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At least 109 records · Page 6

An ISU study of asteroid mining

During the 1990 summer session of the International Space University, 59 graduate students from 16 countries carried out a design project on using the resources of near-earth asteroids. The results of the project, whose full report is now available from ISU, are summarized. The student team included people in these fields: architecture, business and management, engineering, life sciences, physical sciences, policy and law, resources and manufacturing, and satellite applications. They designed a project for transporting equipment and personnel to a near-earth asteroid, setting up a mining base there, and hauling products back for use in cislunar space. In addition, they outlined the needed precursor steps, beginning with expansion of present ground-based programs for finding and characterizing near-earth asteroids and continuing with automated flight missions to candidate bodies. (To limit the summer project's scope the actual design of these flight-mission precursors was excluded.) The main conclusions were that asteroid mining may provide an important complement to the future use of lunar resources, with the potential to provide large amounts of water and carbonaceous materials for use off earth. However, the recovery of such materials from presently known asteroids did not show an economic gain under the study assumptions; therefore, asteroid mining cannot yet be considered a prospective business.

Burke, J. D.↗

Proximity operations in space station environment

Viewgraphs on proximity operations in space station environment are presented. Topics covered include: automated flight; remote manual piloting; task requirements and constraints; problem formulation; and flight parameter flow/pilot interaction for proximity operations task.

Rhodes, Brandt↗

Application of Artificial Intelligence Techniques in Uninhabitated Aerial Vehicle Flight

This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA southeastern University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

Dufrene, Warren R., Jr.↗

Application of Artificial Intelligence Techniques in Uninhabited Aerial Vehicle Flight

This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA Southeastearn University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

Dufrene, Warren R., Jr.↗

Biocybernetic system evaluates indices of operator engagement in automated task

A biocybernetic system has been developed as a method to evaluate automated flight deck concepts for compatibility with human capabilities. A biocybernetic loop is formed by adjusting the mode of operation of a task set (e.g., manual/automated mix) based on electroencephalographic (EEG) signals reflecting an operator's engagement in the task set. A critical issue for the loop operation is the selection of features of the EEG to provide an index of engagement upon which to base decisions to adjust task mode. Subjects were run in the closed-loop feedback configuration under four candidate and three experimental control definitions of an engagement index. The temporal patterning of system mode switching was observed for both positive and negative feedback of the index. The indices were judged on the basis of their relative strength in exhibiting expected feedback control system phenomena (stable operation under negative feedback and unstable operation under positive feedback). Of the candidate indices evaluated in this study, an index constructed according to the formula, beta power/(alpha power + theta power), reflected task engagement best.

Cerebral Cortex/physiology↗

Orion Handling Qualities During ISS Rendezvous and Docking

The Orion spacecraft was designed to rendezvous with multiple vehicles in low earth orbit (LEO) and beyond. To perform the required rendezvous and docking task, Orion must provide enough control authority to perform coarse translational maneuvers while maintaining precision to perform the delicate docking corrections. While Orion has autonomous docking capabilities, it is expected that final approach and docking operations with the International Space Station (ISS) will initially be performed in a manual mode. A series of evaluations was conducted by NASA and Lockheed Martin at the Johnson Space Center to determine the handling qualities (HQ) of the Orion spacecraft during different docking and rendezvous conditions using the Cooper-Harper scale. This paper will address the specifics of the handling qualities methodology, vehicle configuration, scenarios flown, data collection tools, and subject ratings and comments. The initial Orion HQ assessment examined Orion docking to the ISS. This scenario demonstrates the Translational Hand Controller (THC) handling qualities of Orion. During this initial assessment, two different scenarios were evaluated. The first was a nominal docking approach to a stable ISS, with Orion initializing with relative position dispersions and a closing rate of approximately 0.1 ft/sec. The second docking scenario was identical to the first, except the attitude motion of the ISS was modeled to simulate a stress case ( 1 degree deadband per axis and 0.01 deg/sec rate deadband per axis). For both scenarios, subjects started each run on final approach at a docking port-to-port range of 20 ft. Subjects used the THC in pulse mode with cues from the docking camera image, window views, and range and range rate data displayed on the Orion display units. As in the actual design, the attitude of the Orion vehicle was held by the automated flight control system at 0.5 degree deadband per axis. Several error sources were modeled including Reaction Control System (RCS) jet angular and position misalignment, RCS thrust magnitude uncertainty, RCS jet force direction uncertainty due to self plume impingement, and Orion center of mass uncertainty.

Hart, Jeremy J.↗

Multi-Operator Multi-UAV (MOMU) Control: Exploring the Influence of Sensor Tools and Playbook Task Delegation

New concepts of operations for Unmanned Aerial Vehicles (UAVs) will require a change from the current 2:1 operator to vehicle crew configuration. One particular control paradigm, largely driven by logistics, manpower, and training burdens, as well as the desire to force multiply, involves a single operator simultaneously managing multiple UAVs. This mode of operations has shown to significantly increase cognitive workload and decrease situation awareness, as operators are required to simultaneously attend to multiple sources of information. One potential way to mitigate potential drawbacks of multi-vehicle control by a single operator is to migrate to a multi-operator multi-UAV (MOMU) crew configuration, whereby M operators control N (> M) vehicles. This type of crew configuration can be organized in several ways to dynamically manage cognitive workload, match operator qualifications and skills to mission requirements, increase utilization of available assets, and thereby achieve maximum force multiplication. The present experiment examined task performance in a simulated MOMU environment and evaluated the potential benefits of sensor management aids ("Tools") as well as integrated sensor and flight automation ("Plays") compared to a fully manual condition ("Manual"). Tools support the operator by facilitating rapid understanding and management of sensor information, while the Plays support the operator by offloading/automating subtasks. Six pairs of participants were recruited for this study and tasked with sharing a pool of UAVs in order to conduct reconnaissance, surveillance, and target acquisition (RSTA) missions in adjacent Areas of Operation (AOs). Participants were given four tasks to accomplish, in order of priority: 1) prosecute High Value Targets (HVTs); 2) identify / track targets (military vehicles); 3) identify / mark civilian vehicles; and 4) respond to chat messages. Performance on the mission tasks was measured in terms of accuracy and reaction time. A composite mission score was also calculated using a payoff matrix that weighted each task according to priority. The results indicate that Playbook demonstrated better performance overall with higher accuracy rates and the highest composite score compared to Tools and Manual. The implications of these results to supporting future MOMU concepts of operations is discussed.

Playbook↗

Assured Vehicle Automation 1 Sim - Results Outbrief

In early 2022, the Human Autonomy Teaming Lab (NASA Ames Research Center) conducted a manned, human-in-the-loop (HITL) simulation. This part-task HITL began the lab’s Hazard Perception and Avoidance (HPA) technical work under NASA’s Advanced Air Mobility (AAM), Automated Flight and Contingency Management (AFCM) Sub-Project. The results of that sim guided the objectives of the current study, which were to examine pilots’ use of the Airborne Collision Avoidance System (ACAS) rotorcraft variant (Xr) v2 in multiple phases of flight with two separate Xr Modes, fully leverage Xr v2 features (e.g., use radar altimeter data to inform low altitude Resolution Advisory [RA] behavior, utilize the ability to designate “terminal-area intruders,” and display airspeed-based Detect and Avoid [DAA] guidance), emulate a “Traffic Advisory” (TA), and present Xr in a higher-fidelity environment. Therefore, this study was conducted in the Vertical Motion Simulator, and the variables included Phase of Flight (En-route, Hover, and Approach) as well as ACAS Xr Mode (TA/RA and DAA). The data collected included response times, losses of well clear, and maneuver sizes and durations as well as subjective ratings like acceptability and usability. Additional details and future anticipations are also discussed.

air taxis↗

Hazard Perception & Avoidance (HPA), Assured Vehicle Automation 1 Simulation (AVA-1h) Results Outbrief

In late 2022, the Human Autonomy Teaming Lab (NASA Ames Research Center) conducted a manned, human-in-the-loop (HITL) simulation. This HITL was the lab’s second Hazard Perception and Avoidance (HPA) technical work under NASA’s Advanced Air Mobility (AAM), Automated Flight and Contingency Management (AFCM) Sub-Project. The goals were to assess detect and avoid technology for manned, electric vertical takeoff and landing (eVTOL) aircraft. This simulation tested Resolution Advisory (RA) responses and return-to-course (RTC) maneuvers for the second version of the Airborne Collision Avoidance System’s (ACAS) rotary-wing (Xr) variant. This was conducted at the center's Vertical Motion Simulator (VMS), on a motion-based platform, and was configured to fly eVTOL aircraft while maneuvering for intruding traffic. Variables for this study included ACAS Xr modes (i.e., TA/RA and DAA) and phases of flight (i.e., Cruise, Hover, and Approach). The data collected included response times, losses of well clear, and pilots' noncompliances to alerts and guidance as well as subjective ratings like acceptability and perceived workload. Additional details and future anticipations are also discussed.

ACAS Xr↗

Plant Disease Detection: Exploring Applications in Hyperspectral Imaging and Machine Learning for Agriculture

The threat of crop disease on food security and agriculture is projected to escalate, leading to reduced crop yields, global economic loss, and endangered food availability to vulnerable populations. Early identification of plant disease is crucial to combatting the crisis but traditional manual methods for disease detection are laborious and may miss early signs of infection. The proposed solution suggests equipping a drone with a hyperspectral camera to collect images and analyzing the data with neural networks trained to flag and classify infected plants. This approach offers a faster, more accurate, and potentially more cost-effective alternative to current practices. While the expensive and complex nature of hyperspectral imaging (HSI) may be an obstacle to the adoption of the drone, rapidly advancing technologies compounded with rental-based usage may make these tools simpler, cheaper, and more accessible to a wider audience. The research further discusses the potential for automated flight paths and the expansion of disease detection to a broader range of crops.

plant disease detection↗

Configuring the Orion Guidance, Navigation, and Control Flight Software for Automated Sequencing

The Orion Crew Exploration Vehicle is being designed with greater automation capabilities than any other crewed spacecraft in NASA s history. The Guidance, Navigation, and Control (GN&C) flight software architecture is designed to provide a flexible and evolvable framework that accommodates increasing levels of automation over time. Within the GN&C flight software, a data-driven approach is used to configure software. This approach allows data reconfiguration and updates to automated sequences without requiring recompilation of the software. Because of the great dependency of the automation and the flight software on the configuration data, the data management is a vital component of the processes for software certification, mission design, and flight operations. To enable the automated sequencing and data configuration of the GN&C subsystem on Orion, a desktop database configuration tool has been developed. The database tool allows the specification of the GN&C activity sequences, the automated transitions in the software, and the corresponding parameter reconfigurations. These aspects of the GN&C automation on Orion are all coordinated via data management, and the database tool provides the ability to test the automation capabilities during the development of the GN&C software. In addition to providing the infrastructure to manage the GN&C automation, the database tool has been designed with capabilities to import and export artifacts for simulation analysis and documentation purposes. Furthermore, the database configuration tool, currently used to manage simulation data, is envisioned to evolve into a mission planning tool for generating and testing GN&C software sequences and configurations. A key enabler of the GN&C automation design, the database tool allows both the creation and maintenance of the data artifacts, as well as serving the critical role of helping to manage, visualize, and understand the data-driven parameters both during software development and throughout the life of the Orion project.

Odegard, Ryan G.↗

Design and Testing of an Approach to Automated In-Flight Safety Risk Management for sUAS Operations

An onboard risk management automation design is presented based on run-time assurance principles, as well as the concept for In-Time Aviation Safety Management Systems (IASMS) as described by the National Academies. The automation is designed to operate independently of the autopilot and perform real-time risk assessment spanning multiple classes of hazards, predict constraint violations, and track autopilot states. In the event of elevated risk conditions or predicted constraint violations, the automation will select from a set of available contingencies and trigger autopilot mode changes if necessary to mitigate risk exposure. The onboard automation also informs the remote operator/pilot of what the independent monitor is observing and any contingency decisions or actions that may arise during flight. Details of an implementation of this design and results of verification and validation activities, as required to meet stringent NASA software and system assurance standards, are also presented. This includes simulation and flight testing using small unmanned aircraft systems.

Ersin Ancel↗

Flight Test Evaluation of Automation-Induced Oscillations

Flight-test systems analysis techniques are applied to the case of aircraft automation-induced oscillations(AIO). Emerging technological advancements in flight control automation and artificial intelligence have created a need for evaluating the age-old aerial phenomenon of undesired aircraft oscillations. This paper is an overview on the study of AIO as interactions between human pilot, software engineer, and vehicle dynamics(e.g., latency) with the presence of winds aloft. Flight-test evaluation included a broad, non-comprehensive theory on cyclical and non-cyclical oscillations and a preliminary evaluation of the ecosystem from software engineer, airspace architect, and human test pilot.

David Zahn↗

Simulation and analysis of image-based navigation system for rotorcraft low-altitude flight

The automation of helicopter NOE flight entails the modification of nominal trajectories on the basis of the detection and location of obstacles by means of onboard sensors. This process is presently studied using a sequence of images from a passive sensor mounted at the helicopter's center of gravity and oriented with the viewing axis along the rotorcraft's longitudinal body-axis. Three different Kalman filters are used to estimate the location of an object on the ground during the course of various simulated helicopter maneuvers; two of the three filters are found to yield good object location estimates.

Sridhar, Banavar↗

Terminal Area Procedures for Paired Runways

Parallel runway operations have been found to increase capacity within the National Airspace but poor visibility conditions reduce the use of these operations. The NextGen and SESAR Programs have identified the capacity benefits from increased use of closely-space parallel runway. Previous research examined the concepts and procedures related to parallel runways however, there has been no investigation of the procedures associated with the strategic and tactical pairing of aircraft for these operations. This simulation study developed and examined the pilot and controller procedures and information requirements for creating aircraft pairs for parallel runway operations. The goal was to achieve aircraft pairing with a temporal separation of 15s (+/- 10s error) at a coupling point that was about 12 nmi from the runway threshold. Two variables were explored for the pilot participants: two levels of flight deck automation (current-day flight deck automation and auto speed control future automation) as well as two flight deck displays that assisted in pilot conformance monitoring. The controllers were also provided with automation to help create and maintain aircraft pairs. Results show the operations in this study were acceptable and safe. Subjective workload, when using the pairing procedures and tools, was generally low for both controllers and pilots, and situation awareness was typically moderate to high. Pilot workload was influenced by display type and automation condition. Further research on pairing and off-nominal conditions is required however, this investigation identified promising findings about the feasibility of closely-spaced parallel runway operations.

Lozito, Sandra↗

Terminal Area Procedures for Paired Runways

Parallel Runway operations have been found to increase capacity within the National Airspace (NAS) however, poor visibility conditions reduce this capacity [1]. Much research has been conducted to examine the concepts and procedures related to parallel runways however, there has been no investigation of the procedures associated with the strategic and tactical pairing of aircraft for these operations. This study developed and examined the pilot and controller procedures and information requirements for creating aircraft pairs for parallel runway operations. The goal was to achieve aircraft pairing with a temporal separation of 15s(+/- 10s error) at a coupling point that is about 12 nmi from the runway threshold. Two variables were explored for the pilot participants: Two levels of flight deck automation (current-day flight deck automation, and a prototype future automation) as well as two flight deck displays that assisted in pilot conformance monitoring. The controllers were also provided with automation to help create and maintain aircraft pairs. Data showed that the operations in this study were found to be acceptable and safe. Workload when using the pairing procedures and tools was generally low for both controllers and pilots, and situation awareness (SA) was typically moderate to high. There were some differences based upon the display and automation conditions for the pilots. Future research should consider the refinement of the concepts and tools for pilot and controller displays and automation for parallel runway concepts.

Lozito, Sandy↗

An evaluation of flight path management automation in transport category aircraft

A desk-top simulation of a Boeing 757/767 Electronic Flight Instrumentation System (EFIS) and Control Display Unit (CDU) was used in an experiment to compare three modes of communication for the clearance amendment process: standard voice procedures, a textual delivery method, and a graphical delivery method. Eight qualified Boeing 757/767 pilots served as subjects. Each flew nine landing scenarios with three amendments given in each scenario. Both acceptable and unacceptable clearance amendments were presented in order to assess situational awareness. Times for comprehension and execution of the amendment were recorded along with workload ratings, responses to unacceptable amendments, and subjective impressions. The graphical mode was found to be superior in terms of the time measures and subjective ratings. No difference was found between the modes in the ability to detect unacceptable clearances.

Chandra, D.↗