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Results for “Human Performance Manual”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Telerobotics for Human Exploration: Enhancing Crew Capabilities in Deep Space

Future space missions in Earth orbit, to the Moon, and to other distant destinations offer many new opportunities for exploration. But, astronaut time will always be limited and some work will not be feasible or efficient for humans to perform manually. Telerobots, however, can complement human explorers, performing work under remote control from Earth, orbit or nearby habitats. A central challenge, therefore, is to understand how humans and remotely operated robots can be jointly employed to maximize mission performance and success. This presentation provides an overview of the key issues with using telerobots for human exploration.

telerobotics↗
NASA NTRS1984

The Effect of Part-simulation of Weightlessness on Human Control of Bilateral Teleoperation: Neuromotor Considerations

The effect of weightlessness on the human operator's performance in force reflecting position control of remote manipulators was investigated. A gravity compensation system was developed to simulate the effect of weightlessness on the operator's arm. A universal force reflecting hand controller (FRHC) and task simulation software were employed. Two experiments were performed because of anticipated disturbances in neuromotor control specification on the human operator in an orbital control environment to investigate: (1) the effect of controller stiffness on the attainment of a learned terminal position in the three dimensional controller space, and (2) the effect of controller stiffness and damping on force tracking of the contour of a simulated three dimensional cube using the part simulation of weightless conditions. The results support the extension of neuromotor control models, which postulate a stiffness balance encoding of terminal position, to three dimensional motion of a multilink system, confirm the existence of a disturbance in human manual control performance under gravity compensated conditions, and suggest techniques for compensation of weightlessness induced performance decrement through appropriate specification of hand controller response characteristics. These techniques are based on the human control model.

Corker, K.↗
NASA NTRS1966

Two-dimensional manual control systems

Experiments to determine necessary modifications to current models of human controller of single variable systems to make them representative of controller in two variable situations

MATHEMATICAL MODEL↗
NASA NTRS1977

Multi-attribute subjective evaluations of manual tracking tasks vs. objective performance of the human operator

A computational method to deal with the multidimensional nature of tracking and/or monitoring tasks is developed. Operator centered variables, including the operator's perception of the task, are considered. Matrix ratings are defined based on multidimensional scaling techniques and multivariate analysis. The method consists of two distinct steps: (1) to determine the mathematical space of subjective judgements of a certain individual (or group of evaluators) for a given set of tasks and experimental conditionings; and (2) to relate this space with respect to both the task variables and the objective performance criteria used. Results for a variety of second-order trackings with smoothed noise-driven inputs indicate that: (1) many of the internally perceived task variables form a nonorthogonal set; and (2) the structure of the subjective space varies among groups of individuals according to the degree of familiarity they have with such tasks.

Siapkaras, A.↗
NASA NTRS2012

Automated Lab-on-a-Chip Electrophoresis System

Capillary electrophoresis is an analytical technique that can be used to detect and quantify extremely small amounts of various biological molecules. In the search for biochemical traces of life on other planets, part of this search involves an examination of amino acids, which are the building blocks of life on Earth. The most sensitive method for detecting amino acids is the use of laser induced fluorescence. However, since amino acids do not, in general, fluoresce, they first must be reacted with a fluorescent dye label prior to analysis. After this process is completed, the liquid sample then must be transported into the electrophoresis system. If the system is to be reused multiple times, samples must be added and removed each time. In typical laboratories, this process is performed manually by skilled human operators using standard laboratory equipment. This level of human intervention is not possible if this technology is to be implemented on extraterrestrial targets. Microchip capillary electrophoresis (CE) combined with laser induced fluorescence detection (LIF) was selected as an extremely sensitive method to detect amino acids and other compounds that can be tagged with a fluorescent dye. It is highly desirable to package this technology into an integrated, autonomous, in situ instrument capable of performing CE-LIF on the surface of an extraterrestrial body. However, to be fully autonomous, the CE device must be able to perform a large number of sample preparation and analysis operations without the direct intervention of a human.

Willis, Peter A.↗
DOE OSTI2025

Improving Cyber Situational Understanding

Effective cybersecurity operations require the ability to analyze large amounts of information to assess security risks and formulate defensive strategies against adversaries. This has become more complex in recent years as the sprawl and interconnectivity of devices grows through implementation of virtualization, cloud computing, and Internet of Things (IoT). The amount of data and analysis required for effective cybersecurity command and control decisions far exceeds humans’ capacity to perform manually. We characterize the analysis problem as cyber situational understanding. The research presented to improve cyber situational understanding focuses on vulnerability analysis and threat intelligence. Regarding vulnerabilities, entities must analyze and plan work for between thousands and tens of thousands of software vulnerabilities annually. Entities heavily use network firewalls to limit vulnerability exposure. As a result, some of these vulnerabilities permit exposure to adversarial exploitation, whereas others are inaccessible and therefore present negligible risk of exploitation. Distinguishing between high and low risk software vulnerabilities requires a deep understanding of the vulnerability, network firewall protection, and characteristics of the targeted device. This problem is solved by extracting network service features from vulnerability data features using both machine-learning and natural language processing. Then, the network firewall topology is parsed to determine which vulnerabilities are reachable by adversaries. Ultimately, a state-based safety analysis ascertains which vulnerabilities are unsafe. A related vulnerability analysis problem occurs in cybersecurity operations when associating an entity’s hardware and software assets to public vulnerability databases. Assets often reveal hardware and software through installation artifacts and network service identification, and entities store these artifacts in inventory databases. However, software and hardware vendors apply a standard Common Platform Enumeration (CPE) naming convention when publicly reporting vulnerabilities. Associating these two datasets often requires many hours to days of manual inspection. The proposed solution automates the mapping approach of human analysts using fuzzy matching techniques, natural language processing, and, ultimately, machine learning to present a small set of recommendations for mapping the two datasets. The result significantly reduces human analysis time and reduces the occurrence of false positives in vulnerability notifications. Finally, cyber threat intelligence (CTI) requires associating cyber observable artifacts, such as IP addresses, URIs, and file hashes, with cyber threat tactics, techniques, and procedures. Unfortunately, most CTI data is compartmentalized across multiple organizations and cannot be shared due to the legal and reputational risk with cyber threat being associated with the entity. The approach to solving this problem inovlves using a distributed ledger with anonymous token spending and authentication. This allows a consortium of semi-trusted entities to share the workload of curating CTI for a threat sharing community’s cooperative benefit.

Huff, Philip↗
NASA NTRS2017

Effects of Retinal Eccentricity on Human Manual Control

This study investigated the effects of viewing a primary flight display at different retinal eccentricities on human manual control behavior and performance. Ten participants performed a pitch tracking task while looking at a simplified primary flight display at different horizontal and vertical retinal eccentricities, and with two different controlled dynamics. Tracking performance declined at higher eccentricity angles and participants behaved more nonlinearly. The visual error rate gain increased with eccentricity for single-integrator-like controlled dynamics, but decreased for double-integrator-like dynamics. Participants' visual time delay was up to 100 ms higher at the highest horizontal eccentricity compared to foveal viewing. Overall, vertical eccentricity had a larger impact than horizontal eccentricity on most of the human manual control parameters and performance. Results might be useful in the design of displays and procedures for critical flight conditions such as in an aerodynamic stall.

system identification↗
NASA NTRS2016

Performance of an Automated System for Control of Traffic in Terminal Airspace

This paper examines the performance of a system that performs automated conflict resolution and arrival scheduling for aircraft in the terminal airspace around major airports. Such a system has the potential to perform separation assurance and arrival sequencing tasks that are currently handled manually by human controllers. The performance of the system is tested against several simulated traffic scenarios that are characterized by the rate at which air traffic is metered into the terminal airspace. For each traffic scenario, the levels of performance that are examined include: number of conflicts predicted to occur, types of resolution maneuver used to resolve predicted conflicts, and the amount of delay for all flights. The simulation results indicate that the percentage of arrivals that required a maneuver that changes the flight's horizontal route ranged between 11% and 15% in all traffic scenarios. That finding has certain implications if this automated system were to be implemented simply as a decision support tool. It is also found that arrival delay due to purely wake vortex separation requirements on final approach constituted only between 29% and 35% of total arrival delay, while the remaining major portion of it is mainly due to delay back propagation effects.

air traffic control↗
NASA NTRS2020

Fit2Fly: A Proof of Concept for Testing the Commercial Feasibility of Unmanned Aerial System Operations

As autonomous Unmanned Aerial Systems (UAS) become more prevalent, improvements in airworthiness assessments, data security, establishing vehicle trust, and more will become necessary to make fleet operations of these systems routine. Currently, these are verified for every UAS vehicle through a time-intensive manual inspection performed by human individuals. This process becomes infeasible when introduced into large-scale operations, so the Fit2Fly project is attempting to address these concerns. Fit2Fly is a multi-year project with a large scope, so we chose to narrow our focus to building a proof-of-concept feasibility simulation in tandem with physical UAS demonstration. This work resulted in a software simulation capable of running asynchronous commercial operations with persistent data modeling in coordination with several autonomous drones using integrated radio and GPS configurations.

Ryan Bonk↗
NASA NTRS1966

Preview control behavior and optimal control norms

Model based on optimal control theory for characterizing human operator in preview control task to provide reference frame for studying performance value and learning in manual control

HUMAN PERFORMANCE↗