Search NASA⌕ Search

SEARCH · Search NASA

Results for “Unmanned”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

An Evaluation of Detect and Avoid (DAA) Displays for Unmanned Aircraft Systems: The Effect of Information Level and Display Location on Pilot Performance

A consortium of government, industry and academia is currently working to establish minimum operational performance standards for Detect and Avoid (DAA) and Control and Communications (C2) systems in order to enable broader integration of Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS). One subset of these performance standards will need to address the DAA display requirements that support an acceptable level of pilot performance. From a pilot's perspective, the DAA task is the maintenance of self separation and collision avoidance from other aircraft, utilizing the available information and controls within the Ground Control Station (GCS), including the DAA display. The pilot-in-the-loop DAA task requires the pilot to carry out three major functions: 1) detect a potential threat, 2) determine an appropriate resolution maneuver, and 3) execute that resolution maneuver via the GCS control and navigation interface(s). The purpose of the present study was to examine two main questions with respect to DAA display considerations that could impact pilots' ability to maintain well clear from other aircraft. First, what is the effect of a minimum (or basic) information display compared to an advanced information display on pilot performance? Second, what is the effect of display location on UAS pilot performance? Two levels of information level (basic, advanced) were compared across two levels of display location (standalone, integrated), for a total of four displays. The authors propose an eight-stage pilot-DAA interaction timeline from which several pilot response time metrics can be extracted. These metrics were compared across the four display conditions. The results indicate that the advanced displays had faster overall response times compared to the basic displays, however, there were no significant differences between the standalone and integrated displays. Implications of the findings on understanding pilot performance on the DAA task, the development of DAA display performance standards, as well as the need for future research are discussed.

detect and avoid↗
NASA NTRS2015

Identification of Human Factors in Unmanned Aviation Via Pilot Incident Reports

There is a need for incident data relevant to the operation of civilian unmanned aircraft systems (UAS) in the National Air Space (NAS). Currently, very limited incident and accident data are available from military sources, and the tightly-restricted civilian UAS industry has produced very few incident reports that could shed light on design issues relevant to human factors. An exploratory study is being conducted to examine the feasibility of collecting voluntary critical incident reports from UAS pilots, and using the information to identify areas where human factors guidelines will be of assistance. Experienced UAS pilots are participating in small focus groups in which they are prompted to describe critical incidents that either reveal a system flaw, or highlight a case where the human operator contributed to system resilience or mission success. The de-identified incidents are being analyzed to identify contributing factors, with a focus on design issues that either hindered or assisted the pilot in dealing with the incident. Preliminary findings will be described.

human factors↗
NASA NTRS2015

R2U2: Monitoring and Diagnosis of Security Threats for Unmanned Aerial Systems

We present R2U2, a novel framework for runtime monitoring of security properties and diagnosing of security threats on-board Unmanned Aerial Systems (UAS). R2U2, implemented in FPGA hardware, is a real-time, REALIZABLE, RESPONSIVE, UNOBTRUSIVE Unit for security threat detection. R2U2 is designed to continuously monitor inputs from the GPS and the ground control station, sensor readings, actuator outputs, and flight software status. By simultaneously monitoring and performing statistical reasoning, attack patterns and post-attack discrepancies in the UAS behavior can be detected. R2U2 uses runtime observer pairs for linear and metric temporal logics for property monitoring and Bayesian networks for diagnosis of security threats. We discuss the design and implementation that now enables R2U2 to handle security threats and present simulation results of several attack scenarios on the NASA DragonEye UAS.

Formal Methods↗
NASA NTRS2015

Towards Real-Time, On-Board, Hardware-Supported Sensor and Software Health Management for Unmanned Aerial Systems

For unmanned aerial systems (UAS) to be successfully deployed and integrated within the national airspace, it is imperative that they possess the capability to effectively complete their missions without compromising the safety of other aircraft, as well as persons and property on the ground. This necessity creates a natural requirement for UAS that can respond to uncertain environmental conditions and emergent failures in real-time, with robustness and resilience close enough to those of manned systems. We introduce a system that meets this requirement with the design of a real-time onboard system health management (SHM) capability to continuously monitor sensors, software, and hardware components. This system can detect and diagnose failures and violations of safety or performance rules during the flight of a UAS. Our approach to SHM is three-pronged, providing: (1) real-time monitoring of sensor and software signals; (2) signal analysis, preprocessing, and advanced on-the-fly temporal and Bayesian probabilistic fault diagnosis; and (3) an unobtrusive, lightweight, read-only, low-power realization using Field Programmable Gate Arrays (FPGAs) that avoids overburdening limited computing resources or costly re-certification of flight software. We call this approach rt-R2U2, a name derived from its requirements. Our implementation provides a novel approach of combining modular building blocks, integrating responsive runtime monitoring of temporal logic system safety requirements with model-based diagnosis and Bayesian network-based probabilistic analysis. We demonstrate this approach using actual flight data from the NASA Swift UAS.

Unmanned Aerial System↗
NASA NTRS2016

Applying Required Navigation Performance Concept for Traffic Management of Small Unmanned Aircraft Systems

In anticipation of a rapid increase in the number of civil Unmanned Aircraft System(UAS) operations, NASA is researching prototype technologies for a UAS Traffic Management (UTM) system that will investigate airspace integration requirements for enabling safe, efficient low-altitude operations. One aspect a UTM system must consider is the correlation between UAS operations (such as vehicles, operation areas and durations), UAS performance requirements, and the risk to people and property in the operational area. This paper investigates the potential application of the International Civil Aviation Organizations (ICAO) Required Navigation Performance (RNP) concept to relate operational risk with trajectory conformance requirements. The approach is to first define a method to quantify operational risk and then define the RNP level requirement as a function of the operational risk. Greater operational risk corresponds to more accurate RNP level, or smaller tolerable Total System Error (TSE). Data from 19 small UAS flights are used to develop and validate a formula that defines this relationship. An approach to assessing UAS-RNP conformance capability using vehicle modeling and wind field simulation is developed to investigate how this formula may be applied in a future UTM system. The results indicate the modeled vehicles flight path is robust to the simulated wind variation, and it can meet RNP level requirements calculated by the formula. The results also indicate how vehicle-modeling fidelity may be improved to adequately verify assessed RNP level.

required navigation performance↗
NASA NTRS2016

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project: KDP-A for Phase 2 Minimum Operational Performance Standards

UAS Integration in the NAS Project has: a) Developed Technical Challenges that are crucial to UAS integration, aligned with NASA's Strategic Plan and Thrusts, and support FAA standards development. b) Demonstrated rigorous project management processes through the execution of previous phases. c) Defined Partnership Plans. d) Established path to KDP-C. Request approval of Technical Challenges, execution of partnerships and plans, and execution of near-term FY17 activities. There is an increasing need to fly UAS in the NAS to perform missions of vital importance to National Security and Defense, Emergency Management, and Science. There is also an emerging need to enable commercial applications such as cargo transport (e.g. FedEx). Unencumbered NAS Access for Civil/Commercial UAS. Provide research findings, utilizing simulation and flight tests, to support the development and validation of DAA and C2 technologies necessary for integrating Unmanned Aircraft Systems into the National Airspace System.

pilotless aircraft↗
NASA NTRS2016

Air Traffic Controller Acceptability of Unmanned Aircraft System Detect-and-Avoid Thresholds

A human-in-the-loop experiment was conducted with 15 retired air traffic controllers to investigate two research questions: (a) what procedures are appropriate for the use of unmanned aircraft system (UAS) detect-and-avoid systems, and (b) how long in advance of a predicted close encounter should pilots request or execute a separation maneuver. The controller participants managed a busy Oakland air route traffic control sector with mixed commercial/general aviation and manned/UAS traffic, providing separation services, miles-in-trail restrictions and issuing traffic advisories. Controllers filled out post-scenario and post-simulation questionnaires, and metrics were collected on the acceptability of procedural options and temporal thresholds. The states of aircraft were also recorded when controllers issued traffic advisories. Subjective feedback indicated a strong preference for pilots to request maneuvers to remain well clear from intruder aircraft rather than deviate from their IFR clearance. Controllers also reported that maneuvering at 120 seconds until closest point of approach (CPA) was too early; maneuvers executed with less than 90 seconds until CPA were more acceptable. The magnitudes of the requested maneuvers were frequently judged to be too large, indicating a possible discrepancy between the quantitative UAS well clear standard and the one employed subjectively by manned pilots. The ranges between pairs of aircraft and the times to CPA at which traffic advisories were issued were used to construct empirical probability distributions of those metrics. Given these distributions, we propose that UAS pilots wait until an intruder aircraft is approximately 80 seconds to CPA or 6 nmi away before requesting a maneuver, and maneuver immediately if the intruder is within 60 seconds and 4 nmi. These thresholds should make the use of UAS detect and avoid systems compatible with current airspace procedures and controller expectations.

unmanned aircraft systems↗
NASA NTRS2017

The Generic Resolution Advisor and Conflict Evaluator (GRACE) for Unmanned Aircraft Detect-And-Avoid Systems

The paper describes the Generic Resolution Advisor and Conflict Evaluator (GRACE), a novel alerting and guidance algorithm that combines flexibility, robustness, and computational efficiency. GRACE is generic since it was designed without any assumptions regarding temporal or spatial scales, aircraft performance, or its sensor and communication systems. Therefore, GRACE was adopted as a core component of the Java Architecture for Detect-And-Avoid (DAA) Extensibility and Modeling, developed by NASA as a research and modeling tool for Unmanned Aerial Systems Integration in the National Airspace System (NAS). GRACE has been used in a number of real-time and fast-time experiments supporting evolving requirements of DAA research, including parametric studies, NAS-wide simulations, human-in-the-loop experiments, and live flight tests.

Unmanned Aircraft↗
NASA NTRS2016

Assessing the Impact of Operational Constraints on the Near-Term Unmanned Aircraft System Traffic Management Supported Market

An economic impact market analysis was conducted for 16 leading sectors of commercial Unmanned Aerial System (UAS) applications predicted to be enabled by 2020 through the NASA UAS Traffic Management (UTM) program. Subject matter experts from seven industries were interviewed to validate concept of operations (ConOps) and market adoption assumptions for each sector. The market analysis was used to estimate direct economic impacts for each sector including serviceable addressable market, capital investment, revenue recovery potential, and operations cost savings. The resultant economic picture distinguishes the agricultural, pipeline and railroad inspection, construction, and maritime sectors of the nascent commercial UAS industry as providing the highest potential economic value in the United States. Sensitivity studies characterized the variability of select UAS sectors economic value to key regulatory or UTM ConOps requirements such as weight, altitude, and flight over populated area constraints. Takeaways from the analysis inform the validation of UTM requirements, technologies and timetables from a commercial market need and value viewpoint. This work concluded in August 2015 and reflects the state of the UAS industry and market projections at that time.

Air Traffic Management↗
NASA NTRS2017

Ensuring Interoperability Between Unmanned Aircraft Detect-and-Avoid and Manned Aircraft Collision Avoidance

The Unmanned Aircraft Systems (UAS) community in the United States has identified the need for a collision avoidance region in which UAS Detect-and-Avoid (DAA) vertical guidance is restricted to preclude interoperability issues with manned aircraft collision avoidance system vertical resolution advisories (RAs). This paper documents the process by which the collision avoidance region was defined. Three candidate definitions were evaluated on 1.3 million simulated pairwise encounters between UAS and manned aircraft covering a wide range of horizontal and vertical closure rates, angles, and miss distances. Each definition was evaluated with regard to UAS DAA interoperability with manned aircraft collision avoidance in terms of how well it achieved: 1) the primary objective of restricting DAA vertical guidance prior to RAs when the aircraft are close, and 2) the secondary objective of avoiding unnecessary restrictions of DAA vertical guidance at DAA alerts when the aircraft are further apart. The collision avoidance region definition that fully achieves the primary objective and best achieves the secondary objective was recommended to and accepted by the UAS community in the United States. By this definition, UAS and manned aircraft are in the collision avoidance region where DAA vertical guidance is restricted when the time to closest point of approach (CPA) is less than 50 seconds and either the time to co-altitude is less than 50 seconds or the current vertical separation is less than 800 feet.

unmanned aircraft systems; collision avoidance; in↗
NASA NTRS2017

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project

This presentation summarizes the simulation work conducted by the Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project. It focuses on the contribution of that research to the development of RTCA Special Committee 228's (SC-228) Minimum Operational Performance Standards (MOPS) for UAS. The research objectives and primary findings from four different human-in-the-loop simulations are discussed, along with the specific requirements these studies led to in the final MOPS document.

unmanned aircraft systems↗
NASA NTRS2018

Small Unmanned Aircraft Electromagnetic Interference (EMI) Initial Assessment

With many applications envisioned for small Unmanned Aircraft Systems (sUAS), and potentially millions of sUAS expected to be in operation in the future, the electromagnetic interference environment associated with the sUAS is of interest to understanding the potential performance impacts on the sUAS command and control communications link as well as the sUAS payload and payload links. As part of NASA's UAS Traffic Management (UTM) Project, flight experiments are planned to characterize the RF environment at altitudes up to 400 ft to better understand how UTM command and control links can be expected to perform. The flight experiments will use an RF channel sensing payload attached to an sUAS. In terms of the payload being capable of measuring relatively low level signals at altitude, electromagnetic interference (EMI) emanating from the sUAS vehicle itself could potentially complicate the measurement process. For this reason, NASA was interested in measuring the EMI performance of the sUAS planned for these flight experiments, a DJI model S1000. The S1000 was thus measured in a controlled EMI test chamber at the NASA Ames Research Center. The S1000 is a carbon fiber based platform with eight rotors. As such, the EMI test results represent potential performance of a number of similar sUAS types. sUAS platforms significantly different from the S1000 may also require EMI testing, and the method employed for NASA's S1000 EMI tests can be applied to other platforms. In this paper we describe the UTM project, the RF channel sensing payload, the EMI testing method and EMI test results for the S1000, and discuss the implications of these results.

Unmanned aircraft↗
NASA NTRS2018

Small Unmanned Aircraft Electromagnetic Interference (EMI) Initial Assessment

With many applications envisioned for small Unmanned Aircraft Systems (sUAS), and potentially millions of sUAS expected to be in operation in the future, the electromagnetic interference environment associated with the sUAS is of interest to understanding the potential performance impacts on the sUAS command and control communications link as well as the sUAS payload and payload links. As part of NASAâ€"TM"s UAS Traffic Management (UTM) Project, flight experiments are planned to characterize the RF environment at altitudes up to 400 ft to better understand how UTM command and control links can be expected to perform. The flight experiments will use an RF channel sensing payload attached to an sUAS. In terms of the payload being capable of measuring relatively low level signals at altitude, electromagnetic interference (EMI) emanating from the sUAS vehicle itself could potentially complicate the measurement process. For this reason, NASA was interested in measuring the EMI performance of the sUAS planned for these flight experiments, a DJI model S1000. The S1000 was thus measured in a controlled EMI test chamber at the NASA Ames Research Center. The S1000 is a carbon fiber based platform with eight rotors. As such, the EMI test results represent potential performance of a number of similar sUAS types. sUAS platforms significantly different from the S1000 may also require EMI testing, and the method employed for NASAâ€"TM"s S1000 EMI tests can be applied to other platforms. In this paper we describe the UTM project, the RF channel sensing payload, the EMI testing method and EMI test results for the S1000, and discuss the implications of these results.

traffic management↗
NASA NTRS2018

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project: Terminal Operations HITL 1B Primary Results

This presentation provides an overview of the primary results from the Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project's second Terminal Operations human-in-the-loop simulation. This talk covers the background of this follow-on experiment, which includes an overview of the first Terminal Operations HITL performed by the project. The primary results include a look at the number and durations of detect and avoid (DAA) alerts issued by the two DAA systems under test. It also includes response time metrics and metrics on the ability of the pilot-in-command (PIC) to maintain sufficient separation. Additional interoperability metrics are included to illustrate how pilots interact with the tower controller. Implications and conclusions are covered at the end.

unmanned aircraft systems↗
NASA NTRS2018

An Overview of Recent NASA Airborne Science Projects in the Arctic Using Manned and Unmanned Aircraft

As NASA prepares to launch ICESAT-II there are significant efforts underway to plan for aircraft under-flights to calibrate the onboard lasers and to validate data products. This presentation will begin with an overview of recent airborne science missions including Operation Ice Bridge that have focused observations on the arctic. This will be followed by results from recent NASA sponsored unmanned aircraft missions and a discussion how these new observing technologies can contribute to future research in the Arctic. Information on recent icing wind tunnel testing and comparisons with icing prediction models will also be shared leading to discussions on specific challenges in adapting systems to harsh arctic conditions.

Aircraft↗
NASA NTRS2014

Guaranteed Road Network Search with Small Unmanned Aircraft

The use of teams of small unmanned aircraft in real-world rapid-response missions is fast becoming a reality. One such application is search and detection of an evader in urban areas. This paper draws on results in graph-based pursuit-evasion, developing mappings from these abstractions to primitive motions that may be performed by aircraft, to produce search strategies providing guaranteed capture of road-bound targets. The first such strategy is applicable to evaders of arbitrary speed and agility, offering a conservative solution that is insensitive to motion constraints pursuers may possess. This is built upon to generate two strategies for capture of targets having a known speed bound that require searcher teams of much smaller size. The efficacy of these algorithms is demonstrated by evaluation in extensive simulation using realistic vehicle models across a spectrum of environment classes.

unmanned aircraft systems↗
NASA NTRS2017

An Integrated System for Autonomous Search and Track with a Small Unmanned Aerial Vehicle

This article presents a framework for searching, detecting, and tracking an object of interest with a small unmanned aerial vehicle (sUAV). The vehicle is given an area to search for an object of interest. Once the object is detected, the sUAV follows the target while maintaining a fixed distance and centered on its image plane. This paper describes an architecture for integrating autonomy capabilities for search and track for sUAVs. The system has been implemented in the Robot Operating System (ROS) framework using the Parrot ARDrone platform. In this paper we present our technical approach, the system architecture and demonstrate the principles of the approach in a simulation environment and indoor flight tests.

Unmanned Aerial Vehicle↗