physical conditions that can pose risks to workers or mechanical systems. The project team has profiled the importance levels of these categories of information into a knowledge model. This knowledge model specifies what types of information are more critical for a given task in a given workspace so that computers can automatically identify critical objects and sensors in a scene for delivering context-ware safety information to field workers through AR devices. Significant research development of this project results in technical research outcomes and a prototyping system that illustrates the technical feasibility of establishing an ICAD-AR system supporting the proactive safety information display for nuclear field workers. This final report summarizes the project team’s technological achievements in the past three years. Overall, the project team completed the development and integration of five techniques into a prototype ICAD Augmented Reality (ICAD-AR) system and demonstrated the developed system’s real-time execution in a mechanical room. The project team completed the analysis of using this prototype in other types of workspaces based on 3D image data and digital design models collected from two additional workspaces (a water treatment plant and a flow loop training facility). The integrated techniques include 1) Natural Language Processing (NLP) algorithms supporting the generation and updates of nuclear fieldwork process models based on text analysis of work packages and operation manuals; 2) sensor log analysis for predicting control actions in given sensor reading contexts; 3) computer vision algorithms for automatic localization and navigation of workers; 4) object detection algorithms for identifying task-related objects and correlated sensors for safety checking; 5) AR technique as a platform for supporting the integration. The testing results of these five techniques have shown that 1) the sensor log analysis model can predict the next control action with an accuracy of 0.883; 2) the trained natural language processing model can extract more than 80% of the critical information from paper-based procedures (PBPs); 3) the navigation algorithm with the integration of Visual Inertial Odometry (VIO) and Non-Recursive Bayesian Filter methods make operator’s trajectory estimation resilient to drift error; 4) the computer vision algorithm can detect task-specific and safety-critical objects with an average accuracy of 95.3%. The project team used work procedures collected from a flow loop training facility and two datasets collected from two mechanical rooms simulating the workspaces of NPPs to demonstrate the technical capabilities of the developed ICAD-AR prototype. The demonstration validated the technical feasibility of establishing the ICAD-AR system for nuclear field workers and identified the challenges in 1) automatic text analysis of work packages; 2) use of limited samples of sensor logs for predicting the proper timings of control actions; 3) reliably tracking workers and their task progress in mechanical rooms with many similar objects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Fast Vehicle Turning-Movement Counting using Localization-based Tracking

Despite the high utility of traffic volume and turning movement data, such data is still hard to come by for the vast majority of roadways and intersections in nearly ev- ery city. Edge computing devices offer a promising tool for recording turning movement data if lightweight algorithms can be designed to run in real-time with relatively modest computational complexity. To that end, this work presents Vehicle Turning-Movement Counting using Localization- based Tracking (LBT-Count). This method is fast because it never performs detection on a full frame. Instead, only a few portions of the image are cropped and used to de- tect objects within the frame. The method achieves com- petitive performance on the public evaluation server for Track 1 of the AI City Challenge (7th overall on the first 50% of data). Furthermore, we show that LBT-Count is 52% faster than an analogous counting algorithm utilizing a traditional tracking-by-detection framework on available challenge data.

42 ENGINEERING↗

Laser Solutions for Reducing the Environmental Risks Associated with Orbital Debris and Near Earth Objects

Increasing activity in space is gradually increasing the amount of orbital debris in low earth orbit. As the debris increases, the environmental risk (hypervelocity collisions) associated with spaceflight also increases. Debris larger than 10 cm can typically be detected and tracked sufficiently to allow risk avoidance to be achieved by maneuvering to safe distances. Risk reduction for objects smaller than I cm may be accomplished through shielding. However, intermediate sized debris remains a problem. A convenient risk reduction solution has been identified using modem laser technology. In this approach, a relatively low energy laser facility operating near e equator may significantly reduce the amount of intermediate sized debris (1 - 10 cm) in a few years of operation. A sufficiently intense laser pulse arriving at a debris objects surface will ablate a micro-thin layer of material. As this hot gas rapidly expands away from the object, a small change in momentum is imparted. The momentum change for one pulse is insignificant. However, since the laser can provide 10-1000 pulses per second over several minutes, the cumulative effect is substantive. The object's perigee may be lowered in this manner into atmosphere where it will be vaporized. This same technique may be employed on a larger scale for risk reduction in asteroids, meteoroids, and comets colliding with the Earth at hypervelocities.

Campbell, Jonathan W.↗