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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

ICAROUS: Integrated Configurable Architecture for Unmanned Systems

NASA's Unmanned Aerial System (UAS) Traffic Management (UTM) project aims at enabling near-term, safe operations of small UAS vehicles in uncontrolled airspace, i.e., Class G airspace. A far-term goal of UTM research and development is to accommodate the expected rise in small UAS traffic density throughout the National Airspace System (NAS) at low altitudes for beyond visual line-of-sight operations. This video describes a new capability referred to as ICAROUS (Integrated Configurable Algorithms for Reliable Operations of Unmanned Systems), which is being developed under the auspices of the UTM project. ICAROUS is a software architecture comprised of highly assured algorithms for building safety-centric, autonomous, unmanned aircraft applications. Central to the development of the ICAROUS algorithms is the use of well-established formal methods to guarantee higher levels of safety assurance by monitoring and bounding the behavior of autonomous systems. The core autonomy-enabling capabilities in ICAROUS include constraint conformance monitoring and autonomous detect and avoid functions. ICAROUS also provides a highly configurable user interface that enables the modular integration of mission-specific software components.

Consiglio, Maria C.↗
NASA NTRS2016

ICAROUS - Integrated Configurable Algorithms for Reliable Operations Of Unmanned Systems

NASA's Unmanned Aerial System (UAS) Traffic Management (UTM) project aims at enabling near-term, safe operations of small UAS vehicles in uncontrolled airspace, i.e., Class G airspace. A far-term goal of UTM research and development is to accommodate the expected rise in small UAS traffic density throughout the National Airspace System (NAS) at low altitudes for beyond visual line-of-sight operations. This paper describes a new capability referred to as ICAROUS (Integrated Configurable Algorithms for Reliable Operations of Unmanned Systems), which is being developed under the UTM project. ICAROUS is a software architecture comprised of highly assured algorithms for building safety-centric, autonomous, unmanned aircraft applications. Central to the development of the ICAROUS algorithms is the use of well-established formal methods to guarantee higher levels of safety assurance by monitoring and bounding the behavior of autonomous systems. The core autonomy-enabling capabilities in ICAROUS include constraint conformance monitoring and contingency control functions. ICAROUS also provides a highly configurable user interface that enables the modular integration of mission-specific software components.

Consiglio, María↗
NASA NTRS2004

Architecture for robot intelligence

An architecture for robot intelligence enables a robot to learn new behaviors and create new behavior sequences autonomously and interact with a dynamically changing environment. Sensory information is mapped onto a Sensory Ego-Sphere (SES) that rapidly identifies important changes in the environment and functions much like short term memory. Behaviors are stored in a DBAM that creates an active map from the robot's current state to a goal state and functions much like long term memory. A dream state converts recent activities stored in the SES and creates or modifies behaviors in the DBAM.

Peters, II, Richard Alan↗
NASA NTRS2008

Architecture for Multiple Interacting Robot Intelligences

An architecture for robot intelligence enables a robot to learn new behaviors and create new behavior sequences autonomously and interact with a dynamically changing environment. Sensory information is mapped onto a Sensory Ego-Sphere (SES) that rapidly identifies important changes in the environment and functions much like short term memory. Behaviors are stored in a database associative memory (DBAM) that creates an active map from the robot's current state to a goal state and functions much like long term memory. A dream state converts recent activities stored in the SES and creates or modifies behaviors in the DBAM.

Peters, Richard Alan, II↗
NASA NTRS2009

Apparatus for multiprocessor-based control of a multiagent robot

An architecture for robot intelligence enables a robot to learn new behaviors and create new behavior sequences autonomously and interact with a dynamically changing environment. Sensory information is mapped onto a Sensory Ego-Sphere (SES) that rapidly identifies important changes in the environment and functions much like short term memory. Behaviors are stored in a DBAM that creates an active map from the robot's current state to a goal state and functions much like long term memory. A dream state converts recent activities stored in the SES and creates or modifies behaviors in the DBAM.

Peters, II, Richard Alan↗
NASA NTRS1988

Blackboard architectures and their relationship to autonomous space systems

The blackboard architecture provides a powerful paradigm for the autonomy expected in future spaceborne systems, especially SDI and Space Station. Autonomous systems will require skill in both the classic task of information analysis and the newer tasks of decision making, planning and system control. Successful blackboard systems have been built to deal with each of these tasks separately. The blackboard paradigm achieves success in difficult domains through its ability to integrate several uncertain sources of knowledge. In addition to flexible behavior during autonomous operation, the system must also be capable of incrementally growing from semiautonomy to full autonomy. The blackboard structure allows this development. The blackboard's ability to handle error, its flexible execution, and variants of this paradigm are discussed as they apply to specific problems of the space environment.

Thornbrugh, Allison↗
NASA NTRS2012

Nemesis Autonomous Test System

A generalized framework has been developed for systems validation that can be applied to both traditional and autonomous systems. The framework consists of an automated test case generation and execution system called Nemesis that rapidly and thoroughly identifies flaws or vulnerabilities within a system. By applying genetic optimization and goal-seeking algorithms on the test equipment side, a "war game" is conducted between a system and its complementary nemesis. The end result of the war games is a collection of scenarios that reveals any undesirable behaviors of the system under test. The software provides a reusable framework to evolve test scenarios using genetic algorithms using an operation model of the system under test. It can automatically generate and execute test cases that reveal flaws in behaviorally complex systems. Genetic algorithms focus the exploration of tests on the set of test cases that most effectively reveals the flaws and vulnerabilities of the system under test. It leverages advances in state- and model-based engineering, which are essential in defining the behavior of autonomous systems. It also uses goal networks to describe test scenarios.

Barltrop, Kevin J.↗
NASA NTRSDate not supplied

Use of Autonomous Vehicles in Emergency Situations - Wildfire Planning and Mitigation

Unmanned vehicles can be useful in emergency situations for many applications such as surveillance, access to harsh environments, and delivery of supplies. However, efforts to use drones in these situations has not been well-coordinated. This project is looking at multiple aspects of the problem with sub-teams addressing: establishing a method and database network to identify and communicate resources for deployment during major incidents and disasters; identifying how drones and other aviation assets can be useful in wildfire-specific emergencies, including mitigation and prevention planning; and considering safety, rules, and behavior of autonomous vehicles.

Autonomous Vehicles↗
NASA NTRS1993

Autogenic-feedback training improves pilot performance during emergency flying conditions

Studies have shown that autonomous mode behavior is one cause of aircraft fatalities due to pilot error. In such cases, the pilot is in a high state of psychological and physiological arousal and tends to focus on one problem, while ignoring more critical information. The effect of training in physiological self-recognition and regulation, as a means of improving crew cockpit performance was examined. Seventeen pilots were assigned to the treatment and control groups matched for accumulated flight hours. The treatment group comprised four pilots of HC-130 Hercules aircraft and four HH-65 Dolphin helicopter pilots; the control group comprised three pilots of HC-130's and six Dolphin helicopter pilots. During an initial flight physiological data were recorded for each crewmember and individual crew performance and rated by an instructor pilot. Eight crewmembers were then taught to regulate their own physiological response levels using Autogenic-Feedback Training (AFT). The remaining subjects received no training. During a second flight, treatment subjects showed significant improvement in performance, while controls did not improve. The results indicate that AFT management of high states of physiological arousal may improve pilot performance during emergency flying conditions.

Kellar, Michael A.↗
NASA NTRS1993

Psychophysiological investigations of the biomedical problems of manned spaceflight

The Final Report on psychophysiological investigations of the biomedical problems of manned spaceflight is presented. In the first project, statistical analyses of human autonomic data were performed. The objectives were the following: to establish a relational data base containing human psychophysiological data obtained from Shuttle flight experiments and ground-based research over a 20 year period; to enable multi-user access and retrieval of these data for subsequent analyses and for possible inclusion in the proposed Life Sciences Data Archive; and to enable/conduct statistical analyses across several experiments on large subject populations which can thereby provide definitive answers to questions on human autonomic and behavioral responses and adaptation to environmental stressors on Earth and in space. The second project studied motion sickness. The objectives were: to test/develop hardware and procedures to be incorporated into preflight training of crewmembers of Spacelab-J; and to examine spin-off applications of AFT. The third project studied orthostatic intolerance. The objective was to test the feasibility of applying autogenic-feedback training as a potential treatment for postflight orthostatic intolerance.

Source record↗
NASA NTRS1994

Autogenic-feedback training improves pilot performance during emergency flying conditions

Studies have shown that autonomous mode behavior is one cause of aircraft fatalities due to pilot error. In such cases, the pilot is in a high state of psychological and physiological arousal and tends to focus on one problem, while ignoring more critical information. This study examined the effect of training in physiological self-recognition and regulation, as a means of improving crew cockpit performance. Seventeen pilots were assigned to the treatment and control groups matched for accumulated flight hours. The treatment group comprised three pilots of HC-130 Hercules aircraft and four HH-65 Dolphin helicopter pilots; the control group comprised three pilots of HC-130's and six Dolphin helicopter pilots. During an initial flight, physiological data were recorded for each crew member and individual crew performance was rated by an instructor pilot. Eight crewmembers were then taught to regulate their own physiological response levels using Autogenic-Feedback Training (AFT). The remaining subjects received no training. During a second flight, treatment subjects showed significant improvement in performance, while controls did not improve. The results indicate that AFT management of high states of physiological arousal may improve pilot performance during emergency flying conditions.

Kellar, Michael A.↗
NASA NTRS2001

Autogenic Feedback Training Exercise and pilot performance: enhanced functioning under search-and-rescue flying conditions

Studies have shown that autonomous mode behavior is one cause of aircraft fatalities due to pilot error. In such cases, the pilot is in a high state of psychological and physiological arousal and tends to focus on one problem, while ignoring more critical information. This study examined the effect of training in physiological self-recognition and regulation, as a means of improving crew cockpit performance. Seventeen pilots were assigned to the treatment and control groups matched for accumulated flight hours. The treatment group contained 4 pilots from HC-130 Hercules aircraft and 4 HH-65 Dolphin helicopter pilots; the control group contained 3 pilots of HC-130s and 6 helicopter pilots. During an initial flight, physiological data were recorded on each crewmember and an instructor pilot rated individual crew performance. Eight crewmembers were then taught to regulate their own physiological response levels using Autogenic-Feedback Training Exercise (AFTE). The remaining participants received no training. During a second flight, treatment participants showed significant improvement in performance (rated by the same instructor pilot as in pretests) while controls did not improve. The results indicate that AFTE management of high states of physiological arousal may improve pilot performance during emergency flying conditions.

NASA Discipline Neuroscience↗
NASA NTRS2002

Predictors of response to a behavioral treatment in patients with chronic gastric motility disorders

Chronic gastric motility disorders have proven intractable to most traditional therapies. Twenty-six patients with chronic nausea and vomiting were treated with a behavioral technique, autonomic training (AT) with directed imagery (verbal instructions), to help facilitate physiological control. After treatment, gastrointestinal symptoms decreased by >30% in 58% of the treated patients. We compared those improved patients to the 43% who did not improve significantly. No significant differences existed in baseline symptoms and autonomic measures between both groups. However, baseline measures of gastric emptying and autonomic function predicted treatment outcome. Patients who improved manifested mild to moderate delay in baseline gastric emptying measures. The percent of liquid gastric emptying at 60 mins and the sympathetic adrenergic measure of percent of change in the foot cutaneous blood flow in response to cold stress test predicted improvement in AT outcome, with clinical diagnostic values of 77% and 71%, respectively. We conclude that AT treatment can be efficacious in some patients with impaired gastric emptying and adrenergic dysfunction. More work is warranted to compare biofeedback therapy with gastric motility patients and controls in population-based studies.

NASA Center ARC↗
NASA NTRS2006

Humanoids for Lunar and Planetary Surface Operations

Human-like shape makes humanoids well suited for being fostered/taught by humans, and for learning from humans, which we consider the best means to develop cognitive and perceptual/motor skills for truly intelligent, cognitive robots.

autonomous behavior↗
NASA NTRS2011

NASA Tech Briefs, April 2011

Topics covered include: Amperometric Solid Electrolyte Oxygen Microsensors with Easy Batch Fabrication; Two-Axis Direct Fluid Shear Stress Sensor for Aerodynamic Applications; Target Assembly to Check Boresight Alignment of Active Sensors; Virtual Sensor Test Instrumentation; Evaluation of the Reflection Coefficient of Microstrip Elements for Reflectarray Antennas; Miniaturized Ka-Band Dual-Channel Radar; Continuous-Integration Laser Energy Lidar Monitor; Miniaturized Airborne Imaging Central Server System; Radiation-Tolerant, SpaceWire-Compatible Switching Fabric; Small Microprocessor for ASIC or FPGA Implementation; Source-Coupled, N-Channel, JFET-Based Digital Logic Gate Structure Using Resistive Level Shifters; High-Voltage-Input Level Translator Using Standard CMOS; Monitoring Digital Closed-Loop Feedback Systems; MASCOT - MATLAB Stability and Control Toolbox; MIRO Continuum Calibration for Asteroid Mode; GOATS Image Projection Component; Coded Modulation in C and MATLAB; Low-Dead-Volume Inlet for Vacuum Chamber; Thermal Control Method for High-Current Wire Bundles by Injecting a Thermally Conductive Filler; Method for Selective Cleaning of Mold Release from Composite Honeycomb Surfaces; Infrared-Bolometer Arrays with Reflective Backshorts; Commercialization of LARC (trade mark) -SI Polyimide Technology; Novel Low-Density Ablators Containing Hyperbranched Poly(azomethine)s; Carbon Nanotubes on Titanium Substrates for Stray Light Suppression; Monolithic, High-Speed Fiber-Optic Switching Array for Lidar; Grid-Tied Photovoltaic Power System; Spectroelectrochemical Instrument Measures TOC; A Miniaturized Video System for Monitoring Drosophila Behavior; Hydrofocusing Bioreactor Produces Anti-Cancer Alkaloids; Creep Measurement Video Extensometer; Radius of Curvature Measurement of Large Optics Using Interferometry and Laser Tracker n-B-pi-p Superlattice Infrared Detector; Safe Onboard Guidance and Control Under Probabilistic Uncertainty; General Tool for Evaluating High-Contrast Coronagraphic Telescope Performance Error Budgets; Hidden Statistics of Schroedinger Equation; Optimal Padding for the Two-Dimensional Fast Fourier Transform; Spatial Query for Planetary Data; Higher Order Mode Coupling in Feed Waveguide of a Planar Slot Array Antenna; Evolutionary Computational Methods for Identifying Emergent Behavior in Autonomous Systems; Sampling Theorem in Terms of the Bandwidth and Sampling Interval; Meteoroid/Orbital Debris Shield Engineering Development Practice and Procedure; Self-Balancing, Optical-Center-Pivot, Fast-Steering Mirror; Wireless Orbiter Hang-Angle Inclinometer System; and Internal Electrostatic Discharge Monitor - IESDM.

Source record↗
NASA NTRS2003

Sensory Motor Coordination in Robonaut

As a participant of the year 2000 NASA Summer Faculty Fellowship Program, I worked with the engineers of the Dexterous Robotics Laboratory at NASA Johnson Space Center on the Robonaut project. The Robonaut is an articulated torso with two dexterous arms, left and right five-fingered hands, and a head with cameras mounted on an articulated neck. This advanced space robot, now driven only teleoperatively using VR gloves, sensors and helmets, is to be upgraded to a thinking system that can find, interact with and assist humans autonomously, allowing the Crew to work with Robonaut as a (junior) member of their team. Thus, the work performed this summer was toward the goal of enabling Robonaut to operate autonomously as an intelligent assistant to astronauts. Our underlying hypothesis is that a robot can develop intelligence if it learns a set of basic behaviors (i.e., reflexes - actions tightly coupled to sensing) and through experience learns how to sequence these to solve problems or to accomplish higher-level tasks. We describe our approach to the automatic acquisition of basic behaviors as learning sensory-motor coordination (SMC). Although research in the ontogenesis of animals development from the time of conception) supports the approach of learning SMC as the foundation for intelligent, autonomous behavior, we do not know whether it will prove viable for the development of autonomy in robots. The first step in testing the hypothesis is to determine if SMC can be learned by the robot. To do this, we have taken advantage of Robonaut's teleoperated control system. When a person teleoperates Robonaut, the person's own SMC causes the robot to act purposefully. If the sensory signals that the robot detects during teleoperation are recorded over several repetitions of the same task, it should be possible through signal analysis to identify the sensory-motor couplings that accompany purposeful motion. In this report, reasons for suspecting SMC as the basis for intelligent behavior will be reviewed. A robot control system for autonomous behavior that uses learned SMC will be proposed. Techniques for the extraction of salient parameters from sensory and motor data will be discussed. Experiments with Robonaut will be discussed and preliminary data presented.

Peters, Richard Alan, II↗