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At least 469 records · Page 26

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NASA NTRS2011

Router Agent Technology for Policy-Based Network Management

This innovation can be run as a standalone network application on any computer in a networked environment. This design can be configured to control one or more routers (one instance per router), and can also be configured to listen to a policy server over the network to receive new policies based on the policy- based network management technology. The Router Agent Technology transforms the received policies into suitable Access Control List syntax for the routers it is configured to control. It commits the newly generated access control lists to the routers and provides feedback regarding any errors that were faced. The innovation also automatically generates a time-stamped log file regarding all updates to the router it is configured to control. This technology, once installed on a local network computer and started, is autonomous because it has the capability to keep listening to new policies from the policy server, transforming those policies to router-compliant access lists, and committing those access lists to a specified interface on the specified router on the network with any error feedback regarding commitment process. The stand-alone application is named RouterAgent and is currently realized as a fully functional (version 1) implementation for the Windows operating system and for CISCO routers.

Chow, Edward T.↗

NASA NTRS2012

Using Agent Based Modeling (ABM) to Develop Cultural Interaction Simulations

Today, most cultural training is based on or built around "cultural engagements" or discrete interactions between the individual learner and one or more cultural "others". Often, success in the engagement is the end or the objective. In reality, these interactions usually involve secondary and tertiary effects with potentially wide ranging consequences. The concern is that learning culture within a strict engagement context might lead to "checklist" cultural thinking that will not empower learners to understand the full consequence of their actions. We propose the use of agent based modeling (ABM) to collect, store, and, simulating the effects of social networks, promulgate engagement effects over time, distance, and consequence. The ABM development allows for rapid modification to re-create any number of population types, extending the applicability of the model to any requirement for social modeling.

Drucker, Nick↗

NASA NTRS2012

A Model of Rapid Radicalization Behavior Using Agent-Based Modeling and Quorum Sensing

Understanding the dynamics of radicalization, especially rapid radicalization, has become increasingly important to US policy in the past several years. Traditionally, radicalization is considered a slow process, but recent social and political events demonstrate that the process can occur quickly. Examining this rapid process, in real time, is impossible. However, recreating an event using modeling and simulation (M&S) allows researchers to study some of the complex dynamics associated with rapid radicalization. We propose to adapt the biological mechanism of quorum sensing as a tool to explore, or possibly explain, rapid radicalization. Due to the complex nature of quorum sensing, M&S allows us to examine events that we could not otherwise examine in real time. For this study, we employ Agent Based Modeling (ABM), an M&S paradigm suited to modeling group behavior. The result of this study was the successful creation of rapid radicalization using quorum sensing. The Battle of Mogadishu was the inspiration for this model and provided the testing conditions used to explore quorum sensing and the ideas behind rapid radicalization. The final product has wider applicability however, using quorum sensing as a possible tool for examining other catalytic rapid radicalization events.

Schwartz, Noah↗

NASA NTRS2014

Model Checking Degrees of Belief in a System of Agents

Reasoning about degrees of belief has been investigated in the past by a number of authors and has a number of practical applications in real life. In this paper we present a unified framework to model and verify degrees of belief in a system of agents. In particular, we describe an extension of the temporal-epistemic logic CTLK and we introduce a semantics based on interpreted systems for this extension. In this way, degrees of beliefs do not need to be provided externally, but can be derived automatically from the possible executions of the system, thereby providing a computationally grounded formalism. We leverage the semantics to (a) construct a model checking algorithm, (b) investigate its complexity, (c) provide a Java implementation of the model checking algorithm, and (d) evaluate our approach using the standard benchmark of the dining cryptographers. Finally, we provide a detailed case study: using our framework and our implementation, we assess and verify the situational awareness of the pilot of Air France 447 flying in off-nominal conditions.

MAS Verification↗

NASA NTRS2014

Consensus-Based Formation Control of a Class of Multi-Agent Systems

This paper presents a consensus-based formation control scheme for autonomous multi-agent systems represented by double integrator dynamics. Assuming that the information graph topology consists of an undirected connected graph, a leader-based consensus-type control law is presented and shown to provide asymptotic formation stability when subjected to piecewise constant formation velocity commands. It is also shown that global asymptotic stability is preserved in the presence of (0, infinity)- sector monotonic non-decreasing actuator nonlinearities.

Joshi, Suresh↗

NASA NTRS2015

An Approach to Quantify Workload in a System of Agents

The role of humans in aviation and other domains continues to shift from manual control to automation monitoring. Studies have found that humans are often poorly suited for monitoring roles, and workload can easily spike in off-nominal situations. Current workload measurement tools, like NASA TLX, use human operators to assess their own workload after using a prototype system. Such measures are used late in the design process and can result in ex- pensive alterations when problems are discovered. Our goal in this work is to provide a quantitative workload measure for use early in the design process. We leverage research in human cognition to de ne metrics that can measure workload on belief-desire-intentions based multi-agent systems. These measures can alert designers to potential workload issues early in design. We demonstrate the utility of our approach by characterizing quantitative differences in the workload for a single pilot operations model compared to a traditional two pilot model.

Single Pilot Operations↗

NASA NTRS2016

FOST 2 Upgrade with Hollow-Fiber CTA FO Module and Generation of Osmotic Agent for Microorganism Growth Studies

FOST 2 is an integrated membrane system that incorporates a forward osmosis subsystem and a reverse osmosis subsystem working in series. It has been designed as a post treatment system to process the effluent from the Membrane Aerated Biological Reactor developed at NASA Johnson Space Center and Texas Tech University. Its function is to remove dissolved solids residual such as ammonia and suspended solids, as well as to provide a physical barrier to microbial and viral contamination. A tubular CTA membrane module from HTI and a flat-sheet lipid-base membrane module from Porifera were integrated and tested on FOST 2 in the past, using both a bioreactor's effluent and greywater as the feed solution. This paper documents the performance of FOST 2 after its upgrade with a hollow-fiber CTA membrane module from Toyobo, treating real black-water to generate the osmotic agent solution necessary to conduct growth studies of genetically engineered microorganism for the Synthetic Biological Membrane project.

Water treatment↗

NASA NTRS2016

Tholins as Coloring Agents on Pluto and Other Icy Solar System Bodies

Tholins are refractory organic solids of complex structure and high molecular weight, with a wide range of color ranging from yellow and orange to dark red, and through tan to black. They are made in the laboratory by energy deposition (photons or charged particles) in gases and ices containing the simple molecules (e.g., N2, CH4, CO) found in planetary atmospheres or condensed on planetary surfaces. They are widely implicated in providing the colors and albedos, particularly in the region 0.3-1.0 microns, of several outer Solar System bodies, including Pluto, as well as aerosols in planetary atmospheres such as Titan. Recent color images of Pluto with the New Horizons spacecraft show concentrations of coloring agent(s) in some regions of the surface, and apparent near-absence in other regions. Tholins that may to some degree represent surface chemistry on Pluto have been synthesized in the laboratory by energetic processing of mixtures of the ices (N2, CH4, CO) known on Pluto's surface, or the same molecules in the gas phase. Details of the composition and yield vary with experimental conditions. Chemical analysis of Pluto ice tholins shows evidence of amides, carboxylic acids, urea, carbodiimides, and nitriles. Aromatic/olefinic, amide, and other functional groups are identified in XANES analysis. The ice tholins produced by e- irradiation have a higher concentration of N than UV ice tholins, with N/C approx. 0.9 (versus approx. 0.5 for UV tholins) and O/C approx.0.2. Raman spectra of the electron tholin show a high degree of structural disorder, while strong UV fluorescence indicates a large aromatic content. EUV photolysis of a Pluto gaseous atmosphere analog yields pale yellow solids relatively transparent in the visual, and with aliphatic CH bonds prominent in IR spectra. This or similar material may be responsible for Pluto's hazes.

Tholins↗

NASA NTRS2017

Modeling Space Radiation with Radiomimetic Agent Bleomycin

Space radiation consists of proton and helium from solar particle events (SPE) and high energy heavy ions from galactic cosmic ray (GCR). This mixture of radiation with particles at different energy levels has different effects on biological systems. Currently, majority studies of radiation effects on human were based on single-source radiation due to the limitation of available method to model effects of space radiation on living organisms. While NASA Space Radiation Laboratory is working on advanced switches to make it possible to have a mixed field radiation with particles of different energies, the radiation source will be limited. Development of an easily available experimental model for studying effects of mixed field radiation could greatly speed up our progress in our understanding the molecular mechanisms of damage and responses from exposure to space radiation, and facilitate the discovery of protection and countermeasures against space radiation, which is critical for the mission to Mars. Bleomycin, a radiomimetic agent, has been widely used to study radiation induced DNA damage and cellular responses. Previously, bleomycin was often compared to low low Linear Energy Transfer (LET) gamma radiation without defined characteristics. Our recent work demonstrated that bleomycin could induce complex clustered DNA damage in human fibroblasts that is similar to DNA damage induced by high LET radiation. These type of DNA damage is difficult to repair and can be visualized by gamma-H2Ax staining weeks after the initial insult. The survival ratio between early and late plating of human fibroblasts after bleomycin treatment is between low LET and high LET radiation. Our results suggest that bleomycin induces DNA damage and other cellular stresses resembling those resulted from mixed field radiation with both low and high LET particles. We hypothesize that bleomycin could be used to mimic space radiation in biological systems. Potential advantages and limitations of using bleomycin to treat biological specimen as an easily available model to study effects of space radiation on biological systems and to develop countermeasures for space radiation associated risks will be discussed.

Lu, Tao↗

NASA NTRS2017

Time-Coordination Strategies and Control Laws for Multi-Agent Unmanned Systems

Time-critical coordination tools for unmanned systems can be employed to enforce the type of temporal constraints required in terminal control areas, ensure minimum distance requirements among vehicles are satisfied, and successfully perform coordinated missions. In comparison with previous literature, this paper presents an ampler spectrum of coordination and temporal specifications for unmanned systems, and proposes a general control law that can enforce this range of constraints. The constraint classification presented con- siders the nature of the desired arrival window and the permissible coordination errors to define six different types of time-coordination strategies. The resulting decentralized coordination control law allows the vehicles to negotiate their speeds along their paths in response to information exchanged over the communication network. This control law organizes the different members in the fleet hierarchically per their behavior and informational needs as reference agent, leaders, and followers. Examples and simulation results for all the coordination strategies presented demonstrate the applicability and efficacy of the coordination control law for multiple unmanned systems.

Puig-Navarro, Javier↗

NASA NTRS2019

The Shapeshifter: A Morphing, Multi-Agent, Multi-Modal Robotic Platform for the Exploration of Titan

In this report, we present a robotic platform, the Shapeshifter, that allows multi-domain and redundant mobility on Saturn's moon Titan - and potentially other bodies with atmospheres. The Shapeshifter is a collection of simple and a affordable robotic units, called Cobots, comparable to personal palm-size quadcopters. By attaching and detaching with each other, multiple Cobots can shape-shift into novel structures, capable of (a) rolling on a at surface, to increase the traverse range, (b) flying in a flight array formation, and (c) swimming on or under liquid. A ground station, called the Home-base, complements the robotic platform, hosting science instrumentation and providing power to recharge the batteries of the Cobots. Our Phase I study had the objective of providing an initial assessment of the feasibility of the proposed robotic platform architecture, and in particular (a) to characterize the expected science return of a mission to the Sotra-Patera region on Titan; (b) to verify the mechanical and algorithmic feasibility of building a multi-agent platform capable of flying, docking, rolling and un-docking; (c) to evaluate the increased range and efficiency of rolling on Titan w.r.t to flying; (d) to define a case-study of a mission for the exploration of the cryovolcano Sotra-Patera on Titan, whose expected variety of geological features challenges conventional mobility platforms.

Agha-mohammadi, Ali-akbar↗

NASA NTRS2020

Design of Autonomous Medical Response Agent (AMRA) Aggregate Information Dashboard (AID)

Future astronauts in deep space missions will rely on tools and technologies empowering them to self-diagnose and self-treat medical conditions. Given communications delays and limited bandwidth in future long-duration exploration missions (LDEMs), medical decision support technologies must empower the crew to manage routine medical activities, acute medical incidents, as well as emergency medical scenarios independently from ground support.The Autonomous Medical Response Agent (AMRA) is envisioned as a digital tool enabling crew to issue medical complaints and interact with a medical decision support algorithm which develops a differential diagnosis and recommends a treatment protocol for the condition. AMRA will draw from individual crew medical history in addition to crew symptoms to more efficiently identify high-risk medical conditions. A new symptom could be indicative of a chronic condition or a normal adaptation to long-duration spaceflight, but could just as easily be indicative of an adverse vehicle condition affecting the entire crew.While real-time communication with a flight surgeon may not possible, the crew will nonetheless require a means to communicate and document both routine and emergency medical incidents to ground support. Conversely, flight surgeons and medical specialists on the ground will need to understand information such as crew vitals or responses to medical check-ups and examinations within the larger context of crew schedule, mission activities, and vehicle performance. A user interface which establishes communication protocols between an individual crew member and AMRA, as well as ground support to the crew is a significant area of research demanding input and consideration.The design of AMRA AID is intended to: a) represent routine medical activities as well as new (unplanned) medical incidents within the larger context of crew schedule and mission activities, and b) increase confidence between ground support and crew members over the course of LDEMs. Maintaining situation awareness of unplanned medical incidents between ground and crew will be a critical element within LDEMs. Two medical incidents headache and difficulty breathing are being explored within a user interface prototype which captures communications protocols between crew members and mission control, human health monitoring, vehicle or environmental monitoring, as well as crew schedule and mission activities holistically.

Yashar, M.↗

NASA NTRS2020

Freeze-Thaw Cycling as a Chemical Weathering Agent on a Cold and Icy Mars

Liquid water was abundant on early Mars, but whether the climate was warm and wet or cold and icy with punctuated periods of melting is still poorly understood. Modern climate models for Mars tend to predict a colder, icier early climate than previously imagined. In addition, ice and glaciation have been major geologic agents throughout the later Hesperian and Amazonian eras. One process that can act in such climates is repeated freezing and thawing of water on the surface and in the subsurface, and is significant because it can occur anywhere with an active layer and could have persisted for a time after liquid water was no longer stable on Mars’ surface. As freeze-thaw is the dominant mechanical weathering process in most glacial/periglacial terrains, it was likely a significant geomorphologic driver at local to regional scales during past climates, and would potentially have been most active when day-average surface temperatures exceeded 0 °C for part of the year. Indeed, freeze-thaw involving liquid water in the Amazonian is evidenced by abundant geomorphic features including polygonal ground and solifluction lobes requiring seasonal thawing. In addition to physical modification, freezing can drive solutions towards supersaturation and force dissolved solutes out as precipitates. In Mars-like terrains, dissolved solutes are typically dominated by silica. In polar regions on Earth, freeze-thaw cycles have been shown to promote deposition of silica, and freeze-thaw experiments on synthetic solutions found stable amorphous silica that built up over multiple cycles. Freeze-thaw may therefore be an important but overlooked chemical weathering process on Mars. However, our ability to assess its impact on alteration of martian terrains is majorly limited by the current lack of understanding of the alteration phases produced (and formation rates) under controlled freeze-thaw weathering of Mars-relevant materials. To address this knowledge gap, we report results from (1) freeze-thaw weathering products found at a glacial Mars analog site at the Three Sisters, Oregon, and (2) new controlled freeze-thaw experiments on basaltic material.

Scudder, N. A.↗

NASA NTRS2020

Optimal Multi-Agent Search and Rescue Using Potential Field Theory

This paper presents an algorithm for efficient search and rescue using a multi-agent system of vehicles. The algorithm uses an artificial potential field combined with a time-varying reward function for visiting various points within the search area. The reward function is used to weight the attractiveness of these points in the potential field, and collision avoidance terms are used to repel vehicles from each other, which has the additional effect of reducing duplication of searching efforts. The algorithm generates velocity commands in real-time based on communication with the other vehicles. This framework allows vehicles to react in a dynamic environment, which is a significant advantage to simply following a-priori defined trajectories. Simulation results are presented to demonstrate the ability of the algorithm to cover the search area effectively. The algorithm is also compared to an exhaustive lawn-mower search pattern. This comparison is done via a Monte Carlo simulation with randomized target initial conditions and trajectories. The time to find the target improved by 16 and 30% in the mean and median, respectively. Additionally, this paper presents a method for analyzing the upper bound for time to find a target under the potential field guidance algorithm assuming a radially expanding search area.

John R Cooper↗

NASA NTRSDate not supplied

A Distributed Simulation-to-Flight Framework to Support Investigating Trust/Trustworthiness in Multi-Agent Systems

As autonomous systems continue to grow both in use and complexity, the necessity for robust and extensible simulation-to-flight methods is paramount for establishing an effective architecture for autonomous systems. A fundamental objective of the ATTRACTOR (Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability) project was to design and develop a distributed mixed-reality simulation environment to begin establishing a basis for certification of autonomous systems via research into trust and trustworthiness. In this paper, we present an autonomous systems architecture and development framework paired with a persistent distributed modeling and simulation environment for test and evaluation of autonomous systems. The Autonomous Entity Operations Network (AEON) framework enables autonomous system development with an easily extensible collection of libraries and plug-n-play nodes facilitated by the Data Distribution Service (DDS) communication protocol standard. The Baseline Environment for Autonomous Modeling (BEAM) simulation environment is a distributed mixed-reality Unity™-based environment built around the same DDS communication paradigm allowing for easy integration with AEON-based autonomous applications. They were designed under ATTRACTOR in order to measure and establish trustworthiness and trust in single- and multi-agent human-machine systems whether these machines are fixed-wing general aviation, rotary-wing Unmanned Aerial Vehicles (UAVs), ground rovers, or even spacecraft. Together AEON and BEAM enable sim-to-flight with minimal configuration changes. By using AEON and BEAM, source code that runs in simulation ports directly to hardware and has successfully flown in the lab and in the National Airspace System (NAS) at NASA LaRC many times over the lifetime of ATTRACTOR.

Benjamin N Kelley↗

NASA NTRSDate not supplied

Synthetic Data Generation for 3D Mesh Prediction and Spatial Reasoning During Multi-Agent Robotic Missions

In-space assembly operations require accurate reasoning over the pose, location, and structural organization of both the autonomous agents and assembly materials. In a full six-degree-of-freedom space, an accurate understanding of the full three-dimensional structure of the object of interest greatly enriches information for pose estimation and collision planning. Current methods of predicting pose estimation require a priori understanding of the shape of the object. Additionally, visual information in the space environment is impacted by variations in contrast and illumination. Using synthetic data allows us to rapidly generate large datasets with in varying environments and lighting conditions.This work details the generation of synthetic data used to explore the use of a region-based convolutional neural networks to detect objects of interest and predict a voxel-based three-dimensional mesh in order to understand their full three-dimensional shape. This mesh provides useful spatial information during in-space assembly operations without requiring either the complexity of maintaining models over the progress of building an object or observations from multiple angles. The generated meshes are then compared to that of ground truth in order to measure its performance.

synthetic data↗

NASA NTRSDate not supplied

A Distributed Simulation-to-Flight Framework to Support Investigating Trust/Trustworthiness in Multi-Agent Systems

Benjamin N Kelley↗

NASA NTRSDate not supplied

Synthetic Data Generation for 3D Mesh Prediction and Spatial Reasoning During Multi-Agent Robotic Missions

In-space assembly operations require accurate reasoning over the pose, location, and structural organization of both the autonomous agents and assembly materials. In a full six-degree-of-freedom space, an accurate understanding of the full three-dimensional structure of the object of interest greatly enriches information for pose estimation and collision planning. Current methods of predicting pose estimation require a priori understanding of the shape of the object. Additionally, visual information in the space environment is impacted by variations in contrast and illumination. Using synthetic data allows us to rapidly generate large datasets with in varying environments and lighting conditions. This work details the generation of synthetic data used to explore the use of a region-based convolutional neural networks to detect objects of interest and predict a voxel-based three-dimensional mesh in order to understand their full three-dimensional shape. This mesh provides useful spatial information during in-space assembly operations without requiring either the complexity of maintaining models over the progress of building an object or observations from multiple angles. The generated meshes are then compared to that of ground truth in order to measure its performance.

James Ecker↗