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Video demonstrate the ability of ICAROUS (Independent Configurable Architecture for Reliable Operations of Autonomous Systems) to perform autonomous traffic avoidance and merging with cooperative aircraft in simulation. The Video will be shown in the NASA booth at AUVSI XPONENTIAL (Chicago, IL 4/29/19-5 /2/19) to aid in demonstrating and explaining the capabilities of the ICAROUS research system.
This paper describes the results of a fast-time simulation experiment and a high-fidelity simulator validation with merging streams of aircraft flying Continuous Descent Arrivals through generic airspace to a runway at Dallas-Ft Worth. Aircraft made small speed adjustments based on an airborne-based spacing algorithm, so as to arrive at the threshold exactly at the assigned time interval behind their Traffic-To-Follow. The 40 aircraft were initialized at different altitudes and speeds on one of four different routes, and then merged at different points and altitudes while flying Continuous Descent Arrivals. This merging and spacing using flight deck equipment and procedures to augment or implement Air Traffic Management directives is called Flight Deck-based Merging and Spacing, an important subset of a larger Airborne Precision Spacing functionality. This research indicates that Flight Deck-based Merging and Spacing initiated while at cruise altitude and well prior to the Terminal Radar Approach Control entry can significantly contribute to the delivery of aircraft at a specified interval to the runway threshold with a high degree of accuracy and at a reduced pilot workload. Furthermore, previously documented work has shown that using a Continuous Descent Arrival instead of a traditional step-down descent can save fuel, reduce noise, and reduce emissions. Research into Flight Deck-based Merging and Spacing is a cooperative effort between government and industry partners.
Most research in modelling human information processing and decision making has been devoted to the case of the single human operator. In the present effort, concepts from the fields of organizational behavior, engineering psychology, team theory and mathematical modelling are merged in an attempt to consider first the case of two cooperating decisionmakers (the Dyad) in a multi-task environment. Rooted in the well-known Dynamic Decision Model (DDM), the normative descriptive approach brings basic cognitive and psychophysical characteristics inherent to human behavior into a team theoretic analytic framework. An experimental paradigm, involving teams in dynamic decision making tasks, is designed to produce the data with which to build the theoretical model.
The Robotic Air Vehicle (RAV) system is described. The program's objectives were to design, implement, and demonstrate cooperating expert systems for piloting robotic air vehicles. The development of this system merges conventional programming used in passive navigation with Artificial Intelligence techniques such as voice recognition, spatial reasoning, and expert systems. The individual components of the RAV system are discussed as well as their interactions with each other and how they operate as a system.
NASA needs autonomous robotic exploration of difficult (rough and/or steep) scientifically interesting Martian terrains. Concepts involving distributed autonomy for cooperative robotic exploration are key to enabling new scientific objectives in robotic missions. We propose to utilize a legged robot as an adjunct scout to a rover for access to difficult - scientifically interesting - terrains (rocky areas, slopes, cliffs). Our final mission scenario involves the Ames rover platform "K9" and Scorpion acting together to explore a steep cliff, with the Scorpion robot rappelling down using the K9 as an anchor as well as mission planner and executive. Cooperation concepts, including wheeled rappelling robots have been proposed before. Now we propose to test the combined advantages of a wheeled vehicle with a legged scout as well as the advantages of merging of high level planning and execution with biologically inspired, behavior based robotics. We propose to use the 8-legged, multifunctional autonomous robot platform Scorpion that is currently capable of: Walking on different terrains (rocks, sand, grass, ...). Perceiving its environment and modifying its behavioral pattern accordingly. These capabilities would be extended to enable the Scorpion to: communicate and cooperate with a partner robot; climb over rocks, rubble piles, and objects with structural features. This will be done in the context of exploration of rough terrains in the neighborhood of the rover, but inaccessible to it, culminating in the added capability of rappelling down a steep cliff for both vertical and horizontal terrain observation.
On-going work into user requirements analysis using CLIPS (NASA/JSC) expert systems as an intelligent event simulator has led to research into three-dimensional (3D) interfaces. Previous work involved CLIPS and two-dimensional (2D) models. Integral to this work was the development of the University of Massachusetts Lowell parallel version of CLIPS, called PCLIPS. This allowed us to create both a Software Bus and a group problem-solving environment for expert systems development. By shifting the PCLIPS paradigm to use the VEOS messaging protocol we have merged VEOS (HlTL/Seattle) and CLIPS into a distributed virtual worlds prototyping environment (VCLIPS). VCLIPS uses the VEOS protocol layer to allow multiple experts to cooperate on a single problem. We have begun to look at the control of a virtual factory. In the virtual factory there are actors and objects as found in our Lincoln Logs Factory of the Future project. In this artificial reality architecture there are three VCLIPS entities in action. One entity is responsible for display and user events in the 3D virtual world. Another is responsible for either simulating the virtual factory or communicating with the real factory. The third is a user interface expert. The interface expert maps user input levels, within the current prototype, to control information for the factory. The interface to the virtual factory is based on a camera paradigm. The graphics subsystem generates camera views of the factory on standard X-Window displays. The camera allows for view control and object control. Control or the factory is accomplished by the user reaching into the camera views to perform object interactions. All communication between the separate CLIPS expert systems is done through VEOS.
Drone usage has been on the rise in recent years with applications that include parcel delivery, wildlife protection, precision farming, law enforcement, and industrial inspection, just to name a few. Once regulations and safety policies are put in place to allow for the widespread use of unmanned drones, the number of aircraft in the National Airspace System (NAS) is expected to skyrocket to millions, potentially congesting the airspace which increases the likelihood of separation violations and possibly incidents. Currently, flight infrastructure can only support a few thousand aircraft flying over the United States National Airspace System (NAS) at any given time. A delay at one airport can send ripple effects throughout the system, causing more delays and missed connections. In air traffic control, separation is the concept of keeping an “ownship” aircraft outside a minimum distance from “intruder” aircraft to reduce the risk of the aircraft colliding, as well as preventing accidents due to secondary factors, such as wake turbulence. Maintaining proper separation is often a safety critical property for fixed-wing drones in the airspace. This paper addresses drone separation in time and distance for high volume corridors (en route) and lanes (on ground), merging as well as crossing intersections of multiple corridors/lanes. In this paper, the term drone is applied to both Unmanned Aerial Vehicle (UAV) and small Unmanned Aircraft System (UAS) vehicles operating autonomously. There exists a gamut of approaches to the merging and crossing problems. At one end of the extreme are the conservative yet low cost and verifiable solutions of today that deal with two drones at a time. At the other end are complex Machine Learning-based solutions with high computing requirements for fully autonomous drones of the future that are expected to handle all contentions. This paper presents a feasible and verifiable strategic approach to these problems that is based on distributed cooperation between the drones and the infrastructure. Three phases of the strategic approach (Prepare, Adjust, Commit) are presented. Simulation results are presented that show the proposed approach is stable and resilient to induced perturbations and guarantees a set of fixed-wing drones to merge and cross intersections by adjusting their speed based on their distance to the aircraft in front of them while remaining in the equilibrium state. The equilibrium state is defined as the state when a set of n aircraft move at a relatively constant speed and uniform spacing from each other in a congested system. A congested system is defined as the state when at least one aircraft cannot move at its maximum allowed speed. Unlike existing centralized and pre-planned approaches, the proposed solution is fully distributed and enables autonomous aircraft to decide to adjust their speed and distance with respect to the preceding aircraft, dynamically. Simulation results are presented that assess the feasibility of the approach.
Drone usage has been on the rise in recent years with applications that include parcel delivery, wildlife protection, precision farming, law enforcement, and industrial inspection, just to name a few. Once regulations and safety policies are put in place to allow for the widespread use of unmanned drones, the number of aircraft in the National Airspace System (NAS) is expected to skyrocket to millions, potentially congesting the airspace which increases the likelihood of separation violations and possibly incidents. Currently, flight infrastructure can only support a few thousand aircraft flying over the United States National Airspace System (NAS) at any given time. A delay at one airport can send ripple effects throughout the system, causing more delays and missed connections. In air traffic control, separation is the concept of keeping an “ownship” aircraft outside a minimum distance from “intruder” aircraft to reduce the risk of the aircraft colliding, as well as preventing accidents due to secondary factors, such as wake turbulence. Maintaining proper separation is often a safety critical property for fixed-wing drones in the airspace. This paper addresses drone separation in time and distance for high volume corridors (en route) and lanes (on ground), merging as well as crossing intersections of multiple corridors/lanes. In this paper, the term drone is applied to both Unmanned Aerial Vehicle (UAV) and small Unmanned Aircraft System (UAS) vehicles operating autonomously. There exists a gamut of approaches to the merging and crossing problems. At one end of the extreme are the conservative yet low cost and verifiable solutions of today that deal with two drones at a time. At the other end are complex Machine Learning-based solutions with high computing requirements for fully autonomous drones of the future that are expected to handle all contentions. This paper presents a feasible and verifiable strategic approach to these problems that is based on distributed cooperation between the drones and the infrastructure. Three phases of the strategic approach (Prepare, Adjust, Commit) are presented. Simulation results are presented that show the proposed approach is stable and resilient to induced perturbations and guarantees a set of fixed-wing drones to merge and cross intersections by adjusting their speed based on their distance to the aircraft in front of them while remaining in the equilibrium state. The equilibrium state is defined as the state when a set of n aircraft move at a relatively constant speed and uniform spacing from each other in a congested system. A congested system is defined as the state when at least one aircraft cannot move at its maximum allowed speed. Unlike existing centralized and pre-planned approaches, the proposed solution is fully distributed and enables autonomous aircraft to decide to adjust their speed and distance with respect to the preceding aircraft, dynamically. Simulation results are presented that assess the feasibility of the approach.
We present new 6cm and 4cm radio continuum images of the central regions of the merging galaxy systems NGC3256 and NGC4194. NGC3256 is imaged with a resolution of approx. 1 in. or approx. 190pc; NGC4194 is imaged with a resolution of approx. 0.3 in. or approx. 50pc. In both systems, we detect numerous compact radio sources embedded in more diffuse radio emission. We detect 65 compact sources in NGC3256 at 6cm and we detect 46 compact sources in NGC4194, both to a limiting luminosity of approx. 5 x 10(exp 18) W/ Hz or approx. 5 times the luminosity of Cas A. Most of the compact radio sources are loosely associated with active star forming regions but not with specific optical emission sources. Several compact radio sources in NGC3256 are near positions of compact X-ray sources detected by Lira et al.. In both NGC3256 and NGC4194, we are able to measure reliable spectral indices for the stronger sources. We find in NGC3256 approx. 20% have nominally flat radio spectral indices (indicating they are dominated by thermal radio emission from HII regions) while approx. 80% have nominally steep spectral indices (indicating they are dominated by nonthermal emission from supernova remnants). In NGC4194, half the compact radio sources have flat spectral indices and half have steep indices. For the flat-spectrum sources, we estimate the number of young massive stars and the associated ionized gas masses. For the steep-spectrum sources, we estimate supernova rates. We compare these results with those from other well-studied merging galaxy systems. We gratefully acknowledge use of the NRAO Very Large Array (VLA) and the VLA Archive. NRAO is a facility of the National Science Foundation, operated under cooperative agreement by Associated Universities, Inc.
The Cold War's end opened an opportunity for greater cooperation in planetary exploration for the United States and Russia. Two study groups were formed, Mars Together and FIRE and ICE. The Mars Together team developed a concept for a flight in 1998 that merged one U.S. Mars Surveyor 98 mission with the former Russian Mars 96 mission to further understanding of the Mars surface and atmosphere. The FIRE and ICE team developed concepts for a dual-spacecraft mission to the solar corona and for a mission to Pluto. The missions, scientific potential, and open issues are described.
We present new, deep, high resolution 6cm and 4cm radio continuum images of the central regions of a time-ordered sequence of seven large galaxy mergers. The radio observations are able to detect star-forming re- gions that are completely obscured at optical wavelengths. In all systems, we detect numerous compact radio sources embedded in more diffuse ra- dio emission, with limiting luminosities of approx. 1-5 x 10(exp l8) W Hz or approx. 1-5 times the luminosity of Cas A. Many of the compact radio sources are loosely associated with active starforming regions but not with specific optical or W emission sources. Several of the compact radio sources are coincident with Ultra-luminous X-ray objects (ULX's). In most systems, we are able to measure reliable spectral indices for the stronger sources. We find that the fraction of compact radio cources with nominally flat radio spectral indices (indicating they ae dominated by thermal radio emission from HII regions) decreases with merger age, while the fraction of sources with nonimally steep spectral indices (indicating they are dominated by nonthermal emission from supernova remnants) increases. For the flat-spectrum sources, we estimate the numbers of young massive stars, associated ionized gas masses, we estimate supernova rates and required star-formation rates, We compare these results with those from other well-studied merging galaxy systems and from other determinations of star-formation rates. We gratefully acknowledge use of the NRAO Very Large Array (VLA) and the VLA Archive. NRAO is a facility of the National Science Foundation, operated under cooperative agreement by Associated Universities, Inc.
Drone usage has been on the rise in recent years with applications that include parcel delivery, wildlife protection, precision farming, law enforcement, and industrial inspection, just to name a few. This paper addresses drone separation in time and distance for high volume corridors (en route) and lanes (on ground), merging as well as crossing intersections of multiple corridors/lanes. There exists a gamut of approaches to solving merging and intersection crossing problems. At one end of the extreme are the conservative yet low cost and verifiable solutions of today that deal with two drones at a time. At the other end are complex Machine Learning-based solutions with high computing requirements for fully autonomous drones of the future that are expected to handle all contentions. This paper presents a feasible and verifiable strategic approach to solving these problems that is based on distributed cooperation between the UAVs/UASs and the infrastructure. Unlike existing centralized and pre-planned approaches, the proposed solution is fully distributed and enables autonomous aircraft to decide to adjust their speed and distance with respect to the preceding aircraft, dynamically. Three phases of the strategic approach (Prepare, Adjust, Commit) are presented. Simulation results are presented that show the proposed approach is stable and resilient to induced perturbations and guarantees a set of fixed-wing UAVs/UASs to merge and cross intersections by adjusting their speed based on their distance to the aircraft in front of them.
Rapid prototyping (RP) is a layer-by-layer-based additive manufacturing process for constructing three-dimensional representations of a computer design from a wax, plastic, or similar material. Wire arc spray (WAS) is a metal spray forming technique, which deposits thin layers of metal onto a substrate or pattern. Marshall Space Flight Center currently has both capabilities in-house, and this project proposed merging the two processes into an innovative manufacturing technique, in which intermediate injection molding tool halves were to be fabricated with RP and WAS metal forming.
The overall objective of the present effort is to produce models for major and selected minor components of Europa s neutral atmosphere in 1-D versus altitude and in 2-D versus altitude and longitude or latitude. A 3-D model versus all three coordinates (alt, long, lat) will be studied but development on this is at present limited by computing facilities available to the investigation team. In this first year we have focused on 1-D modeling with Co-I Valery Shematovich s Direct Simulation Monte Carlo (DSMC) code for water group species (H2O, O2, O, OH) and on 2-D with Co-I Mau Wong's version of a similar code for O2, O, CO, CO2, and Na. Surface source rates of H2O and O2 from sputtering and radiolysis are used in the 1-D model, while observations for CO2 at the Europa surface and Na detected in a neutral cloud ejected from Europa are used, along with the O2 sputtering rate, to constrain source rates in the 2-D version. With these separate approaches we are investigating a range of processes important to eventual implementation of a comprehensive 3-D atmospheric model which could be used to understand present observations and develop science requirements for future observations, e.g. from Earth and in Europa orbit. Within the second year we expect to merge the full water group calculations into the 2-D version of the DSMC code which can then be extended to 3-D, pending availability of computing resources. Another important goal in the second year would be the inclusion of sulk and its more volatile oxides (SO, SO2).
Flow-field analysis techniques under continuing development at NASA's Marshall Space Flight Center are the foundation for a new type of health monitoring instrumentation for propulsion systems and a vast range of other applications. Physics, spectroscopy, mechanics, optics, and cutting-edge computer sciences merge to make recent developments in such instrumentation possible. Issues encountered in adaptation of such a system to future space vehicles, or retrofit in existing hardware, are central to the work. This paper is an overview of the collaborative efforts results, current efforts, and future plans.
The objectives of the NASA-AMES Cooperative Agreement were to investigate, develop, and evaluate, via test cases, the system parameters and processing algorithms that constrain the overall performance of the Information Sciences Division's Artificial Intelligence Research Facility. Written reports covering various aspects of the grant were submitted to the co-investigators for the grant. Research studies concentrated on the field of artificial intelligence knowledge-based systems technology. Activities included the following areas: (1) AI training classes; (2) merging optical and digital processing; (3) science experiment remote coaching; (4) SSF data management system tests; (5) computer integrated documentation project; (6) conservation of design knowledge project; (7) project management calendar and reporting system; (8) automation and robotics technology assessment; (9) advanced computer architectures and operating systems; and (10) honors program.
This paper describes a concept for future high-density, terminal air traffic operations that has been developed by interpreting the Joint Planning and Development Office s vision for the Next Generation (NextGen) Air Transportation System and coupling it with emergent NASA and other technologies and procedures during the NextGen timeframe. The concept described in this paper includes five core capabilities: 1) Extended Terminal Area Routing, 2) Precision Scheduling Along Routes, 3) Merging and Spacing, 4) Tactical Separation, and 5) Off-Nominal Recovery. Gradual changes are introduced to the National Airspace System (NAS) by phased enhancements to the core capabilities in the form of increased levels of automation and decision support as well as targeted task delegation. NASA will be evaluating these conceptual technological enhancements in a series of human-in-the-loop simulations and will accelerate development of the most promising capabilities in cooperation with the FAA through the Efficient Flows Into Congested Airspace Research Transition Team.
The Center TRACON Automation System (CTAS) is a new support system that is designed to assist air traffic controllers in the management of arrival traffic. CTAS will provide controllers with more information about current air traffic, enabling them to provide clearances for efficient, conflict-free descents that help achieve an orderly stream of aircraft at the final approach fix. CTAS is a computer-based system that functions as a "ground-based FMS" that can predict flight trajectories and arrival times for all incoming aircraft. CTAS uses an aircraft's cruise airspeed; current air traffic, winds and temperature; performance characteristics of the aircraft type; and individual airline preferences to create a flight profile from cruise altitude to the final approach fix. Controllers can use this flight profile to provide a descent clearance that will allow an aircraft to fly an efficient descent and merge more smoothly with other arriving aircraft. A field test of the CTAS Descent Advisor software was conducted at the Denver Center for aircraft arriving at the Stapleton International Airport from September 12-29. CTAS Descent clearances were given to a NASA flight test aircraft and to 77 airline flights that arrived during low traffic periods. For the airline portion of the field test, cockpit procedures and pilot briefing packages for both FMS equipped and unequipped aircraft were developed in cooperation with an airline. The procedures developed for the FMS equipped aircraft were to fly a VNAV descent at a controller specified speed to cross a metering fix at a specified altitude and speed. For nonFMS aircraft, the clearance also specified a CTAS calculated top-of-descent point. Some CTAS related flight deck issues included how much time was available to the pilots' for compliance, the amount of information that needed to be interpreted in the clearance and possible repercussions of misunderstandings. Data collected during the study ranged from subjective data (including the airline pilots' opinions and comments about the new descent clearances and procedures) to objective data (including observations of aircraft performance from the flight deck). This paper will present data and the resulting changes in the design of the procedures and clearance phraseology.