On the structure of attractors for discrete, periodically forced systems with applications to population models

Treesearch

James F. Selgrade; James H. Roberds

2001-01-01

This work discusses the effects of periodic forcing on attracting cycles and more complicated attractors for autonomous systems of nonlinear difference equations. Results indicate that an attractor for a periodically forced dynamical system may inherit structure from an attractor of the autonomous (unforced) system and also from the periodicity of the forcing. In...

Numerical simulation of active track tensioning system for autonomous hybrid vehicle

NASA Astrophysics Data System (ADS)

Mȩżyk, Arkadiusz; Czapla, Tomasz; Klein, Wojciech; Mura, Gabriel

2017-05-01

One of the most important components of a high speed tracked vehicle is an efficient suspension system. The vehicle should be able to operate both in rough terrain for performance of engineering tasks as well as on the road with high speed. This is especially important for an autonomous platform that operates either with or without human supervision, so that the vibration level can rise compared to a manned vehicle. In this case critical electronic and electric parts must be protected to ensure the reliability of the vehicle. The paper presents a dynamic parameters determination methodology of suspension system for an autonomous high speed tracked platform with total weight of about 5 tonnes and hybrid propulsion system. Common among tracked vehicles suspension solutions and cost-efficient, the torsion-bar system was chosen. One of the most important issues was determining optimal track tensioning - in this case an active hydraulic system was applied. The selection of system parameters was performed with using numerical model based on multi-body dynamic approach. The results of numerical analysis were used to define parameters of active tensioning control system setup. LMS Virtual.Lab Motion was used for multi-body dynamics numerical calculation and Matlab/SIMULINK for control system simulation.

Autonomous and Autonomic Systems: A Paradigm for Future Space Exploration Missions

NASA Technical Reports Server (NTRS)

Truszkowski, Walter F.; Hinchey, Michael G.; Rash, James L.; Rouff, Christopher A.

2004-01-01

NASA increasingly will rely on autonomous systems concepts, not only in the mission control centers on the ground, but also on spacecraft and on rovers and other assets on extraterrestrial bodies. Automomy enables not only reduced operations costs, But also adaptable goal-driven functionality of mission systems. Space missions lacking autonomy will be unable to achieve the full range of advanced mission objectives, given that human control under dynamic environmental conditions will not be feasible due, in part, to the unavoidably high signal propagation latency and constrained data rates of mission communications links. While autonomy cost-effectively supports accomplishment of mission goals, autonomicity supports survivability of remote mission assets, especially when human tending is not feasible. Autonomic system properties (which ensure self-configuring, self-optimizing self-healing, and self-protecting behavior) conceptually may enable space missions of a higher order into any previously flown. Analysis of two NASA agent-based systems previously prototyped, and of a proposed future mission involving numerous cooperating spacecraft, illustrates how autonomous and autonomic system concepts may be brought to bear on future space missions.

Attractors for discrete periodic dynamical systems

Treesearch

John E. Franke; James F. Selgrade

2003-01-01

A mathematical framework is introduced to study attractors of discrete, nonautonomous dynamical systems which depend periodically on time. A structure theorem for such attractors is established which says that the attractor of a time-periodic dynamical system is the unin of attractors of appropriate autonomous maps. If the nonautonomous system is a perturbation of an...

Random attractor of non-autonomous stochastic Boussinesq lattice system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Min, E-mail: zhaomin1223@126.com; Zhou, Shengfan, E-mail: zhoushengfan@yahoo.com

2015-09-15

In this paper, we first consider the existence of tempered random attractor for second-order non-autonomous stochastic lattice dynamical system of nonlinear Boussinesq equations effected by time-dependent coupled coefficients and deterministic forces and multiplicative white noise. Then, we establish the upper semicontinuity of random attractors as the intensity of noise approaches zero.

Enabling Autonomous Rover Science through Dynamic Planning and Scheduling

NASA Technical Reports Server (NTRS)

Estlin, Tara A.; Gaines, Daniel; Chouinard, Caroline; Fisher, Forest; Castano, Rebecca; Judd, Michele; Nesnas, Issa

2005-01-01

This paper describes how dynamic planning and scheduling techniques can be used onboard a rover to autonomously adjust rover activities in support of science goals. These goals could be identified by scientists on the ground or could be identified by onboard data-analysis software. Several different types of dynamic decisions are described, including the handling of opportunistic science goals identified during rover traverses, preserving high priority science targets when resources, such as power, are unexpectedly over-subscribed, and dynamically adding additional, ground-specified science targets when rover actions are executed more quickly than expected. After describing our specific system approach, we discuss some of the particular challenges we have examined to support autonomous rover decision-making. These include interaction with rover navigation and path-planning software and handling large amounts of uncertainty in state and resource estimations.

Supervised autonomous robotic soft tissue surgery.

PubMed

Shademan, Azad; Decker, Ryan S; Opfermann, Justin D; Leonard, Simon; Krieger, Axel; Kim, Peter C W

2016-05-04

The current paradigm of robot-assisted surgeries (RASs) depends entirely on an individual surgeon's manual capability. Autonomous robotic surgery-removing the surgeon's hands-promises enhanced efficacy, safety, and improved access to optimized surgical techniques. Surgeries involving soft tissue have not been performed autonomously because of technological limitations, including lack of vision systems that can distinguish and track the target tissues in dynamic surgical environments and lack of intelligent algorithms that can execute complex surgical tasks. We demonstrate in vivo supervised autonomous soft tissue surgery in an open surgical setting, enabled by a plenoptic three-dimensional and near-infrared fluorescent (NIRF) imaging system and an autonomous suturing algorithm. Inspired by the best human surgical practices, a computer program generates a plan to complete complex surgical tasks on deformable soft tissue, such as suturing and intestinal anastomosis. We compared metrics of anastomosis-including the consistency of suturing informed by the average suture spacing, the pressure at which the anastomosis leaked, the number of mistakes that required removing the needle from the tissue, completion time, and lumen reduction in intestinal anastomoses-between our supervised autonomous system, manual laparoscopic surgery, and clinically used RAS approaches. Despite dynamic scene changes and tissue movement during surgery, we demonstrate that the outcome of supervised autonomous procedures is superior to surgery performed by expert surgeons and RAS techniques in ex vivo porcine tissues and in living pigs. These results demonstrate the potential for autonomous robots to improve the efficacy, consistency, functional outcome, and accessibility of surgical techniques. Copyright © 2016, American Association for the Advancement of Science.

The NASA/Army Autonomous Rotorcraft Project

NASA Technical Reports Server (NTRS)

Whalley, M.; Freed, M.; Takahashi, M.; Christian, D.; Patterson-Hine, A.; Schulein, G.; Harris, R.

2002-01-01

An overview of the NASA Ames Research Center Autonomous Rotorcraft Project (ARP) is presented. The project brings together several technologies to address NASA and US Army autonomous vehicle needs, including a reactive planner for mission planning and execution, control system design incorporating a detailed understanding of the platform dynamics, and health monitoring and diagnostics. A candidate reconnaissance and surveillance mission is described. The autonomous agent architecture and its application to the candidate mission are presented. Details of the vehicle hardware and software development are provided.

Using Multimodal Input for Autonomous Decision Making for Unmanned Systems

NASA Technical Reports Server (NTRS)

Neilan, James H.; Cross, Charles; Rothhaar, Paul; Tran, Loc; Motter, Mark; Qualls, Garry; Trujillo, Anna; Allen, B. Danette

2016-01-01

Autonomous decision making in the presence of uncertainly is a deeply studied problem space particularly in the area of autonomous systems operations for land, air, sea, and space vehicles. Various techniques ranging from single algorithm solutions to complex ensemble classifier systems have been utilized in a research context in solving mission critical flight decisions. Realized systems on actual autonomous hardware, however, is a difficult systems integration problem, constituting a majority of applied robotics development timelines. The ability to reliably and repeatedly classify objects during a vehicles mission execution is vital for the vehicle to mitigate both static and dynamic environmental concerns such that the mission may be completed successfully and have the vehicle operate and return safely. In this paper, the Autonomy Incubator proposes and discusses an ensemble learning and recognition system planned for our autonomous framework, AEON, in selected domains, which fuse decision criteria, using prior experience on both the individual classifier layer and the ensemble layer to mitigate environmental uncertainty during operation.

A forward model-based validation of cardiovascular system identification

NASA Technical Reports Server (NTRS)

Mukkamala, R.; Cohen, R. J.

2001-01-01

We present a theoretical evaluation of a cardiovascular system identification method that we previously developed for the analysis of beat-to-beat fluctuations in noninvasively measured heart rate, arterial blood pressure, and instantaneous lung volume. The method provides a dynamical characterization of the important autonomic and mechanical mechanisms responsible for coupling the fluctuations (inverse modeling). To carry out the evaluation, we developed a computational model of the cardiovascular system capable of generating realistic beat-to-beat variability (forward modeling). We applied the method to data generated from the forward model and compared the resulting estimated dynamics with the actual dynamics of the forward model, which were either precisely known or easily determined. We found that the estimated dynamics corresponded to the actual dynamics and that this correspondence was robust to forward model uncertainty. We also demonstrated the sensitivity of the method in detecting small changes in parameters characterizing autonomic function in the forward model. These results provide confidence in the performance of the cardiovascular system identification method when applied to experimental data.

Planning and Execution for an Autonomous Aerobot

NASA Technical Reports Server (NTRS)

Gaines, Daniel M.; Estlin, Tara A.; Schaffer, Steven R.; Chouinard, Caroline M.

2010-01-01

The Aerial Onboard Autonomous Science Investigation System (AerOASIS) system provides autonomous planning and execution capabilities for aerial vehicles (see figure). The system is capable of generating high-quality operations plans that integrate observation requests from ground planning teams, as well as opportunistic science events detected onboard the vehicle while respecting mission and resource constraints. AerOASIS allows an airborne planetary exploration vehicle to summarize and prioritize the most scientifically relevant data; identify and select high-value science sites for additional investigation; and dynamically plan, schedule, and monitor the various science activities being performed, even during extended communications blackout periods with Earth.

KAM tori and whiskered invariant tori for non-autonomous systems

NASA Astrophysics Data System (ADS)

Canadell, Marta; de la Llave, Rafael

2015-08-01

We consider non-autonomous dynamical systems which converge to autonomous (or periodic) systems exponentially fast in time. Such systems appear naturally as models of many physical processes affected by external pulses. We introduce definitions of non-autonomous invariant tori and non-autonomous whiskered tori and their invariant manifolds and we prove their persistence under small perturbations, smooth dependence on parameters and several geometric properties (if the systems are Hamiltonian, the tori are Lagrangian manifolds). We note that such definitions are problematic for general time-dependent systems, but we show that they are unambiguous for systems converging exponentially fast to autonomous. The proof of persistence relies only on a standard Implicit Function Theorem in Banach spaces and it does not require that the rotations in the tori are Diophantine nor that the systems we consider preserve any geometric structure. We only require that the autonomous system preserves these objects. In particular, when the autonomous system is integrable, we obtain the persistence of tori with rational rotational. We also discuss fast and efficient algorithms for their computation. The method also applies to infinite dimensional systems which define a good evolution, e.g. PDE's. When the systems considered are Hamiltonian, we show that the time dependent invariant tori are isotropic. Hence, the invariant tori of maximal dimension are Lagrangian manifolds. We also obtain that the (un)stable manifolds of whiskered tori are Lagrangian manifolds. We also include a comparison with the more global theory developed in Blazevski and de la Llave (2011).

Computational Fluid Dynamics of the Boundary Layer Characteristics of a Pacific Bluefin Tuna

DTIC Science & Technology

2015-09-18

17  LIST OF ABBREVIATIONS AND ACRONYMS 2D Two Dimensional 3D Three Dimensional AUV Autonomous...Finally, this research has the potential to advance technology of various Navy systems, e.g., torpedo and autonomous underwater vehicle ( AUV ) drag

Autonomic Management in a Distributed Storage System

NASA Astrophysics Data System (ADS)

Tauber, Markus

2010-07-01

This thesis investigates the application of autonomic management to a distributed storage system. Effects on performance and resource consumption were measured in experiments, which were carried out in a local area test-bed. The experiments were conducted with components of one specific distributed storage system, but seek to be applicable to a wide range of such systems, in particular those exposed to varying conditions. The perceived characteristics of distributed storage systems depend on their configuration parameters and on various dynamic conditions. For a given set of conditions, one specific configuration may be better than another with respect to measures such as resource consumption and performance. Here, configuration parameter values were set dynamically and the results compared with a static configuration. It was hypothesised that under non-changing conditions this would allow the system to converge on a configuration that was more suitable than any that could be set a priori. Furthermore, the system could react to a change in conditions by adopting a more appropriate configuration. Autonomic management was applied to the peer-to-peer (P2P) and data retrieval components of ASA, a distributed storage system. The effects were measured experimentally for various workload and churn patterns. The management policies and mechanisms were implemented using a generic autonomic management framework developed during this work. The experimental evaluations of autonomic management show promising results, and suggest several future research topics. The findings of this thesis could be exploited in building other distributed storage systems that focus on harnessing storage on user workstations, since these are particularly likely to be exposed to varying, unpredictable conditions.

Recurrent myocardial infarction: Mechanisms of free-floating adaptation and autonomic derangement in networked cardiac neural control.

PubMed

Kember, Guy; Ardell, Jeffrey L; Shivkumar, Kalyanam; Armour, J Andrew

2017-01-01

The cardiac nervous system continuously controls cardiac function whether or not pathology is present. While myocardial infarction typically has a major and catastrophic impact, population studies have shown that longer-term risk for recurrent myocardial infarction and the related potential for sudden cardiac death depends mainly upon standard atherosclerotic variables and autonomic nervous system maladaptations. Investigative neurocardiology has demonstrated that autonomic control of cardiac function includes local circuit neurons for networked control within the peripheral nervous system. The structural and adaptive characteristics of such networked interactions define the dynamics and a new normal for cardiac control that results in the aftermath of recurrent myocardial infarction and/or unstable angina that may or may not precipitate autonomic derangement. These features are explored here via a mathematical model of cardiac regulation. A main observation is that the control environment during pathology is an extrapolation to a setting outside prior experience. Although global bounds guarantee stability, the resulting closed-loop dynamics exhibited while the network adapts during pathology are aptly described as 'free-floating' in order to emphasize their dependence upon details of the network structure. The totality of the results provide a mechanistic reasoning that validates the clinical practice of reducing sympathetic efferent neuronal tone while aggressively targeting autonomic derangement in the treatment of ischemic heart disease.

Dual-Schemata Model

NASA Astrophysics Data System (ADS)

Taniguchi, Tadahiro; Sawaragi, Tetsuo

In this paper, a new machine-learning method, called Dual-Schemata model, is presented. Dual-Schemata model is a kind of self-organizational machine learning methods for an autonomous robot interacting with an unknown dynamical environment. This is based on Piaget's Schema model, that is a classical psychological model to explain memory and cognitive development of human beings. Our Dual-Schemata model is developed as a computational model of Piaget's Schema model, especially focusing on sensori-motor developing period. This developmental process is characterized by a couple of two mutually-interacting dynamics; one is a dynamics formed by assimilation and accommodation, and the other dynamics is formed by equilibration and differentiation. By these dynamics schema system enables an agent to act well in a real world. This schema's differentiation process corresponds to a symbol formation process occurring within an autonomous agent when it interacts with an unknown, dynamically changing environment. Experiment results obtained from an autonomous facial robot in which our model is embedded are presented; an autonomous facial robot becomes able to chase a ball moving in various ways without any rewards nor teaching signals from outside. Moreover, emergence of concepts on the target movements within a robot is shown and discussed in terms of fuzzy logics on set-subset inclusive relationships.

Autonomous learning by simple dynamical systems with a discrete-time formulation

NASA Astrophysics Data System (ADS)

Bilen, Agustín M.; Kaluza, Pablo

2017-05-01

We present a discrete-time formulation for the autonomous learning conjecture. The main feature of this formulation is the possibility to apply the autonomous learning scheme to systems in which the errors with respect to target functions are not well-defined for all times. This restriction for the evaluation of functionality is a typical feature in systems that need a finite time interval to process a unit piece of information. We illustrate its application on an artificial neural network with feed-forward architecture for classification and a phase oscillator system with synchronization properties. The main characteristics of the discrete-time formulation are shown by constructing these systems with predefined functions.

Steady states and outbreaks of two-phase nonlinear age-structured model of population dynamics with discrete time delay.

PubMed

Akimenko, Vitalii; Anguelov, Roumen

2017-12-01

In this paper we study the nonlinear age-structured model of a polycyclic two-phase population dynamics including delayed effect of population density growth on the mortality. Both phases are modelled as a system of initial boundary values problem for semi-linear transport equation with delay and initial problem for nonlinear delay ODE. The obtained system is studied both theoretically and numerically. Three different regimes of population dynamics for asymptotically stable states of autonomous systems are obtained in numerical experiments for the different initial values of population density. The quasi-periodical travelling wave solutions are studied numerically for the autonomous system with the different values of time delays and for the system with oscillating death rate and birth modulus. In both cases it is observed three types of travelling wave solutions: harmonic oscillations, pulse sequence and single pulse.

Enhancing Autonomy of Aerial Systems Via Integration of Visual Sensors into Their Avionics Suite

DTIC Science & Technology

2016-09-01

aerial platform for subsequent visual sensor integration. 14. SUBJECT TERMS autonomous system, quadrotors, direct method, inverse ...CONTROLLER ARCHITECTURE .....................................................43 B. INVERSE DYNAMICS IN THE VIRTUAL DOMAIN ......................45 1...control station GPS Global-Positioning System IDVD inverse dynamics in the virtual domain ILP integer linear program INS inertial-navigation system

Recent CESAR (Center for Engineering Systems Advanced Research) research activities in sensor based reasoning for autonomous machines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pin, F.G.; de Saussure, G.; Spelt, P.F.

1988-01-01

This paper describes recent research activities at the Center for Engineering Systems Advanced Research (CESAR) in the area of sensor based reasoning, with emphasis being given to their application and implementation on our HERMIES-IIB autonomous mobile vehicle. These activities, including navigation and exploration in a-priori unknown and dynamic environments, goal recognition, vision-guided manipulation and sensor-driven machine learning, are discussed within the framework of a scenario in which an autonomous robot is asked to navigate through an unknown dynamic environment, explore, find and dock at the panel, read and understand the status of the panel's meters and dials, learn the functioningmore » of a process control panel, and successfully manipulate the control devices of the panel to solve a maintenance emergency problems. A demonstration of the successful implementation of the algorithms on our HERMIES-IIB autonomous robot for resolution of this scenario is presented. Conclusions are drawn concerning the applicability of the methodologies to more general classes of problems and implications for future work on sensor-driven reasoning for autonomous robots are discussed. 8 refs., 3 figs.« less

Autonomous Multi-Sensor Coordination: The Science Goal Monitor

NASA Technical Reports Server (NTRS)

Koratkar, Anuradha; Grosvenor, Sandy; Jung, John; Hess, Melissa; Jones, Jeremy

2004-01-01

Many dramatic earth phenomena are dynamic and coupled. In order to fully understand them, we need to obtain timely coordinated multi-sensor observations from widely dispersed instruments. Such a dynamic observing system must include the ability to Schedule flexibly and react autonomously to sciencehser driven events; Understand higher-level goals of a sciencehser defined campaign; Coordinate various space-based and ground-based resources/sensors effectively and efficiently to achieve goals. In order to capture transient events, such a 'sensor web' system must have an automated reactive capability built into its scientific operations. To do this, we must overcome a number of challenges inherent in infusing autonomy. The Science Goal Monitor (SGM) is a prototype software tool being developed to explore the nature of automation necessary to enable dynamic observing. The tools being developed in SGM improve our ability to autonomously monitor multiple independent sensors and coordinate reactions to better observe dynamic phenomena. The SGM system enables users to specify what to look for and how to react in descriptive rather than technical terms. The system monitors streams of data to identify occurrences of the key events previously specified by the scientisther. When an event occurs, the system autonomously coordinates the execution of the users' desired reactions between different sensors. The information can be used to rapidly respond to a variety of fast temporal events. Investigators will no longer have to rely on after-the-fact data analysis to determine what happened. Our paper describes a series of prototype demonstrations that we have developed using SGM and NASA's Earth Observing-1 (EO-1) satellite and Earth Observing Systems' Aqua/Terra spacecrafts' MODIS instrument. Our demonstrations show the promise of coordinating data from different sources, analyzing the data for a relevant event, autonomously updating and rapidly obtaining a follow-on relevant image. SGM was used to investigate forest fires, floods and volcanic eruptions. We are now identifying new Earth science scenarios that will have more complex SGM reasoning. By developing and testing a prototype in an operational environment, we are also establishing and gathering metrics to gauge the success of automating science campaigns.

Autonomous satellite navigation with the Global Positioning System

NASA Technical Reports Server (NTRS)

Fuchs, A. J.; Wooden, W. H., II; Long, A. C.

1977-01-01

This paper discusses the potential of using the Global Positioning System (GPS) to provide autonomous navigation capability to NASA satellites in the 1980 era. Some of the driving forces motivating autonomous navigation are presented. These include such factors as advances in attitude control systems, onboard science annotation, and onboard gridding of imaging data. Simulation results which demonstrate baseline orbit determination accuracies using GPS data on Seasat, Landsat-D, and the Solar Maximum Mission are presented. Emphasis is placed on identifying error sources such as GPS time, GPS ephemeris, user timing biases, and user orbit dynamics, and in a parametric sense on evaluating their contribution to the orbit determination accuracies.

Autonomous control of roving vehicles for unmanned exploration of the planets

NASA Technical Reports Server (NTRS)

Yerazunis, S. W.

1978-01-01

The guidance of an autonomous rover for unmanned planetary exploration using a short range (0.5 - 3.0 meter) hazard detection system was studied. Experimental data derived from a one laser/one detector system were used in the development of improved algorithms for the guidance of the rover. The new algorithms which account for the dynamic characteristics of the Rensselaer rover can be applied to other rover concepts provided that the rover dynamic parameters are modified appropriately. The new algorithms will also be applicable to the advanced scanning system. The design of an elevation scanning laser/multisensor hazard detection system was completed. All mechanical and electronic hardware components with the exception of the sensor optics and electronic components were constructed and tested.

Mathematical biomarkers for the autonomic regulation of cardiovascular system.

PubMed

Campos, Luciana A; Pereira, Valter L; Muralikrishna, Amita; Albarwani, Sulayma; Brás, Susana; Gouveia, Sónia

2013-10-07

Heart rate and blood pressure are the most important vital signs in diagnosing disease. Both heart rate and blood pressure are characterized by a high degree of short term variability from moment to moment, medium term over the normal day and night as well as in the very long term over months to years. The study of new mathematical algorithms to evaluate the variability of these cardiovascular parameters has a high potential in the development of new methods for early detection of cardiovascular disease, to establish differential diagnosis with possible therapeutic consequences. The autonomic nervous system is a major player in the general adaptive reaction to stress and disease. The quantitative prediction of the autonomic interactions in multiple control loops pathways of cardiovascular system is directly applicable to clinical situations. Exploration of new multimodal analytical techniques for the variability of cardiovascular system may detect new approaches for deterministic parameter identification. A multimodal analysis of cardiovascular signals can be studied by evaluating their amplitudes, phases, time domain patterns, and sensitivity to imposed stimuli, i.e., drugs blocking the autonomic system. The causal effects, gains, and dynamic relationships may be studied through dynamical fuzzy logic models, such as the discrete-time model and discrete-event model. We expect an increase in accuracy of modeling and a better estimation of the heart rate and blood pressure time series, which could be of benefit for intelligent patient monitoring. We foresee that identifying quantitative mathematical biomarkers for autonomic nervous system will allow individual therapy adjustments to aim at the most favorable sympathetic-parasympathetic balance.

Mathematical biomarkers for the autonomic regulation of cardiovascular system

PubMed Central

Campos, Luciana A.; Pereira, Valter L.; Muralikrishna, Amita; Albarwani, Sulayma; Brás, Susana; Gouveia, Sónia

2013-01-01

Heart rate and blood pressure are the most important vital signs in diagnosing disease. Both heart rate and blood pressure are characterized by a high degree of short term variability from moment to moment, medium term over the normal day and night as well as in the very long term over months to years. The study of new mathematical algorithms to evaluate the variability of these cardiovascular parameters has a high potential in the development of new methods for early detection of cardiovascular disease, to establish differential diagnosis with possible therapeutic consequences. The autonomic nervous system is a major player in the general adaptive reaction to stress and disease. The quantitative prediction of the autonomic interactions in multiple control loops pathways of cardiovascular system is directly applicable to clinical situations. Exploration of new multimodal analytical techniques for the variability of cardiovascular system may detect new approaches for deterministic parameter identification. A multimodal analysis of cardiovascular signals can be studied by evaluating their amplitudes, phases, time domain patterns, and sensitivity to imposed stimuli, i.e., drugs blocking the autonomic system. The causal effects, gains, and dynamic relationships may be studied through dynamical fuzzy logic models, such as the discrete-time model and discrete-event model. We expect an increase in accuracy of modeling and a better estimation of the heart rate and blood pressure time series, which could be of benefit for intelligent patient monitoring. We foresee that identifying quantitative mathematical biomarkers for autonomic nervous system will allow individual therapy adjustments to aim at the most favorable sympathetic-parasympathetic balance. PMID:24109456

Issues in the design of an executive controller shell for Space Station automation

NASA Technical Reports Server (NTRS)

Erickson, William K.; Cheeseman, Peter C.

1986-01-01

A major goal of NASA's Systems Autonomy Demonstration Project is to focus research in artificial intelligence, human factors, and dynamic control systems in support of Space Station automation. Another goal is to demonstrate the use of these technologies in real space systems, for both round-based mission support and on-board operations. The design, construction, and evaluation of an intelligent autonomous system shell is recognized as an important part of the Systems Autonomy research program. His paper describes autonomous systems and executive controllers, outlines how these intelligent systems can be utilized within the Space Station, and discusses a number of key design issues that have been raised during some preliminary work to develop an autonomous executive controller shell at NASA Ames Research Center.

Autonomous learning by simple dynamical systems with delayed feedback.

PubMed

Kaluza, Pablo; Mikhailov, Alexander S

2014-09-01

A general scheme for the construction of dynamical systems able to learn generation of the desired kinds of dynamics through adjustment of their internal structure is proposed. The scheme involves intrinsic time-delayed feedback to steer the dynamics towards the target performance. As an example, a system of coupled phase oscillators, which can, by changing the weights of connections between its elements, evolve to a dynamical state with the prescribed (low or high) synchronization level, is considered and investigated.

Recurrent myocardial infarction: Mechanisms of free-floating adaptation and autonomic derangement in networked cardiac neural control

PubMed Central

Ardell, Jeffrey L.; Shivkumar, Kalyanam; Armour, J. Andrew

2017-01-01

The cardiac nervous system continuously controls cardiac function whether or not pathology is present. While myocardial infarction typically has a major and catastrophic impact, population studies have shown that longer-term risk for recurrent myocardial infarction and the related potential for sudden cardiac death depends mainly upon standard atherosclerotic variables and autonomic nervous system maladaptations. Investigative neurocardiology has demonstrated that autonomic control of cardiac function includes local circuit neurons for networked control within the peripheral nervous system. The structural and adaptive characteristics of such networked interactions define the dynamics and a new normal for cardiac control that results in the aftermath of recurrent myocardial infarction and/or unstable angina that may or may not precipitate autonomic derangement. These features are explored here via a mathematical model of cardiac regulation. A main observation is that the control environment during pathology is an extrapolation to a setting outside prior experience. Although global bounds guarantee stability, the resulting closed-loop dynamics exhibited while the network adapts during pathology are aptly described as ‘free-floating’ in order to emphasize their dependence upon details of the network structure. The totality of the results provide a mechanistic reasoning that validates the clinical practice of reducing sympathetic efferent neuronal tone while aggressively targeting autonomic derangement in the treatment of ischemic heart disease. PMID:28692680

Dynamic characteristics of heart rate control by the autonomic nervous system in rats.

PubMed

Mizuno, Masaki; Kawada, Toru; Kamiya, Atsunori; Miyamoto, Tadayoshi; Shimizu, Shuji; Shishido, Toshiaki; Smith, Scott A; Sugimachi, Masaru

2010-09-01

We estimated the transfer function of autonomic heart rate (HR) control by using random binary sympathetic or vagal nerve stimulation in anaesthetized rats. The transfer function from sympathetic stimulation to HR response approximated a second-order, low-pass filter with a lag time (gain, 4.29 +/- 1.55 beats min(1) Hz(1); natural frequency, 0.07 +/- 0.03 Hz; damping coefficient, 1.96 +/- 0.64; and lag time, 0.73 +/- 0.12 s). The transfer function from vagal stimulation to HR response approximated a first-order, low-pass filter with a lag time (gain, 8.84 +/- 4.51 beats min(1) Hz(1); corner frequency, 0.12 +/- 0.06 Hz; and lag time, 0.12 +/- 0.08 s). These results suggest that the dynamic characteristics of HR control by the autonomic nervous system in rats are similar to those of larger mammals.

Neural network regulation driven by autonomous neural firings

NASA Astrophysics Data System (ADS)

Cho, Myoung Won

2016-07-01

Biological neurons naturally fire spontaneously due to the existence of a noisy current. Such autonomous firings may provide a driving force for network formation because synaptic connections can be modified due to neural firings. Here, we study the effect of autonomous firings on network formation. For the temporally asymmetric Hebbian learning, bidirectional connections lose their balance easily and become unidirectional ones. Defining the difference between reciprocal connections as new variables, we could express the learning dynamics as if Ising model spins interact with each other in magnetism. We present a theoretical method to estimate the interaction between the new variables in a neural system. We apply the method to some network systems and find some tendencies of autonomous neural network regulation.

Evolving Systems: Adaptive Key Component Control and Inheritance of Passivity and Dissipativity

NASA Technical Reports Server (NTRS)

Frost, S. A.; Balas, M. J.

2010-01-01

We propose a new framework called Evolving Systems to describe the self-assembly, or autonomous assembly, of actively controlled dynamical subsystems into an Evolved System with a higher purpose. Autonomous assembly of large, complex flexible structures in space is a target application for Evolving Systems. A critical requirement for autonomous assembling structures is that they remain stable during and after assembly. The fundamental topic of inheritance of stability, dissipativity, and passivity in Evolving Systems is the primary focus of this research. In this paper, we develop an adaptive key component controller to restore stability in Nonlinear Evolving Systems that would otherwise fail to inherit the stability traits of their components. We provide sufficient conditions for the use of this novel control method and demonstrate its use on an illustrative example.

Dynamics of heart rate variability analysed through nonlinear and linear dynamics is already impaired in young type 1 diabetic subjects.

PubMed

Souza, Naiara M; Giacon, Thais R; Pacagnelli, Francis L; Barbosa, Marianne P C R; Valenti, Vitor E; Vanderlei, Luiz C M

2016-10-01

Autonomic diabetic neuropathy is one of the most common complications of type 1 diabetes mellitus, and studies using heart rate variability to investigate these individuals have shown inconclusive results regarding autonomic nervous system activation. Aims To investigate the dynamics of heart rate in young subjects with type 1 diabetes mellitus through nonlinear and linear methods of heart rate variability. We evaluated 20 subjects with type 1 diabetes mellitus and 23 healthy control subjects. We obtained the following nonlinear indices from the recurrence plot: recurrence rate (REC), determinism (DET), and Shanon entropy (ES), and we analysed indices in the frequency (LF and HF in ms2 and normalised units - nu - and LF/HF ratio) and time domains (SDNN and RMSSD), through analysis of 1000 R-R intervals, captured by a heart rate monitor. There were reduced values (p<0.05) for individuals with type 1 diabetes mellitus compared with healthy subjects in the following indices: DET, REC, ES, RMSSD, SDNN, LF (ms2), and HF (ms2). In relation to the recurrence plot, subjects with type 1 diabetes mellitus demonstrated lower recurrence and greater variation in their plot, inter-group and intra-group, respectively. Young subjects with type 1 diabetes mellitus have autonomic nervous system behaviour that tends to randomness compared with healthy young subjects. Moreover, this behaviour is related to reduced sympathetic and parasympathetic activity of the autonomic nervous system.

AN OFFSET FOR AFSOF: COMBINING ADDITIVE MANUFACTURING AND AUTONOMOUS SYSTEMS WITH SWARM EMPLOYMENT

DTIC Science & Technology

2016-10-01

teams composed of autonomous robot players compete in games of soccer .58 Strongly coordinated centralized systems are similar to the distributed...goal in a dynamically changing environment. This is a very active area of research and exemplified by the robot soccer league, a competition where...University, 2013, 23. 63 Massie, Andrew. “Autonomy and the Future Force” Strategic Studies Quarterly, Summer 2016, 146. 64 Zacharias, Greg. "Autonomus

Autonomous Multi-sensor Coordination: The Science Goal Monitor

NASA Technical Reports Server (NTRS)

Koratkar, Anuradha; Jung, John; Geiger, Jenny; Grosvenor, Sandy

2004-01-01

Next-generation science and exploration systems will employ new observation strategies that will use multiple sensors in a dynamic environment to provide high quality monitoring, self-consistent analyses and informed decision making. The Science Goal Monitor (SGM) is a prototype software tool being developed to explore the nature of automation necessary to enable dynamic observing of earth phenomenon. The tools being developed in SGM improve our ability to autonomously monitor multiple independent sensors and coordinate reactions to better observe the dynamic phenomena. The SGM system enables users to specify events of interest and how to react when an event is detected. The system monitors streams of data to identify occurrences of the key events previously specified by the scientist/user. When an event occurs, the system autonomously coordinates the execution of the users desired reactions between different sensors. The information can be used to rapidly respond to a variety of fast temporal events. Investigators will no longer have to rely on after-the-fact data analysis to determine what happened. Our paper describes a series of prototype demonstrations that we have developed using SGM and NASA's Earth Observing-1 (EO-1) satellite and Earth Observing Systems Aqua/Terra spacecrafts MODIS instrument. Our demonstrations show the promise of coordinating data from different sources, analyzing the data for a relevant event, autonomously updating and rapidly obtaining a follow-on relevant image. SGM is being used to investigate forest fires, floods and volcanic eruptions. We are now identifying new earth science scenarios that will have more complex SGM reasoning. By developing and testing a prototype in an operational environment, we are also establishing and gathering metrics to gauge the success of automating science campaigns.

Damage Detection and Verification System (DDVS) for In-Situ Health Monitoring

NASA Technical Reports Server (NTRS)

Williams, Martha K.; Lewis, Mark; Szafran, J.; Shelton, C.; Ludwig, L.; Gibson, T.; Lane, J.; Trautwein, T.

2015-01-01

Project presentation for Game Changing Program Smart Book Release. Detection and Verification System (DDVS) expands the Flat Surface Damage Detection System (FSDDS) sensory panels damage detection capabilities and includes an autonomous inspection capability utilizing cameras and dynamic computer vision algorithms to verify system health. Objectives of this formulation task are to establish the concept of operations, formulate the system requirements for a potential ISS flight experiment, and develop a preliminary design of an autonomous inspection capability system that will be demonstrated as a proof-of-concept ground based damage detection and inspection system.

Periodic response of nonlinear systems

NASA Technical Reports Server (NTRS)

Nataraj, C.; Nelson, H. D.

1988-01-01

A procedure is developed to determine approximate periodic solutions of autonomous and non-autonomous systems. The trignometric collocation method (TCM) is formalized to allow for the analysis of relatively small order systems directly in physical coordinates. The TCM is extended to large order systems by utilizing modal analysis in a component mode synthesis strategy. The procedure was coded and verified by several check cases. Numerical results for two small order mechanical systems and one large order rotor dynamic system are presented. The method allows for the possibility of approximating periodic responses for large order forced and self-excited nonlinear systems.

Development of High Fidelity Mobility Simulation of an Autonomous Vehicle in an Off-Road Scenario Using Integrated Sensor, Controller, and Multi-Body Dynamics

DTIC Science & Technology

2011-08-01

VEHICLE IN AN OFF-ROAD SCENARIO USING INTEGRATED SENSOR, CONTROLLER, AND MULTI-BODY DYNAMICS Paramsothy Jayakumar , PhD William Smith US Army...environment for a control system, mechanical system dynamics , and sensor simulation for an improved assessment of the vehicle system performance...improve vehicle dynamic performance; we must also evaluate and improve the sensor suite employed on the vehicle, and the controller used to operate

Numerical modeling of dynamics of heart rate and arterial pressure during passive orthostatic test

NASA Astrophysics Data System (ADS)

Ishbulatov, Yu. M.; Kiselev, A. R.; Karavaev, A. S.

2018-04-01

A model of human cardiovascular system is proposed to describe the main heart rhythm, influence of autonomous regulation on frequency and strength of heart contractions and resistance of arterial vessels; process of formation of arterial pressure during systolic and diastolic phases; influence of respiration; synchronization between loops of autonomous regulation. The proposed model is used to simulate the dynamics of heart rate and arterial pressure during passive transition from supine to upright position. Results of mathematical modeling are compared to original experimental data.

Poincaré recurrence statistics as an indicator of chaos synchronization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boev, Yaroslav I., E-mail: boev.yaroslav@gmail.com; Vadivasova, Tatiana E., E-mail: vadivasovate@yandex.ru; Anishchenko, Vadim S., E-mail: wadim@info.sgu.ru

The dynamics of the autonomous and non-autonomous Rössler system is studied using the Poincaré recurrence time statistics. It is shown that the probability distribution density of Poincaré recurrences represents a set of equidistant peaks with the distance that is equal to the oscillation period and the envelope obeys an exponential distribution. The dimension of the spatially uniform Rössler attractor is estimated using Poincaré recurrence times. The mean Poincaré recurrence time in the non-autonomous Rössler system is locked by the external frequency, and this enables us to detect the effect of phase-frequency synchronization.

Dynamic SLA Negotiation in Autonomic Federated Environments

NASA Astrophysics Data System (ADS)

Rubach, Pawel; Sobolewski, Michael

Federated computing environments offer requestors the ability to dynamically invoke services offered by collaborating providers in the virtual service network. Without an efficient resource management that includes Dynamic SLA Negotiation, however, the assignment of providers to customer's requests cannot be optimized and cannot offer high reliability without relevant SLA guarantees. We propose a new SLA-based SERViceable Metacomputing Environment (SERVME) capable of matching providers based on QoS requirements and performing autonomic provisioning and deprovisioning of services according to dynamic requestor needs. This paper presents the SLA negotiation process that includes on-demand provisioning and uses an object-oriented SLA model for large-scale service-oriented systems supported by SERVME. An initial reference implementation in the SORCER environment is also described.

Autonomous Navigation Using Celestial Objects

NASA Technical Reports Server (NTRS)

Folta, David; Gramling, Cheryl; Leung, Dominic; Belur, Sheela; Long, Anne

1999-01-01

In the twenty-first century, National Aeronautics and Space Administration (NASA) Enterprises envision frequent low-cost missions to explore the solar system, observe the universe, and study our planet. Satellite autonomy is a key technology required to reduce satellite operating costs. The Guidance, Navigation, and Control Center (GNCC) at the Goddard Space Flight Center (GSFC) currently sponsors several initiatives associated with the development of advanced spacecraft systems to provide autonomous navigation and control. Autonomous navigation has the potential both to increase spacecraft navigation system performance and to reduce total mission cost. By eliminating the need for routine ground-based orbit determination and special tracking services, autonomous navigation can streamline spacecraft ground systems. Autonomous navigation products can be included in the science telemetry and forwarded directly to the scientific investigators. In addition, autonomous navigation products are available onboard to enable other autonomous capabilities, such as attitude control, maneuver planning and orbit control, and communications signal acquisition. Autonomous navigation is required to support advanced mission concepts such as satellite formation flying. GNCC has successfully developed high-accuracy autonomous navigation systems for near-Earth spacecraft using NASA's space and ground communications systems and the Global Positioning System (GPS). Recently, GNCC has expanded its autonomous navigation initiative to include satellite orbits that are beyond the regime in which use of GPS is possible. Currently, GNCC is assessing the feasibility of using standard spacecraft attitude sensors and communication components to provide autonomous navigation for missions including: libration point, gravity assist, high-Earth, and interplanetary orbits. The concept being evaluated uses a combination of star, Sun, and Earth sensor measurements along with forward-link Doppler measurements from the command link carrier to autonomously estimate the spacecraft's orbit and reference oscillator's frequency. To support autonomous attitude determination and control and maneuver planning and control, the orbit determination accuracy should be on the order of kilometers in position and centimeters per second in velocity. A less accurate solution (one hundred kilometers in position) could be used for acquisition purposes for command and science downloads. This paper provides performance results for both libration point orbiting and high Earth orbiting satellites as a function of sensor measurement accuracy, measurement types, measurement frequency, initial state errors, and dynamic modeling errors.

Autonomous collection of dynamically-cued multi-sensor imagery

NASA Astrophysics Data System (ADS)

Daniel, Brian; Wilson, Michael L.; Edelberg, Jason; Jensen, Mark; Johnson, Troy; Anderson, Scott

2011-05-01

The availability of imagery simultaneously collected from sensors of disparate modalities enhances an image analyst's situational awareness and expands the overall detection capability to a larger array of target classes. Dynamic cooperation between sensors is increasingly important for the collection of coincident data from multiple sensors either on the same or on different platforms suitable for UAV deployment. Of particular interest is autonomous collaboration between wide area survey detection, high-resolution inspection, and RF sensors that span large segments of the electromagnetic spectrum. The Naval Research Laboratory (NRL) in conjunction with the Space Dynamics Laboratory (SDL) is building sensors with such networked communications capability and is conducting field tests to demonstrate the feasibility of collaborative sensor data collection and exploitation. Example survey / detection sensors include: NuSAR (NRL Unmanned SAR), a UAV compatible synthetic aperture radar system; microHSI, an NRL developed lightweight hyper-spectral imager; RASAR (Real-time Autonomous SAR), a lightweight podded synthetic aperture radar; and N-WAPSS-16 (Nighttime Wide-Area Persistent Surveillance Sensor-16Mpix), a MWIR large array gimbaled system. From these sensors, detected target cues are automatically sent to the NRL/SDL developed EyePod, a high-resolution, narrow FOV EO/IR sensor, for target inspection. In addition to this cooperative data collection, EyePod's real-time, autonomous target tracking capabilities will be demonstrated. Preliminary results and target analysis will be presented.

A Method on Dynamic Path Planning for Robotic Manipulator Autonomous Obstacle Avoidance Based on an Improved RRT Algorithm.

PubMed

Wei, Kun; Ren, Bingyin

2018-02-13

In a future intelligent factory, a robotic manipulator must work efficiently and safely in a Human-Robot collaborative and dynamic unstructured environment. Autonomous path planning is the most important issue which must be resolved first in the process of improving robotic manipulator intelligence. Among the path-planning methods, the Rapidly Exploring Random Tree (RRT) algorithm based on random sampling has been widely applied in dynamic path planning for a high-dimensional robotic manipulator, especially in a complex environment because of its probability completeness, perfect expansion, and fast exploring speed over other planning methods. However, the existing RRT algorithm has a limitation in path planning for a robotic manipulator in a dynamic unstructured environment. Therefore, an autonomous obstacle avoidance dynamic path-planning method for a robotic manipulator based on an improved RRT algorithm, called Smoothly RRT (S-RRT), is proposed. This method that targets a directional node extends and can increase the sampling speed and efficiency of RRT dramatically. A path optimization strategy based on the maximum curvature constraint is presented to generate a smooth and curved continuous executable path for a robotic manipulator. Finally, the correctness, effectiveness, and practicability of the proposed method are demonstrated and validated via a MATLAB static simulation and a Robot Operating System (ROS) dynamic simulation environment as well as a real autonomous obstacle avoidance experiment in a dynamic unstructured environment for a robotic manipulator. The proposed method not only provides great practical engineering significance for a robotic manipulator's obstacle avoidance in an intelligent factory, but also theoretical reference value for other type of robots' path planning.

A QoS Management Technique of Urgent Information Provision in ITS Services Using DSRC for Autonomous Base Stations

NASA Astrophysics Data System (ADS)

Shimura, Akitoshi; Aizono, Takeiki; Hiraiwa, Masashi; Sugano, Shigeki

A QoS management technique based on an autonomous decentralized mobility system, which is an autonomous decentralized system enhanced to provide mobile stations with information about urgent roadway situations, is proposed in this paper. This technique enables urgent messages to be flexibly and quickly transmitted to mobile stations by multiple decentralized base stations using dedicated short range communication. It also supports the easy addition of additional base stations. Each station autonomously creates information-delivery communities based on the urgency of the messages it receives through the roadside network and the distances between the senders and receivers. Each station dynamically determines the urgency of messages according to the message content and the speed of the mobile stations. Evaluation of this technique applied to the Smart Gateway system, which provides driving-assistance services to mobile stations through dedicated short-range communication, demonstrated its effectiveness and that it is suitable for actual systems.

Developing a Telescope Simulator Towards a Global Autonomous Robotic Telescope Network

NASA Astrophysics Data System (ADS)

Giakoumidis, N.; Ioannou, Z.; Dong, H.; Mavridis, N.

2013-05-01

A robotic telescope network is a system that integrates a number of telescopes to observe a variety of astronomical targets without being operated by a human. This system autonomously selects and observes targets in accordance to an optimized target. It dynamically allocates telescope resources depending on the observation requests, specifications of the telescopes, target visibility, meteorological conditions, daylight, location restrictions and availability and many other factors. In this paper, we introduce a telescope simulator, which can control a telescope to a desired position in order to observe a specific object. The system includes a Client Module, a Server Module, and a Dynamic Scheduler module. We make use and integrate a number of open source software to simulate the movement of a robotic telescope, the telescope characteristics, the observational data and weather conditions in order to test and optimize our system.

Navigation for the new millennium: Autonomous navigation for Deep Space 1

NASA Technical Reports Server (NTRS)

Reidel, J. E.; Bhaskaran, S.; Synnott, S. P.; Desai, S. D.; Bollman, W. E.; Dumont, P. J.; Halsell, C. A.; Han, D.; Kennedy, B. M.; Null, G. W.;

Wind-based navigation of a hot-air balloon on Titan: a feasibility study

NASA Astrophysics Data System (ADS)

Furfaro, Roberto; Lunine, Jonathan I.; Elfes, Alberto; Reh, Kim

2008-04-01

Current analysis of data streamed back to Earth by the Cassini spacecraft features Titan as one of the most exciting places in the solar system. NASA centers and universities around the US, as well as the European Space Agency, are studying the possibility of sending, as part of the next mission to this giant moon of Saturn, a hot-air balloon (Montgolfier-type) for further and more in-depth exploration. The basic idea would be to design a reliable, semi-autonomous, and yet cheap Montgolfier capable of using continuous flow of waste heat from a power source to lift the balloon and sustain its altitude in the Titan environment. In this paper we study the problem of locally navigating a hot-air balloon in the nitrogen-based Titan atmosphere. The basic idea is to define a strategy (i.e. design of a suitable guidance system) that allows autonomous and semi-autonomous navigation of the balloon using the available (and partial) knowledge of the wind structure blowing on the saturnian satellite surface. Starting from first principles we determined the appropriate thermal and dynamical models describing (a) the vertical dynamics of the balloon and (b) the dynamics of the balloon moving on a vertical plane (2-D motion). Next, various non-linear fuzzy-based control strategies have been evaluated, analyzed and implemented in MATLAB to numerically simulate the capability of the system to simultaneously maintain altitude, as well as a scientifically desirable trajectory. We also looked at the ability of the balloon to perform station keeping. The results of the simulation are encouraging and show the effectiveness of such a system to cheaply and effectively perform semi-autonomous exploration of Titan.

Autonomous microfluidic system for phosphate detection.

PubMed

McGraw, Christina M; Stitzel, Shannon E; Cleary, John; Slater, Conor; Diamond, Dermot

2007-02-28

Miniaturization of analytical devices through the advent of microfluidics and micro total analysis systems is an important step forward for applications such as medical diagnostics and environmental monitoring. The development of field-deployable instruments requires that the entire system, including all necessary peripheral components, be miniaturized and packaged in a portable device. A sensor for long-term monitoring of phosphate levels has been developed that incorporates sampling, reagent and waste storage, detection, and wireless communication into a complete, miniaturized system. The device employs a low-power detection and communication system, so the entire instrument can operate autonomously for 7 days on a single rechargeable, 12V battery. In addition, integration of a wireless communication device allows the instrument to be controlled and results to be downloaded remotely. This autonomous system has a limit of detection of 0.3mg/L and a linear dynamic range between 0 and 20mg/L.

Neurotoxic impact of mercury on the central nervous system evaluated by neuropsychological tests and on the autonomic nervous system evaluated by dynamic pupillometry.

PubMed

Milioni, Ana Luiza V; Nagy, Balázs V; Moura, Ana Laura A; Zachi, Elaine C; Barboni, Mirella T S; Ventura, Dora F

2017-03-01

Mercury vapor is highly toxic to the human body. The present study aimed to investigate the occurrence of neuropsychological dysfunction in former workers of fluorescent lamps factories that were exposed to mercury vapor (years after cessation of exposure), diagnosed with chronic mercurialism, and to investigate the effects of such exposure on the Autonomic Nervous System (ANS) using the non-invasive method of dynamic pupillometry. The exposed group and a control group matched by age and educational level were evaluated by the Beck Depression Inventory and with the computerized neuropsychological battery CANTABeclipse - subtests of working memory (Spatial Span), spatial memory (Spatial Recognition Memory), visual memory (Pattern Recognition Memory) and action planning (Stockings of Cambridge). The ANS was assessed by dynamic pupillometry, which provides information on the operation on both the sympathetic and parasympathetic functions. Depression scores were significantly higher among the former workers when compared with the control group. The exposed group also showed significantly worse performance in most of the cognitive functions assessed. In the dynamic pupillometry test, former workers showed significantly lower response than the control group in the sympathetic response parameter (time of 75% of pupillary recovery at 10cd/m 2 luminance). Our study found indications that are suggestive of cognitive deficits and losses in sympathetic autonomic activity among patients occupationally exposed to mercury vapor. Copyright © 2016 Elsevier B.V. All rights reserved.

Analytic Prediction of Emergent Dynamics for Autonomous Negotiating Team (ANT) Systems

DTIC Science & Technology

2003-11-01

it is determined that a “phase transition” behavior is to be expected. 15. NUMBER OF PAGES 140 14. SUBJECT TERMS autonomous negotiation...parameter. Crisis has the worst asymptotic behavior of the three strategies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 iv 3.7...deadline, as opposed to harder with increasing communication time. Again, we see that the crisis strategy has the worst asymptotic behavior over the

Increasing Mission Science Return Through Use of Spacecraft Autonomy and Sensor Webs: A Volcanology Example

NASA Astrophysics Data System (ADS)

Davies, A. G.; Chien, S. A.; Castano, R.; Tran, D. Q.; Scharenbroich, L. J.

2006-12-01

Mission science return is increased through use of onboard autonomy, and using disparate assets integrated into an autonomously-operating sensor web that can re-task these assets to rapidly obtain additional data. Software on spacecraft has been used to analyse data to detect dynamic events of high interest, such as on- going volcanic activity. This capability has been successfully demonstrated by the NASA New Millennium Program Autonomous Sciencecraft Experiment (ASE), on the Earth Observing 1 spacecraft in Earth-orbit [1-2]. The potential now exists for eruption parameters to be quantified onboard a spacecraft, using models that relate thermal emission to volumetric eruption rate. This promises a notification not only of on-going activity, but also the magnitude of the event, within a few hours of the original observation, a process that normally takes weeks. ASE/EO-1 is part of the JPL Volcano Sensor Web [3]. This autonomous system collates information of volcanic activity from numerous assets and retasks EO-1 to obtain observations as soon as practicable. The use of a ground-based planner allows rapid insertion or replacement of new observations, with no human intervention. Endusers are notified automatically by email. Spacecraft autonomy, involving automatic fault detection and mitigation, onboard processing of data, and replanning of observations, allows mission operations to break free from pre-ordained operations sequencing, necessary for studying dynamic volcanic processes on other bodies in the Solar System (e.g., Io and Enceladus). Onboard processing allows quantification of dynamic processes, improving both science content per returned byte and optimization of subsequent resource use. This work was carried out at the Jet Propulsion Laboratory-California Institute of Technology, under contract to NASA. [1] Chien, S. et al. (2004) The EO-1 Autonomous Science Agent, Proceedings of the 2004 Conferences on Autonomous Agents and Multi-agent Systems (AAMAS), New York City, USA, July 2004. [2] Davies, A. G. et al. (2006) Monitoring active volcanism with the Autonomous Sciencecraft Experiment (ASE) on EO-1, RSE, 101, 427-446. [3] Davies, A. G. et al., (2006) Sensor Web enables rapid response to volcanic activity, Eos, 87, 1, 1&5.

Autonomous Navigation of Small Uavs Based on Vehicle Dynamic Model

NASA Astrophysics Data System (ADS)

Khaghani, M.; Skaloud, J.

2016-03-01

This paper presents a novel approach to autonomous navigation for small UAVs, in which the vehicle dynamic model (VDM) serves as the main process model within the navigation filter. The proposed method significantly increases the accuracy and reliability of autonomous navigation, especially for small UAVs with low-cost IMUs on-board. This is achieved with no extra sensor added to the conventional INS/GNSS setup. This improvement is of special interest in case of GNSS outages, where inertial coasting drifts very quickly. In the proposed architecture, the solution to VDM equations provides the estimate of position, velocity, and attitude, which is updated within the navigation filter based on available observations, such as IMU data or GNSS measurements. The VDM is also fed with the control input to the UAV, which is available within the control/autopilot system. The filter is capable of estimating wind velocity and dynamic model parameters, in addition to navigation states and IMU sensor errors. Monte Carlo simulations reveal major improvements in navigation accuracy compared to conventional INS/GNSS navigation system during the autonomous phase, when satellite signals are not available due to physical obstruction or electromagnetic interference for example. In case of GNSS outages of a few minutes, position and attitude accuracy experiences improvements of orders of magnitude compared to inertial coasting. It means that during such scenario, the position-velocity-attitude (PVA) determination is sufficiently accurate to navigate the UAV to a home position without any signal that depends on vehicle environment.

Automatic Parking of Self-Driving CAR Based on LIDAR

NASA Astrophysics Data System (ADS)

Lee, B.; Wei, Y.; Guo, I. Y.

2017-09-01

To overcome the deficiency of ultrasonic sensor and camera, this paper proposed a method of autonomous parking based on the self-driving car, using HDL-32E LiDAR. First the 3-D point cloud data was preprocessed. Then we calculated the minimum size of parking space according to the dynamic theories of vehicle. Second the rapidly-exploring random tree algorithm (RRT) algorithm was improved in two aspects based on the moving characteristic of autonomous car. And we calculated the parking path on the basis of the vehicle's dynamics and collision constraints. Besides, we used the fuzzy logic controller to control the brake and accelerator in order to realize the stably of speed. At last the experiments were conducted in an autonomous car, and the results show that the proposed automatic parking system is feasible and effective.

Thermodynamics of a periodically driven qubit

NASA Astrophysics Data System (ADS)

Donvil, Brecht

2018-04-01

We present a new approach to the open system dynamics of a periodically driven qubit in contact with a temperature bath. We are specifically interested in the thermodynamics of the qubit. It is well known that by combining the Markovian approximation with Floquet theory it is possible to derive a stochastic Schrödinger equation in for the state of the qubit. We follow here a different approach. We use Floquet theory to embed the time-non autonomous qubit dynamics into time-autonomous yet infinite dimensional dynamics. We refer to the resulting infinite dimensional system as the dressed-qubit. Using the Markovian approximation we derive the stochastic Schrödinger equation for the dressed-qubit. The advantage of our approach is that the jump operators are ladder operators of the Hamiltonian. This simplifies the formulation of the thermodynamics. We use the thermodynamics of the infinite dimensional system to recover the thermodynamical description for the driven qubit. We compare our results with the existing literature and recover the known results.

The joy of transient chaos.

PubMed

Tél, Tamás

2015-09-01

We intend to show that transient chaos is a very appealing, but still not widely appreciated, subfield of nonlinear dynamics. Besides flashing its basic properties and giving a brief overview of the many applications, a few recent transient-chaos-related subjects are introduced in some detail. These include the dynamics of decision making, dispersion, and sedimentation of volcanic ash, doubly transient chaos of undriven autonomous mechanical systems, and a dynamical systems approach to energy absorption or explosion.

Simulation and Control Lab Development for Power and Energy Management for NASA Manned Deep Space Missions

NASA Technical Reports Server (NTRS)

McNelis, Anne M.; Beach, Raymond F.; Soeder, James F.; McNelis, Nancy B.; May, Ryan; Dever, Timothy P.; Trase, Larry

2014-01-01

The development of distributed hierarchical and agent-based control systems will allow for reliable autonomous energy management and power distribution for on-orbit missions. Power is one of the most critical systems on board a space vehicle, requiring quick response time when a fault or emergency is identified. As NASAs missions with human presence extend beyond low earth orbit autonomous control of vehicle power systems will be necessary and will need to reliably function for long periods of time. In the design of autonomous electrical power control systems there is a need to dynamically simulate and verify the EPS controller functionality prior to use on-orbit. This paper presents the work at NASA Glenn Research Center in Cleveland, Ohio where the development of a controls laboratory is being completed that will be utilized to demonstrate advanced prototype EPS controllers for space, aeronautical and terrestrial applications. The control laboratory hardware, software and application of an autonomous controller for demonstration with the ISS electrical power system is the subject of this paper.

Spaceflight dynamics 1993; AAS/NASA International Symposium, 8th, Greenbelt, MD, Apr. 26-30, 1993, Parts 1 & 2

NASA Technical Reports Server (NTRS)

Teles, Jerome (Editor); Samii, Mina V. (Editor)

1993-01-01

A conference on spaceflight dynamics produced papers in the areas of orbit determination, spacecraft tracking, autonomous navigation, the Deep Space Program Science Experiment Mission (DSPSE), the Global Positioning System, attitude control, geostationary satellites, interplanetary missions and trajectories, applications of estimation theory, flight dynamics systems, low-Earth orbit missions, orbital mechanics, mission experience in attitude dynamics, mission experience in sensor studies, attitude dynamics theory and simulations, and orbit-related experience. These papaers covered NASA, European, Russian, Japanese, Chinese, and Brazilian space programs and hardware.

Autonomous power expert system

NASA Technical Reports Server (NTRS)

Ringer, Mark J.; Quinn, Todd M.

1990-01-01

The goal of the Autonomous Power System (APS) program is to develop and apply intelligent problem solving and control technologies to the Space Station Freedom Electrical Power Systems (SSF/EPS). The objectives of the program are to establish artificial intelligence/expert system technology paths, to create knowledge based tools with advanced human-operator interfaces, and to integrate and interface knowledge-based and conventional control schemes. This program is being developed at the NASA-Lewis. The APS Brassboard represents a subset of a 20 KHz Space Station Power Management And Distribution (PMAD) testbed. A distributed control scheme is used to manage multiple levels of computers and switchgear. The brassboard is comprised of a set of intelligent switchgear used to effectively switch power from the sources to the loads. The Autonomous Power Expert System (APEX) portion of the APS program integrates a knowledge based fault diagnostic system, a power resource scheduler, and an interface to the APS Brassboard. The system includes knowledge bases for system diagnostics, fault detection and isolation, and recommended actions. The scheduler autonomously assigns start times to the attached loads based on temporal and power constraints. The scheduler is able to work in a near real time environment for both scheduling and dynamic replanning.

Autonomous power expert system

NASA Technical Reports Server (NTRS)

Ringer, Mark J.; Quinn, Todd M.

1990-01-01

The goal of the Autonomous Power System (APS) program is to develop and apply intelligent problem solving and control technologies to the Space Station Freedom Electrical Power Systems (SSF/EPS). The objectives of the program are to establish artificial intelligence/expert system technology paths, to create knowledge based tools with advanced human-operator interfaces, and to integrate and interface knowledge-based and conventional control schemes. This program is being developed at the NASA-Lewis. The APS Brassboard represents a subset of a 20 KHz Space Station Power Management And Distribution (PMAD) testbed. A distributed control scheme is used to manage multiple levels of computers and switchgear. The brassboard is comprised of a set of intelligent switchgear used to effectively switch power from the sources to the loads. The Autonomous Power Expert System (APEX) portion of the APS program integrates a knowledge based fault diagnostic system, a power resource scheduler, and an interface to the APS Brassboard. The system includes knowledge bases for system diagnostics, fault detection and isolation, and recommended actions. The scheduler autonomously assigns start times to the attached loads based on temporal and power constraints. The scheduler is able to work in a near real time environment for both scheduling an dynamic replanning.

Autonomous Navigation Improvements for High-Earth Orbiters Using GPS

NASA Technical Reports Server (NTRS)

Long, Anne; Kelbel, David; Lee, Taesul; Garrison, James; Carpenter, J. Russell; Bauer, F. (Technical Monitor)

2000-01-01

The Goddard Space Flight Center is currently developing autonomous navigation systems for satellites in high-Earth orbits where acquisition of the GPS signals is severely limited This paper discusses autonomous navigation improvements for high-Earth orbiters and assesses projected navigation performance for these satellites using Global Positioning System (GPS) Standard Positioning Service (SPS) measurements. Navigation performance is evaluated as a function of signal acquisition threshold, measurement errors, and dynamic modeling errors using realistic GPS signal strength and user antenna models. These analyses indicate that an autonomous navigation position accuracy of better than 30 meters root-mean-square (RMS) can be achieved for high-Earth orbiting satellites using a GPS receiver with a very stable oscillator. This accuracy improves to better than 15 meters RMS if the GPS receiver's signal acquisition threshold can be reduced by 5 dB-Hertz to track weaker signals.

Role of seasonality on predator-prey-subsidy population dynamics.

PubMed

Levy, Dorian; Harrington, Heather A; Van Gorder, Robert A

2016-05-07

The role of seasonality on predator-prey interactions in the presence of a resource subsidy is examined using a system of non-autonomous ordinary differential equations (ODEs). The problem is motivated by the Arctic, inhabited by the ecological system of arctic foxes (predator), lemmings (prey), and seal carrion (subsidy). We construct two nonlinear, nonautonomous systems of ODEs named the Primary Model, and the n-Patch Model. The Primary Model considers spatial factors implicitly, and the n-Patch Model considers space explicitly as a "Stepping Stone" system. We establish the boundedness of the dynamics, as well as the necessity of sufficiently nutritional food for the survival of the predator. We investigate the importance of including the resource subsidy explicitly in the model, and the importance of accounting for predator mortality during migration. We find a variety of non-equilibrium dynamics for both systems, obtaining both limit cycles and chaotic oscillations. We were then able to discuss relevant implications for biologically interesting predator-prey systems including subsidy under seasonal effects. Notably, we can observe the extinction or persistence of a species when the corresponding autonomous system might predict the opposite. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dynamic analysis and electronic circuit implementation of a novel 3D autonomous system without linear terms

NASA Astrophysics Data System (ADS)

Kengne, J.; Jafari, S.; Njitacke, Z. T.; Yousefi Azar Khanian, M.; Cheukem, A.

2017-11-01

Mathematical models (ODEs) describing the dynamics of almost all continuous time chaotic nonlinear systems (e.g. Lorenz, Rossler, Chua, or Chen system) involve at least a nonlinear term in addition to linear terms. In this contribution, a novel (and singular) 3D autonomous chaotic system without linear terms is introduced. This system has an especial feature of having two twin strange attractors: one ordinary and one symmetric strange attractor when the time is reversed. The complex behavior of the model is investigated in terms of equilibria and stability, bifurcation diagrams, Lyapunov exponent plots, time series and Poincaré sections. Some interesting phenomena are found including for instance, period-doubling bifurcation, antimonotonicity (i.e. the concurrent creation and annihilation of periodic orbits) and chaos while monitoring the system parameters. Compared to the (unique) case previously reported by Xu and Wang (2014) [31], the system considered in this work displays a more 'elegant' mathematical expression and experiences richer dynamical behaviors. A suitable electronic circuit (i.e. the analog simulator) is designed and used for the investigations. Pspice based simulation results show a very good agreement with the theoretical analysis.

Dynamics control of autonomous vehicle at driving limits and experiment on an autonomous formula racing car

NASA Astrophysics Data System (ADS)

Ni, Jun; Hu, Jibin

2017-06-01

In this paper, a novel dynamics controller for autonomous vehicle to simultaneously control it to the driving limits and follow the desired path is proposed. The dynamics controller consists of longitudinal and lateral controllers. In longitudinal controller, the G-G diagram is utilized to describe the driving and handling limits of the vehicle. The accurate G-G diagram is obtained based on phase plane approach and a nonlinear vehicle dynamic model with accurate tyre model. In lateral controller, the tyre cornering stiffness is estimated to improve the robustness of the controller. The stability analysis of the closed-looped error dynamics shows that the controller remains stable against parameters uncertainties in extreme condition such as tyre saturation. Finally, an electric autonomous Formula race car developed by the authors is used to validate the proposed controller. The autonomous driving experiment on an oval race track shows the efficiency and robustness of the proposed controller.

The NASA Dryden Flight Test Approach to an Aerial Refueling System

NASA Technical Reports Server (NTRS)

Hansen, Jennifer L.; Murray, James E.; Campos, Norma V.

2005-01-01

The integration of uninhabited aerial vehicles (UAVs) into controlled airspace has generated a new era of autonomous technologies and challenges. Autonomous aerial refueling would enable UAVs to travel further distances and loiter for extended periods over time-critical targets. The NASA Dryden Flight Research Center recently has completed a flight research project directed at developing a dynamic hose and drogue system model to support the development of an automated aerial refueling system. A systematic dynamic model of the hose and drogue system would include the effects of various influences on the system, such as flight condition, hose and drogue type, tanker type and weight, receiver type, and tanker and receiver maneuvering. Using two NASA F/A-18 aircraft and a conventional hose and drogue aerial refueling store from the Navy, NASA has obtained flight research data that document the response of the hose and drogue system to these effects. Preliminary results, salient trends, and important lessons are presented

The NASA Dryden AAR Project: A Flight Test Approach to an Aerial Refueling System

NASA Technical Reports Server (NTRS)

Hansen, Jennifer L.; Murray, James E.; Campos, Norma V.

2004-01-01

The integration of uninhabited aerial vehicles (UAVs) into controlled airspace has generated a new era of autonomous technologies and challenges. Autonomous aerial refueling would enable UAVs to travel further distances and loiter for extended periods over time-critical targets. The NASA Dryden Flight Research Center recently has completed a flight research project directed at developing a dynamic hose and drogue system model to support the development of an automated aerial refueling system. A systematic dynamic model of the hose and drogue system would include the effects of various influences on the system, such as flight condition, hose and drogue type, tanker type and weight, receiver type, and tanker and receiver maneuvering. Using two NASA F/A-18 aircraft and a conventional hose and drogue aerial refueling store from the Navy, NASA has obtained flight research data that document the response of the hose and drogue system to these effects. Preliminary results, salient trends, and important lessons are presented.

Act-and-wait time-delayed feedback control of autonomous systems

NASA Astrophysics Data System (ADS)

Pyragas, Viktoras; Pyragas, Kestutis

2018-02-01

Recently an act-and-wait modification of time-delayed feedback control has been proposed for the stabilization of unstable periodic orbits in nonautonomous dynamical systems (Pyragas and Pyragas, 2016 [30]). The modification implies a periodic switching of the feedback gain and makes the closed-loop system finite-dimensional. Here we extend this modification to autonomous systems. In order to keep constant the phase difference between the controlled orbit and the act-and-wait switching function an additional small-amplitude periodic perturbation is introduced. The algorithm can stabilize periodic orbits with an odd number of real unstable Floquet exponents using a simple single-input single-output constraint control.

AltiVec performance increases for autonomous robotics for the MARSSCAPE architecture program

NASA Astrophysics Data System (ADS)

Gothard, Benny M.

2002-02-01

One of the main tall poles that must be overcome to develop a fully autonomous vehicle is the inability of the computer to understand its surrounding environment to a level that is required for the intended task. The military mission scenario requires a robot to interact in a complex, unstructured, dynamic environment. Reference A High Fidelity Multi-Sensor Scene Understanding System for Autonomous Navigation The Mobile Autonomous Robot Software Self Composing Adaptive Programming Environment (MarsScape) perception research addresses three aspects of the problem; sensor system design, processing architectures, and algorithm enhancements. A prototype perception system has been demonstrated on robotic High Mobility Multi-purpose Wheeled Vehicle and All Terrain Vehicle testbeds. This paper addresses the tall pole of processing requirements and the performance improvements based on the selected MarsScape Processing Architecture. The processor chosen is the Motorola Altivec-G4 Power PC(PPC) (1998 Motorola, Inc.), a highly parallized commercial Single Instruction Multiple Data processor. Both derived perception benchmarks and actual perception subsystems code will be benchmarked and compared against previous Demo II-Semi-autonomous Surrogate Vehicle processing architectures along with desktop Personal Computers(PC). Performance gains are highlighted with progress to date, and lessons learned and future directions are described.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rivera-Durón, R. R., E-mail: roberto.rivera@ipicyt.edu.mx; Campos-Cantón, E., E-mail: eric.campos@ipicyt.edu.mx; Campos-Cantón, I.

We present the design of an autonomous time-delay Boolean network realized with readily available electronic components. Through simulations and experiments that account for the detailed nonlinear response of each circuit element, we demonstrate that a network with five Boolean nodes displays complex behavior. Furthermore, we show that the dynamics of two identical networks display near-instantaneous synchronization to a periodic state when forced by a common periodic Boolean signal. A theoretical analysis of the network reveals the conditions under which complex behavior is expected in an individual network and the occurrence of synchronization in the forced networks. This research will enablemore » future experiments on autonomous time-delay networks using readily available electronic components with dynamics on a slow enough time-scale so that inexpensive data collection systems can faithfully record the dynamics.« less

Onboard autonomous mission re-planning for multi-satellite system

NASA Astrophysics Data System (ADS)

Zheng, Zixuan; Guo, Jian; Gill, Eberhard

2018-04-01

This paper presents an onboard autonomous mission re-planning system for Multi-Satellites System (MSS) to perform onboard re-planing in disruptive situations. The proposed re-planning system can deal with different potential emergency situations. This paper uses Multi-Objective Hybrid Dynamic Mutation Genetic Algorithm (MO-HDM GA) combined with re-planning techniques as the core algorithm. The Cyclically Re-planning Method (CRM) and the Near Real-time Re-planning Method (NRRM) are developed to meet different mission requirements. Simulations results show that both methods can provide feasible re-planning sequences under unforeseen situations. The comparisons illustrate that using the CRM is average 20% faster than the NRRM on computation time. However, by using the NRRM more raw data can be observed and transmitted than using the CRM within the same period. The usability of this onboard re-planning system is not limited to multi-satellite system. Other mission planning and re-planning problems related to autonomous multiple vehicles with similar demands are also applicable.

Dynamic path planning for autonomous driving on various roads with avoidance of static and moving obstacles

NASA Astrophysics Data System (ADS)

Hu, Xuemin; Chen, Long; Tang, Bo; Cao, Dongpu; He, Haibo

2018-02-01

This paper presents a real-time dynamic path planning method for autonomous driving that avoids both static and moving obstacles. The proposed path planning method determines not only an optimal path, but also the appropriate acceleration and speed for a vehicle. In this method, we first construct a center line from a set of predefined waypoints, which are usually obtained from a lane-level map. A series of path candidates are generated by the arc length and offset to the center line in the s - ρ coordinate system. Then, all of these candidates are converted into Cartesian coordinates. The optimal path is selected considering the total cost of static safety, comfortability, and dynamic safety; meanwhile, the appropriate acceleration and speed for the optimal path are also identified. Various types of roads, including single-lane roads and multi-lane roads with static and moving obstacles, are designed to test the proposed method. The simulation results demonstrate the effectiveness of the proposed method, and indicate its wide practical application to autonomous driving.

Fuzzy Sets in Dynamic Adaptation of Parameters of a Bee Colony Optimization for Controlling the Trajectory of an Autonomous Mobile Robot

PubMed Central

Amador-Angulo, Leticia; Mendoza, Olivia; Castro, Juan R.; Rodríguez-Díaz, Antonio; Melin, Patricia; Castillo, Oscar

2016-01-01

A hybrid approach composed by different types of fuzzy systems, such as the Type-1 Fuzzy Logic System (T1FLS), Interval Type-2 Fuzzy Logic System (IT2FLS) and Generalized Type-2 Fuzzy Logic System (GT2FLS) for the dynamic adaptation of the alpha and beta parameters of a Bee Colony Optimization (BCO) algorithm is presented. The objective of the work is to focus on the BCO technique to find the optimal distribution of the membership functions in the design of fuzzy controllers. We use BCO specifically for tuning membership functions of the fuzzy controller for trajectory stability in an autonomous mobile robot. We add two types of perturbations in the model for the Generalized Type-2 Fuzzy Logic System to better analyze its behavior under uncertainty and this shows better results when compared to the original BCO. We implemented various performance indices; ITAE, IAE, ISE, ITSE, RMSE and MSE to measure the performance of the controller. The experimental results show better performances using GT2FLS then by IT2FLS and T1FLS in the dynamic adaptation the parameters for the BCO algorithm. PMID:27618062

Real-time path planning and autonomous control for helicopter autorotation

NASA Astrophysics Data System (ADS)

Yomchinda, Thanan

Autorotation is a descending maneuver that can be used to recover helicopters in the event of total loss of engine power; however it is an extremely difficult and complex maneuver. The objective of this work is to develop a real-time system which provides full autonomous control for autorotation landing of helicopters. The work includes the development of an autorotation path planning method and integration of the path planner with a primary flight control system. The trajectory is divided into three parts: entry, descent and flare. Three different optimization algorithms are used to generate trajectories for each of these segments. The primary flight control is designed using a linear dynamic inversion control scheme, and a path following control law is developed to track the autorotation trajectories. Details of the path planning algorithm, trajectory following control law, and autonomous autorotation system implementation are presented. The integrated system is demonstrated in real-time high fidelity simulations. Results indicate feasibility of the capability of the algorithms to operate in real-time and of the integrated systems ability to provide safe autorotation landings. Preliminary simulations of autonomous autorotation on a small UAV are presented which will lead to a final hardware demonstration of the algorithms.

Global Precipitation Measurement (GPM) Orbit Design and Autonomous Maneuvers

NASA Technical Reports Server (NTRS)

Folta, David; Mendelsohn, Chad

2003-01-01

The NASA Goddard Space Flight Center's Global Precipitation Measurement (GPM) mission will meet a challenge of measuring worldwide precipitation every three hours. The GPM spacecraft, part of a constellation, will be required to maintain a circular orbit in a high drag environment to accomplish this challenge. Analysis by the Flight Dynamics Analysis Branch has shown that the prime orbit altitude of 40% is necessary to prevent ground track repeating. Combined with goals to minimize maneuver impacts to science data collection and enabling reasonable long-term orbit predictions, the GPM project has decided to fly an autonomous maneuver system. This system is a derivative of the successful New Millennium Program technology flown onboard the Earth Observing-1 mission. This paper presents the driving science requirements and goals of the mission and shows how they will be met. Analysis of the orbit optimization and the AV requirements for several ballistic properties are presented. The architecture of the autonomous maneuvering system to meet the goals and requirements is presented along with simulations using a GPM prototype. Additionally, the use of the GPM autonomous system to mitigate possible collision avoidance and to aid other spacecraft systems during navigation outages is explored.

Community Design for Optimal Energy and Resource Utilization.

ERIC Educational Resources Information Center

Bilenky, Stephen; And Others

Presented is a study which investigated the energy and resource dynamics of a semi-autonomous domestic system for 30 people. The investigation is organized on three levels: (1) developing a preliminary design and design parameters; (2) development and quantification of the energy and resource dynamics; and (3) designing a model to extrapolate…

Evolution of Autonomous Self-Righting Behaviors for Articulated Nanorovers

NASA Technical Reports Server (NTRS)

Tunstel, Edward

1999-01-01

Miniature rovers with articulated mobility mechanisms are being developed for planetary surface exploration on Mars and small solar system bodies. These vehicles are designed to be capable of autonomous recovery from overturning during surface operations. This paper describes a computational means of developing motion behaviors that achieve the autonomous recovery function. It proposes a control software design approach aimed at reducing the effort involved in developing self-righting behaviors. The approach is based on the integration of evolutionary computing with a dynamics simulation environment for evolving and evaluating motion behaviors. The automated behavior design approach is outlined and its underlying genetic programming infrastructure is described.

How does selfing affect the dynamics of selfish transposable elements?

PubMed

Boutin, Thibaud S; Le Rouzic, Arnaud; Capy, Pierre

2012-03-07

Many theoretical models predicting the dynamics of transposable elements (TEs) in genomes, populations, and species have already been proposed. However, most of them only focus on populations of sexual diploid individuals, and TE dynamics in populations partly composed by autogamous individuals remains poorly investigated. To estimate the impact of selfing on TE dynamics, the short- and long-term evolution of TEs was simulated in outcrossing populations with various proportions of selfing individuals. Selfing has a deep impact on TE dynamics: the higher the selfing rate, the lower the probability of invasion. Already known non-equilibrium dynamics (complete loss, domestication, cyclical invasion of TEs) can all be described whatever the mating system. However, their pattern and their respective frequencies greatly depend on the selfing rate. For instance, in cyclical dynamics resulting from interactions between autonomous and non-autonomous copies, cycles are faster when the selfing rate increases. Interestingly, an abrupt change in the mating system from sexuality to complete asexuality leads to the loss of all the elements over a few hundred generations. In general, for intermediate selfing rates, the transposition activity remains maintained. Our theoretical results evidence that a clear and systematic contrast in TE content according to the mating system is expected, with a smooth transition for intermediate selfing rates. Several parameters impact the TE copy number, and all dynamics described in allogamous populations can be also observed in partly autogamous species. This study thus provides new insights to understand the complex signal from empirical comparison of closely related species with different mating systems.

Applying Utility Functions to Adaptation Planning for Home Automation Applications

NASA Astrophysics Data System (ADS)

Bratskas, Pyrros; Paspallis, Nearchos; Kakousis, Konstantinos; Papadopoulos, George A.

A pervasive computing environment typically comprises multiple embedded devices that may interact together and with mobile users. These users are part of the environment, and they experience it through a variety of devices embedded in the environment. This perception involves technologies which may be heterogeneous, pervasive, and dynamic. Due to the highly dynamic properties of such environments, the software systems running on them have to face problems such as user mobility, service failures, or resource and goal changes which may happen in an unpredictable manner. To cope with these problems, such systems must be autonomous and self-managed. In this chapter we deal with a special kind of a ubiquitous environment, a smart home environment, and introduce a user-preference-based model for adaptation planning. The model, which dynamically forms a set of configuration plans for resources, reasons automatically and autonomously, based on utility functions, on which plan is likely to best achieve the user's goals with respect to resource availability and user needs.

Chaotic Dynamics and Application of LCR Oscillators Sharing Common Nonlinearity

NASA Astrophysics Data System (ADS)

Jeevarekha, A.; Paul Asir, M.; Philominathan, P.

2016-06-01

This paper addresses the problem of sharing common nonlinearity among nonautonomous and autonomous oscillators. By choosing a suitable common nonlinear element with the driving point characteristics capable of bringing out chaotic motion in a combined system, we obtain identical chaotic states. The dynamics of the coupled system is explored through numerical and experimental studies. Employing the concept of common nonlinearity, a simple chaotic communication system is modeled and its performance is verified through Multisim simulation.

Physiology of motion sickness symptoms

NASA Technical Reports Server (NTRS)

Harm, Deborah L.

1990-01-01

Motion sickness research is reviewed with the emphasis placed on theories developed to explain its symptomatology. A general review of central nervous system, autonomic nervous system, and neuroendocrine system involvement in the syndrome. Particular attention is given to signs, symptoms, and physiological correlates, methodological issues, and directions for future research based on a dynamic interactive systems model.

Light-powered autonomous and directional molecular motion of a dissipative self-assembling system

NASA Astrophysics Data System (ADS)

Ragazzon, Giulio; Baroncini, Massimo; Silvi, Serena; Venturi, Margherita; Credi, Alberto

2015-01-01

Biomolecular motors convert energy into directed motion and operate away from thermal equilibrium. The development of dynamic chemical systems that exploit dissipative (non-equilibrium) processes is a challenge in supramolecular chemistry and a premise for the realization of artificial nanoscale motors. Here, we report the relative unidirectional transit of a non-symmetric molecular axle through a macrocycle powered solely by light. The molecular machine rectifies Brownian fluctuations by energy and information ratchet mechanisms and can repeat its working cycle under photostationary conditions. The system epitomizes the conceptual and practical elements forming the basis of autonomous light-powered directed motion with a minimalist molecular design.

Autonomous Integrated Receive System (AIRS) requirements definition. Volume 3: Performance and simulation

NASA Technical Reports Server (NTRS)

Chie, C. M.; Su, Y. T.; Lindsey, W. C.; Koukos, J.

1984-01-01

The autonomous and integrated aspects of the operation of the AIRS (Autonomous Integrated Receive System) are discussed from a system operation point of view. The advantages of AIRS compared to the existing SSA receive chain equipment are highlighted. The three modes of AIRS operation are addressed in detail. The configurations of the AIRS are defined as a function of the operating modes and the user signal characteristics. Each AIRS configuration selection is made up of three components: the hardware, the software algorithms and the parameters used by these algorithms. A comparison between AIRS and the wide dynamics demodulation (WDD) is provided. The organization of the AIRS analytical/simulation software is described. The modeling and analysis is for simulating the performance of the PN subsystem is documented. The frequence acquisition technique using a frequency-locked loop is also documented. Doppler compensation implementation is described. The technological aspects of employing CCD's for PN acquisition are addressed.

Quantification of cardiovascular and cardiorespiratory coupling during hypoxia with Joint Symbolic Dynamics.

PubMed

Reulecke, S; Schulz, S; Bauer, R; Witte, H; Voss, A

2011-01-01

Newborn mammals suffering from moderate hypoxia during or after birth are able to compensate a transitory lack of oxygen by adaptation of their vital functions. However, limited information is available about bivariate couplings of the underlying complex processes controlled by the autonomic nervous system. In this study an animal model of seven newborn piglets (2-3 days old, 1.71 ± 0.15 kg) was used. The aim of this study was to analyze the cardiovascular and cardiorespiratory interactions of autonomous nervous system during sustained hypoxia and the interrelationship of these autonomic time series after induced reoxygenation. For this purpose we applied a new high resolution version of the nonlinear method of Joint Symbolic Dynamics (JSD) for analysis of couplings between heart rate and blood pressure and respiration rate time series, respectively. This new method is characterized by using three defined symbols (JSD3) instead of two and the application of thresholds for the symbol transformation. Our results demonstrate that in contrast to the traditional JSD the comparison of cardiovascular interactions reveals only significant differences between normoxic and hypoxic conditions using JSD3 whereas for cardiorespiratory interactions significant differences were revealed by indices from both JSD2 and JSD3 due to reoxygenation. These results suggest that the application of JSD3 reveals more detailed information about cardiovascular and cardiorespiratory interactions of autonomic regulation and might be useful for monitoring of critical human newborns.

An atomic magnetometer with autonomous frequency stabilization and large dynamic range

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pradhan, S., E-mail: spradhan@barc.gov.in, E-mail: pradhans75@gmail.com; Poornima,; Dasgupta, K.

2015-06-15

The operation of a highly sensitive atomic magnetometer using elliptically polarized resonant light is demonstrated. It is based on measurement of zero magnetic field resonance in degenerate two level systems using polarimetric detection. The transmitted light through the polarimeter is used for laser frequency stabilization, whereas reflected light is used for magnetic field measurement. Thus, the experimental geometry allows autonomous frequency stabilization of the laser frequency leading to compact operation of the overall device and has a preliminary sensitivity of <10 pT/Hz{sup 1/2} @ 1 Hz. Additionally, the dynamic range of the device is improved by feedback controlling the biasmore » magnetic field without compromising on its sensitivity.« less

Autonomous Information Fading and Provision to Achieve High Response Time in Distributed Information Systems

NASA Astrophysics Data System (ADS)

Lu, Xiaodong; Arfaoui, Helene; Mori, Kinji

In highly dynamic electronic commerce environment, the need for adaptability and rapid response time to information service systems has become increasingly important. In order to cope with the continuously changing conditions of service provision and utilization, Faded Information Field (FIF) has been proposed. FIF is a distributed information service system architecture, sustained by push/pull mobile agents to bring high-assurance of services through a recursive demand-oriented provision of the most popular information closer to the users to make a tradeoff between the cost of information service allocation and access. In this paper, based on the analysis of the relationship that exists among the users distribution, information provision and access time, we propose the technology for FIF design to resolve the competing requirements of users and providers to improve users' access time. In addition, to achieve dynamic load balancing with changing users preference, the autonomous information reallocation technology is proposed. We proved the effectiveness of the proposed technology through the simulation and comparison with the conventional system.

Propagation, cascades, and agreement dynamics in complex communication and social networks

NASA Astrophysics Data System (ADS)

Lu, Qiming

Many modern and important technological, social, information and infrastructure systems can be viewed as complex systems with a large number of interacting components. Models of complex networks and dynamical interactions, as well as their applications are of fundamental interests in many aspects. Here, several stylized models of multiplex propagation and opinion dynamics are investigated on complex and empirical social networks. We first investigate cascade dynamics in threshold-controlled (multiplex) propagation on random geometric networks. We find that such local dynamics can serve as an efficient, robust, and reliable prototypical activation protocol in sensor networks in responding to various alarm scenarios. We also consider the same dynamics on a modified network by adding a few long-range communication links, resulting in a small-world network. We find that such construction can further enhance and optimize the speed of the network's response, while keeping energy consumption at a manageable level. We also investigate a prototypical agent-based model, the Naming Game, on two-dimensional random geometric networks. The Naming Game [A. Baronchelli et al., J. Stat. Mech.: Theory Exp. (2006) P06014.] is a minimal model, employing local communications that captures the emergence of shared communication schemes (languages) in a population of autonomous semiotic agents. Implementing the Naming Games with local broadcasts on random geometric graphs, serves as a model for agreement dynamics in large-scale, autonomously operating wireless sensor networks. Further, it captures essential features of the scaling properties of the agreement process for spatially-embedded autonomous agents. Among the relevant observables capturing the temporal properties of the agreement process, we investigate the cluster-size distribution and the distribution of the agreement times, both exhibiting dynamic scaling. We also present results for the case when a small density of long-range communication links are added on top of the random geometric graph, resulting in a "small-world"-like network and yielding a significantly reduced time to reach global agreement. We construct a finite-size scaling analysis for the agreement times in this case. When applying the model of Naming Game on empirical social networks, this stylized agent-based model captures essential features of agreement dynamics in a network of autonomous agents, corresponding to the development of shared classification schemes in a network of artificial agents or opinion spreading and social dynamics in social networks. Our study focuses on the impact that communities in the underlying social graphs have on the outcome of the agreement process. We find that networks with strong community structure hinder the system from reaching global agreement; the evolution of the Naming Game in these networks maintains clusters of coexisting opinions indefinitely. Further, we investigate agent-based network strategies to facilitate convergence to global consensus.

Fuzzy Decision-Making Fuser (FDMF) for Integrating Human-Machine Autonomous (HMA) Systems with Adaptive Evidence Sources.

PubMed

Liu, Yu-Ting; Pal, Nikhil R; Marathe, Amar R; Wang, Yu-Kai; Lin, Chin-Teng

2017-01-01

A brain-computer interface (BCI) creates a direct communication pathway between the human brain and an external device or system. In contrast to patient-oriented BCIs, which are intended to restore inoperative or malfunctioning aspects of the nervous system, a growing number of BCI studies focus on designing auxiliary systems that are intended for everyday use. The goal of building these BCIs is to provide capabilities that augment existing intact physical and mental capabilities. However, a key challenge to BCI research is human variability; factors such as fatigue, inattention, and stress vary both across different individuals and for the same individual over time. If these issues are addressed, autonomous systems may provide additional benefits that enhance system performance and prevent problems introduced by individual human variability. This study proposes a human-machine autonomous (HMA) system that simultaneously aggregates human and machine knowledge to recognize targets in a rapid serial visual presentation (RSVP) task. The HMA focuses on integrating an RSVP BCI with computer vision techniques in an image-labeling domain. A fuzzy decision-making fuser (FDMF) is then applied in the HMA system to provide a natural adaptive framework for evidence-based inference by incorporating an integrated summary of the available evidence (i.e., human and machine decisions) and associated uncertainty. Consequently, the HMA system dynamically aggregates decisions involving uncertainties from both human and autonomous agents. The collaborative decisions made by an HMA system can achieve and maintain superior performance more efficiently than either the human or autonomous agents can achieve independently. The experimental results shown in this study suggest that the proposed HMA system with the FDMF can effectively fuse decisions from human brain activities and the computer vision techniques to improve overall performance on the RSVP recognition task. This conclusion demonstrates the potential benefits of integrating autonomous systems with BCI systems.

Fuzzy Decision-Making Fuser (FDMF) for Integrating Human-Machine Autonomous (HMA) Systems with Adaptive Evidence Sources

PubMed Central

Liu, Yu-Ting; Pal, Nikhil R.; Marathe, Amar R.; Wang, Yu-Kai; Lin, Chin-Teng

2017-01-01

A brain-computer interface (BCI) creates a direct communication pathway between the human brain and an external device or system. In contrast to patient-oriented BCIs, which are intended to restore inoperative or malfunctioning aspects of the nervous system, a growing number of BCI studies focus on designing auxiliary systems that are intended for everyday use. The goal of building these BCIs is to provide capabilities that augment existing intact physical and mental capabilities. However, a key challenge to BCI research is human variability; factors such as fatigue, inattention, and stress vary both across different individuals and for the same individual over time. If these issues are addressed, autonomous systems may provide additional benefits that enhance system performance and prevent problems introduced by individual human variability. This study proposes a human-machine autonomous (HMA) system that simultaneously aggregates human and machine knowledge to recognize targets in a rapid serial visual presentation (RSVP) task. The HMA focuses on integrating an RSVP BCI with computer vision techniques in an image-labeling domain. A fuzzy decision-making fuser (FDMF) is then applied in the HMA system to provide a natural adaptive framework for evidence-based inference by incorporating an integrated summary of the available evidence (i.e., human and machine decisions) and associated uncertainty. Consequently, the HMA system dynamically aggregates decisions involving uncertainties from both human and autonomous agents. The collaborative decisions made by an HMA system can achieve and maintain superior performance more efficiently than either the human or autonomous agents can achieve independently. The experimental results shown in this study suggest that the proposed HMA system with the FDMF can effectively fuse decisions from human brain activities and the computer vision techniques to improve overall performance on the RSVP recognition task. This conclusion demonstrates the potential benefits of integrating autonomous systems with BCI systems. PMID:28676734

Cardiovascular autonomic adaptation in lunar and martian gravity during parabolic flight.

PubMed

Widjaja, Devy; Vandeput, Steven; Van Huffel, Sabine; Aubert, André E

2015-06-01

Weightlessness has a well-known effect on the autonomic control of the cardiovascular system. With future missions to Mars in mind, it is important to know what the effect of partial gravity is on the human body. We aim to study the autonomic response of the cardiovascular system to partial gravity levels, as present on the Moon and on Mars, during parabolic flight. ECG and blood pressure were continuously recorded during parabolic flight. A temporal analysis of blood pressure and heart rate to changing gravity was conducted to study the dynamic response. In addition, cardiovascular autonomic control was quantified by means of heart rate (HR) and blood pressure (BP) variability measures. Zero and lunar gravity presented a biphasic cardiovascular response, while a triphasic response was noted during martian gravity. Heart rate and blood pressure are positively correlated with gravity, while the general variability of HR and BP, as well as vagal indices showed negative correlations with increasing gravity. However, the increase in vagal modulation during weightlessness is not in proportion when compared to the increase during partial gravity. Correlations were found between the gravity level and modulations in the autonomic nervous system during parabolic flight. Nevertheless, with future Mars missions in mind, more studies are needed to use these findings to develop appropriate countermeasures.

Longitudinal Control for Mengshi Autonomous Vehicle via Cloud Model

NASA Astrophysics Data System (ADS)

Gao, H. B.; Zhang, X. Y.; Li, D. Y.; Liu, Y. C.

2018-03-01

Dynamic robustness and stability control is a requirement for self-driving of autonomous vehicle. Longitudinal control method of autonomous is a key technique which has drawn the attention of industry and academe. In this paper, we present a longitudinal control algorithm based on cloud model for Mengshi autonomous vehicle to ensure the dynamic stability and tracking performance of Mengshi autonomous vehicle. An experiments is applied to test the implementation of the longitudinal control algorithm. Empirical results show that if the longitudinal control algorithm based Gauss cloud model are applied to calculate the acceleration, and the vehicles drive at different speeds, a stable longitudinal control effect is achieved.

Data-driven discovery of Koopman eigenfunctions using deep learning

NASA Astrophysics Data System (ADS)

Lusch, Bethany; Brunton, Steven L.; Kutz, J. Nathan

2017-11-01

Koopman operator theory transforms any autonomous non-linear dynamical system into an infinite-dimensional linear system. Since linear systems are well-understood, a mapping of non-linear dynamics to linear dynamics provides a powerful approach to understanding and controlling fluid flows. However, finding the correct change of variables remains an open challenge. We present a strategy to discover an approximate mapping using deep learning. Our neural networks find this change of variables, its inverse, and a finite-dimensional linear dynamical system defined on the new variables. Our method is completely data-driven and only requires measurements of the system, i.e. it does not require derivatives or knowledge of the governing equations. We find a minimal set of approximate Koopman eigenfunctions that are sufficient to reconstruct and advance the system to future states. We demonstrate the method on several dynamical systems.

Suboptimal Scheduling in Switched Systems With Continuous-Time Dynamics: A Least Squares Approach.

PubMed

Sardarmehni, Tohid; Heydari, Ali

2018-06-01

Two approximate solutions for optimal control of switched systems with autonomous subsystems and continuous-time dynamics are presented. The first solution formulates a policy iteration (PI) algorithm for the switched systems with recursive least squares. To reduce the computational burden imposed by the PI algorithm, a second solution, called single loop PI, is presented. Online and concurrent training algorithms are discussed for implementing each solution. At last, effectiveness of the presented algorithms is evaluated through numerical simulations.

Cooperative mission execution and planning

NASA Astrophysics Data System (ADS)

Flann, Nicholas S.; Saunders, Kevin S.; Pells, Larry

1998-08-01

Utilizing multiple cooperating autonomous vehicles to perform tasks enhances robustness and efficiency over the use of a single vehicle. Furthermore, because autonomous vehicles can be controlled precisely and their status known accurately in real time, new types of cooperative behaviors are possible. This paper presents a working system called MEPS that plans and executes missions for multiple autonomous vehicles in large structured environments. Two generic spatial tasks are supported, to sweep an area and to visit a location while activating on-board equipment. Tasks can be entered both initially by the user and dynamically during mission execution by both users and vehicles. Sensor data and task achievement data is shared among the vehicles enabling them to cooperatively adapt to changing environmental, vehicle and tasks conditions. The system has been successfully applied to control ATV and micro-robotic vehicles in precision agriculture and waste-site characterization environments.

Autonomic Management of Application Workflows on Hybrid Computing Infrastructure

DOE PAGES

Kim, Hyunjoo; el-Khamra, Yaakoub; Rodero, Ivan; ...

2011-01-01

In this paper, we present a programming and runtime framework that enables the autonomic management of complex application workflows on hybrid computing infrastructures. The framework is designed to address system and application heterogeneity and dynamics to ensure that application objectives and constraints are satisfied. The need for such autonomic system and application management is becoming critical as computing infrastructures become increasingly heterogeneous, integrating different classes of resources from high-end HPC systems to commodity clusters and clouds. For example, the framework presented in this paper can be used to provision the appropriate mix of resources based on application requirements and constraints.more » The framework also monitors the system/application state and adapts the application and/or resources to respond to changing requirements or environment. To demonstrate the operation of the framework and to evaluate its ability, we employ a workflow used to characterize an oil reservoir executing on a hybrid infrastructure composed of TeraGrid nodes and Amazon EC2 instances of various types. Specifically, we show how different applications objectives such as acceleration, conservation and resilience can be effectively achieved while satisfying deadline and budget constraints, using an appropriate mix of dynamically provisioned resources. Our evaluations also demonstrate that public clouds can be used to complement and reinforce the scheduling and usage of traditional high performance computing infrastructure.« less

Distributed Cognition on the road: Using EAST to explore future road transportation systems.

PubMed

Banks, Victoria A; Stanton, Neville A; Burnett, Gary; Hermawati, Setia

2018-04-01

Connected and Autonomous Vehicles (CAV) are set to revolutionise the way in which we use our transportation system. However, we do not fully understand how the integration of wireless and autonomous technology into the road transportation network affects overall network dynamism. This paper uses the theoretical principles underlying Distributed Cognition to explore the dependencies and interdependencies that exist between system agents located within the road environment, traffic management centres and other external agencies in both non-connected and connected transportation systems. This represents a significant step forward in modelling complex sociotechnical systems as it shows that the principles underlying Distributed Cognition can be applied to macro-level systems using the visual representations afforded by the Event Analysis of Systemic Teamwork (EAST) method. Copyright © 2017 Elsevier Ltd. All rights reserved.

Autonomous Cryogenics Loading Operations Simulation Software: Knowledgebase Autonomous Test Engineer

NASA Technical Reports Server (NTRS)

Wehner, Walter S., Jr.

2013-01-01

Working on the ACLO (Autonomous Cryogenics Loading Operations) project I have had the opportunity to add functionality to the physics simulation software known as KATE (Knowledgebase Autonomous Test Engineer), create a new application allowing WYSIWYG (what-you-see-is-what-you-get) creation of KATE schematic files and begin a preliminary design and implementation of a new subsystem that will provide vision services on the IHM (Integrated Health Management) bus. The functionality I added to KATE over the past few months includes a dynamic visual representation of the fluid height in a pipe based on number of gallons of fluid in the pipe and implementing the IHM bus connection within KATE. I also fixed a broken feature in the system called the Browser Display, implemented many bug fixes and made changes to the GUI (Graphical User Interface).

Vision-based control for flight relative to dynamic environments

NASA Astrophysics Data System (ADS)

Causey, Ryan Scott

The concept of autonomous systems has been considered an enabling technology for a diverse group of military and civilian applications. The current direction for autonomous systems is increased capabilities through more advanced systems that are useful for missions that require autonomous avoidance, navigation, tracking, and docking. To facilitate this level of mission capability, passive sensors, such as cameras, and complex software are added to the vehicle. By incorporating an on-board camera, visual information can be processed to interpret the surroundings. This information allows decision making with increased situational awareness without the cost of a sensor signature, which is critical in military applications. The concepts presented in this dissertation facilitate the issues inherent to vision-based state estimation of moving objects for a monocular camera configuration. The process consists of several stages involving image processing such as detection, estimation, and modeling. The detection algorithm segments the motion field through a least-squares approach and classifies motions not obeying the dominant trend as independently moving objects. An approach to state estimation of moving targets is derived using a homography approach. The algorithm requires knowledge of the camera motion, a reference motion, and additional feature point geometry for both the target and reference objects. The target state estimates are then observed over time to model the dynamics using a probabilistic technique. The effects of uncertainty on state estimation due to camera calibration are considered through a bounded deterministic approach. The system framework focuses on an aircraft platform of which the system dynamics are derived to relate vehicle states to image plane quantities. Control designs using standard guidance and navigation schemes are then applied to the tracking and homing problems using the derived state estimation. Four simulations are implemented in MATLAB that build on the image concepts present in this dissertation. The first two simulations deal with feature point computations and the effects of uncertainty. The third simulation demonstrates the open-loop estimation of a target ground vehicle in pursuit whereas the four implements a homing control design for the Autonomous Aerial Refueling (AAR) using target estimates as feedback.

Analysis and design of a capsule landing system and surface vehicle control system for Mars exploration

NASA Technical Reports Server (NTRS)

1974-01-01

A number of problems related to the design, construction and evaluation of an autonomous roving planetary vehicle and its control and operating systems intended for an unmanned exploration of Mars are studied. Vehicle configuration, dynamics, control, systems and propulsion; systems analysis; terrain sensing and modeling and path selection; and chemical analysis of samples are included.

42nd Annual Armament Systems: Gun and Missile Systems

DTIC Science & Technology

2007-04-26

to compare the various contenders: • FCS • Aero and flight dynamics of rounds • Phit and lethality • Direct and indirect fire capability Defence R&D...each other). • Guidance: Unguided, Command Guidance, Lock on Before Launch, Autonomous (needs Phit analysis). • Fuzing: Proximity – RF or Optical

Unified formalism for the generalized kth-order Hamilton-Jacobi problem

NASA Astrophysics Data System (ADS)

Colombo, Leonardo; de Léon, Manuel; Prieto-Martínez, Pedro Daniel; Román-Roy, Narciso

2014-08-01

The geometric formulation of the Hamilton-Jacobi theory enables us to generalize it to systems of higher-order ordinary differential equations. In this work we introduce the unified Lagrangian-Hamiltonian formalism for the geometric Hamilton-Jacobi theory on higher-order autonomous dynamical systems described by regular Lagrangian functions.

Effects of Dynamically Weighting Autonomous Rules in an Unmanned Aircraft System (UAS) Flocking Model

DTIC Science & Technology

2014-09-18

methods of flight plan optimization, and yielded such techniques as: parallel A* (Gudaitis, 1994), Multi-Objective Traveling Salesman algorithms...1 Problem Statement...currently their utilization comes with a price: Problem Statement “Today’s unmanned systems require significant human interaction to operate. As

Identification of Stochastically Perturbed Autonomous Systems from Temporal Sequences of Probability Density Functions

NASA Astrophysics Data System (ADS)

Nie, Xiaokai; Luo, Jingjing; Coca, Daniel; Birkin, Mark; Chen, Jing

2018-03-01

The paper introduces a method for reconstructing one-dimensional iterated maps that are driven by an external control input and subjected to an additive stochastic perturbation, from sequences of probability density functions that are generated by the stochastic dynamical systems and observed experimentally.

Dynamic Modeling and Control of Nuclear Reactors Coupled to Closed-Loop Brayton Cycle Systems using SIMULINK{sup TM}

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wright, Steven A.; Sanchez, Travis

2005-02-06

The operation of space reactors for both in-space and planetary operations will require unprecedented levels of autonomy and control. Development of these autonomous control systems will require dynamic system models, effective control methodologies, and autonomous control logic. This paper briefly describes the results of reactor, power-conversion, and control models that are implemented in SIMULINK{sup TM} (Simulink, 2004). SIMULINK{sup TM} is a development environment packaged with MatLab{sup TM} (MatLab, 2004) that allows the creation of dynamic state flow models. Simulation modules for liquid metal, gas cooled reactors, and electrically heated systems have been developed, as have modules for dynamic power-conversion componentsmore » such as, ducting, heat exchangers, turbines, compressors, permanent magnet alternators, and load resistors. Various control modules for the reactor and the power-conversion shaft speed have also been developed and simulated. The modules are compiled into libraries and can be easily connected in different ways to explore the operational space of a number of potential reactor, power-conversion system configurations, and control approaches. The modularity and variability of these SIMULINK{sup TM} models provides a way to simulate a variety of complete power generation systems. To date, both Liquid Metal Reactors (LMR), Gas Cooled Reactors (GCR), and electric heaters that are coupled to gas-dynamics systems and thermoelectric systems have been simulated and are used to understand the behavior of these systems. Current efforts are focused on improving the fidelity of the existing SIMULINK{sup TM} modules, extending them to include isotopic heaters, heat pipes, Stirling engines, and on developing state flow logic to provide intelligent autonomy. The simulation code is called RPC-SIM (Reactor Power and Control-Simulator)« less

Vital Signs Evaluation of Human Behaviour via an Autonomous Body Area Network System

NASA Astrophysics Data System (ADS)

Hussin, S.; Takayama, S.

2016-11-01

Enhancing Quality of Life (QOL) has long been an explicit and implicit goal for individuals, nations, and the world. QOL involves diverse multidimensional factors spanning wealth, physical health, social well-being, and international relationships. This study presents a definition of QOL combining the measurement of health-related QOL with an autonomous Body Area Network System (BANs). A method of evaluating vital signs is performed and linked to physical intensity assistance in exercise. Specifically, BAN acts as a supportive system which can assist a user in monitoring his or her body's parameters, providing real-time feedbacks and dynamically sharing information from any location to one or more users.

Relation between heart beat fluctuations and cyclic alternating pattern during sleep in insomnia patients.

PubMed

de Leon-Lomeli, R; Murguia, J S; Chouvarda, I; Mendez, M O; Gonzalez-Galvan, E; Alba, A; Milioli, G; Grassi, A; Terzano, M G; Parrino, L

2014-01-01

Insomnia is a condition that affects the nervous and muscular system. Thirty percent of the population between 18 and 60 years suffers from insomnia. The effects of this disorder involve problems such as poor school or job performance and traffic accidents. In addition, patients with insomnia present changes in the cardiac function during sleep. Furthermore, the structure of electroencephalographic A-phases, which builds up the Cyclic Alternating Pattern during sleep, is related to the insomnia events. Therefore, the relationship between these brain activations (A-phases) and the autonomic nervous system would be of interest, revealing the interplay of central and autonomic activity during insomnia. With this goal, a study of the relationship between A-phases and heart rate fluctuations is presented. Polysomnography recording of five healthy subjects, five sleep misperception patients and five patients with psychophysiological insomnia were used in the study. Detrended Fluctuation Analysis (DFA) was used in order to evaluate the heart rate dynamics and this was correlated with the number of A-phases. The results suggest that pathological patients present changes in the dynamics of the heart rate. This is reflected in the modification of A-phases dynamics, which seems to modify of heart rate dynamics.

Wind-Based Navigation of a Hot-air Balloon on Titan: A Feasibility Study

NASA Technical Reports Server (NTRS)

Furfaro, Roberto; Lunine, Jonathan I.; Elfes, Alberto; Reh, Kim

2008-01-01

Current analysis of data streamed back to Earth by the Cassini spacecraft features Titan as one of the most exciting places in the solar system. NASA centers and universities around the US, as well as the European Space Agency, are studying the possibility of sending, as part of the next mission to this giant moon of Saturn, a hot-air balloon (Montgolfier-type) for further and more in-depth exploration. The basic idea would be to design a reliable, semi-autonomous, and yet cheap Montgolfier capable of using continuous flow of waste heat from a power source to lift the balloon and sustain its altitude in the Titan environment. In this paper we study the problem of locally navigating a hot-air balloon in the nitrogen-based Titan atmosphere. The basic idea is to define a strategy (i.e. design of a suitable guidance system) that allows autonomous and semi-autonomous navigation of the balloon using the available (and partial) knowledge of the wind structure blowing on the saturnian satellite surface. Starting from first principles we determined the appropriate thermal and dynamical models describing (a) the vertical dynamics of the balloon and (b) the dynamics of the balloon moving on a vertical plane (2-D motion). Next, various non-linear fuzzy-based control strategies have been evaluated, analyzed and implemented in MATLAB to numerically simulate the capability of the system to simultaneously maintain altitude, as well as a scientifically desirable trajectory. We also looked at the ability of the balloon to perform station keeping. The results of the simulation are encouraging and show the effectiveness of such a system to cheaply and effectively perform semiautonomous exploration of Titan.

[Сhaotic dynamics of cardio-intervals in three age groups of indigenous and non-indigenous population of Ugra].

PubMed

Eskov, V M; Khadartsev, A A; Eskov, V V; Vokhmina, J V

2016-01-01

The problem of life expectancy of indigenous and non-indigenous population of northern territories of the Russian Federation is considered in terms of economic growth and industrial development of the northern territories. The importance of prolonging the period of active working age of non-indigenous population of Khanty-Mansi Autonomous Okrug-Ugra and Yamalo-Nenets Autonomous Okrug is increasing. Four directions for possible prolongation of the active life of non-indigenous population were presented. The problem of comparative dynamics of age-related changes of cardiovascular system on three specific age groups of female indigenous and non-indigenous population is being considered. A decrease in volume of quasi-attractors in the phase space of states is equivalent to strengthening of physical activity, which is typical of normal aging. It is proposed to use the mathematical pattern to reduce these volumes in assessing the dynamics of human aging in the North.

Autonomous Evolution of Dynamic Gaits with Two Quadruped Robots

NASA Technical Reports Server (NTRS)

Hornby, Gregory S.; Takamura, Seichi; Yamamoto, Takashi; Fujita, Masahiro

2004-01-01

A challenging task that must be accomplished for every legged robot is creating the walking and running behaviors needed for it to move. In this paper we describe our system for autonomously evolving dynamic gaits on two of Sony's quadruped robots. Our evolutionary algorithm runs on board the robot and uses the robot's sensors to compute the quality of a gait without assistance from the experimenter. First we show the evolution of a pace and trot gait on the OPEN-R prototype robot. With the fastest gait, the robot moves at over 10/min/min., which is more than forty body-lengths/min. While these first gaits are somewhat sensitive to the robot and environment in which they are evolved, we then show the evolution of robust dynamic gaits, one of which is used on the ERS-110, the first consumer version of AIBO.

Containment control of networked autonomous underwater vehicles: A predictor-based neural DSC design.

PubMed

Peng, Zhouhua; Wang, Dan; Wang, Wei; Liu, Lu

2015-11-01

This paper investigates the containment control problem of networked autonomous underwater vehicles in the presence of model uncertainty and unknown ocean disturbances. A predictor-based neural dynamic surface control design method is presented to develop the distributed adaptive containment controllers, under which the trajectories of follower vehicles nearly converge to the dynamic convex hull spanned by multiple reference trajectories over a directed network. Prediction errors, rather than tracking errors, are used to update the neural adaptation laws, which are independent of the tracking error dynamics, resulting in two time-scales to govern the entire system. The stability property of the closed-loop network is established via Lyapunov analysis, and transient property is quantified in terms of L2 norms of the derivatives of neural weights, which are shown to be smaller than the classical neural dynamic surface control approach. Comparative studies are given to show the substantial improvements of the proposed new method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Formation Learning Control of Multiple Autonomous Underwater Vehicles With Heterogeneous Nonlinear Uncertain Dynamics.

PubMed

Yuan, Chengzhi; Licht, Stephen; He, Haibo

2017-09-26

In this paper, a new concept of formation learning control is introduced to the field of formation control of multiple autonomous underwater vehicles (AUVs), which specifies a joint objective of distributed formation tracking control and learning/identification of nonlinear uncertain AUV dynamics. A novel two-layer distributed formation learning control scheme is proposed, which consists of an upper-layer distributed adaptive observer and a lower-layer decentralized deterministic learning controller. This new formation learning control scheme advances existing techniques in three important ways: 1) the multi-AUV system under consideration has heterogeneous nonlinear uncertain dynamics; 2) the formation learning control protocol can be designed and implemented by each local AUV agent in a fully distributed fashion without using any global information; and 3) in addition to the formation control performance, the distributed control protocol is also capable of accurately identifying the AUVs' heterogeneous nonlinear uncertain dynamics and utilizing experiences to improve formation control performance. Extensive simulations have been conducted to demonstrate the effectiveness of the proposed results.

Preliminary Design of an Autonomous Amphibious System

DTIC Science & Technology

2016-09-01

changing vehicle dynamics will require innovative new autonomy algorithms. The developed software architecture, drive-by- wire kit, and supporting...COMMUNICATIONS ARCHITECTURE .................................................12 3.3 DRIVE-BY- WIRE DESIGN...SOFTWARE MATURATION PLANS ......................................................17 4.2 DRIVE-BY- WIRE PLANNED REFINEMENT

A comparative analysis of alternative approaches for quantifying nonlinear dynamics in cardiovascular system.

PubMed

Chen, Yun; Yang, Hui

2013-01-01

Heart rate variability (HRV) analysis has emerged as an important research topic to evaluate autonomic cardiac function. However, traditional time and frequency-domain analysis characterizes and quantify only linear and stationary phenomena. In the present investigation, we made a comparative analysis of three alternative approaches (i.e., wavelet multifractal analysis, Lyapunov exponents and multiscale entropy analysis) for quantifying nonlinear dynamics in heart rate time series. Note that these extracted nonlinear features provide information about nonlinear scaling behaviors and the complexity of cardiac systems. To evaluate the performance, we used 24-hour HRV recordings from 54 healthy subjects and 29 heart failure patients, available in PhysioNet. Three nonlinear methods are evaluated not only individually but also in combination using three classification algorithms, i.e., linear discriminate analysis, quadratic discriminate analysis and k-nearest neighbors. Experimental results show that three nonlinear methods capture nonlinear dynamics from different perspectives and the combined feature set achieves the best performance, i.e., sensitivity 97.7% and specificity 91.5%. Collectively, nonlinear HRV features are shown to have the promise to identify the disorders in autonomic cardiovascular function.

Joint symbolic dynamics as a model-free approach to study interdependence in cardio-respiratory time series.

PubMed

Baumert, Mathias; Brown, Rachael; Duma, Stephen; Broe, G Anthony; Kabir, Muammar M; Macefield, Vaughan G

2012-01-01

Heart rate and respiration display fluctuations that are interlinked by central regulatory mechanisms of the autonomic nervous system (ANS). Joint assessment of respiratory time series along with heart rate variability (HRV) may therefore provide information on ANS dysfunction. The aim of this study was to investigate cardio-respiratory interaction in patients with Parkinson's disease (PD), a neurodegenerative disorder that is associated with progressive ANS dysfunction. Short-term ECG and respiration were recorded in 25 PD patients and 28 healthy controls during rest. To assess ANS dysfunction we analyzed joint symbolic dynamics of heart rate and respiration, cardio-respiratory synchrograms along with heart rate variability. Neither HRV nor cardio-respiratory synchrograms were significantly altered in PD patients. Symbolic analysis, however, identified a significant reduction in cardio-respiratory interactions in PD patients compared to healthy controls (16 ± 3.6 % vs. 20 ± 6.1 %; p= 0.02). In conclusion, joint symbolic analysis of cardio-respiratory dynamics provides a powerful tool to detect early signs of autonomic nervous system dysfunction in Parkinson's disease patients at an early stage of the disease.

Developing Dynamic Field Theory Architectures for Embodied Cognitive Systems with cedar.

PubMed

Lomp, Oliver; Richter, Mathis; Zibner, Stephan K U; Schöner, Gregor

2016-01-01

Embodied artificial cognitive systems, such as autonomous robots or intelligent observers, connect cognitive processes to sensory and effector systems in real time. Prime candidates for such embodied intelligence are neurally inspired architectures. While components such as forward neural networks are well established, designing pervasively autonomous neural architectures remains a challenge. This includes the problem of tuning the parameters of such architectures so that they deliver specified functionality under variable environmental conditions and retain these functions as the architectures are expanded. The scaling and autonomy problems are solved, in part, by dynamic field theory (DFT), a theoretical framework for the neural grounding of sensorimotor and cognitive processes. In this paper, we address how to efficiently build DFT architectures that control embodied agents and how to tune their parameters so that the desired cognitive functions emerge while such agents are situated in real environments. In DFT architectures, dynamic neural fields or nodes are assigned dynamic regimes, that is, attractor states and their instabilities, from which cognitive function emerges. Tuning thus amounts to determining values of the dynamic parameters for which the components of a DFT architecture are in the specified dynamic regime under the appropriate environmental conditions. The process of tuning is facilitated by the software framework cedar , which provides a graphical interface to build and execute DFT architectures. It enables to change dynamic parameters online and visualize the activation states of any component while the agent is receiving sensory inputs in real time. Using a simple example, we take the reader through the workflow of conceiving of DFT architectures, implementing them on embodied agents, tuning their parameters, and assessing performance while the system is coupled to real sensory inputs.

Developing Dynamic Field Theory Architectures for Embodied Cognitive Systems with cedar

PubMed Central

Lomp, Oliver; Richter, Mathis; Zibner, Stephan K. U.; Schöner, Gregor

2016-01-01

Embodied artificial cognitive systems, such as autonomous robots or intelligent observers, connect cognitive processes to sensory and effector systems in real time. Prime candidates for such embodied intelligence are neurally inspired architectures. While components such as forward neural networks are well established, designing pervasively autonomous neural architectures remains a challenge. This includes the problem of tuning the parameters of such architectures so that they deliver specified functionality under variable environmental conditions and retain these functions as the architectures are expanded. The scaling and autonomy problems are solved, in part, by dynamic field theory (DFT), a theoretical framework for the neural grounding of sensorimotor and cognitive processes. In this paper, we address how to efficiently build DFT architectures that control embodied agents and how to tune their parameters so that the desired cognitive functions emerge while such agents are situated in real environments. In DFT architectures, dynamic neural fields or nodes are assigned dynamic regimes, that is, attractor states and their instabilities, from which cognitive function emerges. Tuning thus amounts to determining values of the dynamic parameters for which the components of a DFT architecture are in the specified dynamic regime under the appropriate environmental conditions. The process of tuning is facilitated by the software framework cedar, which provides a graphical interface to build and execute DFT architectures. It enables to change dynamic parameters online and visualize the activation states of any component while the agent is receiving sensory inputs in real time. Using a simple example, we take the reader through the workflow of conceiving of DFT architectures, implementing them on embodied agents, tuning their parameters, and assessing performance while the system is coupled to real sensory inputs. PMID:27853431

Interpersonal Autonomic Physiology: A Systematic Review of the Literature.

PubMed

Palumbo, Richard V; Marraccini, Marisa E; Weyandt, Lisa L; Wilder-Smith, Oliver; McGee, Heather A; Liu, Siwei; Goodwin, Matthew S

2017-05-01

Interpersonal autonomic physiology is defined as the relationship between people's physiological dynamics, as indexed by continuous measures of the autonomic nervous system. Findings from this field of study indicate that physiological activity between two or more people can become associated or interdependent, often referred to as physiological synchrony. Physiological synchrony has been found in both new and established relationships across a range of contexts, and it correlates with a number of psychosocial constructs. Given these findings, interpersonal physiological interactions are theorized to be ubiquitous social processes that co-occur with observable behavior. However, this scientific literature is fragmented, making it difficult to evaluate consistency across reports. In an effort to facilitate more standardized scholarly approaches, this systematic review provides a description of existing work in the area and highlights theoretical, methodological, and statistical issues to be addressed in future interpersonal autonomic physiology research.

Reasoning and planning in dynamic domains: An experiment with a mobile robot

NASA Technical Reports Server (NTRS)

Georgeff, M. P.; Lansky, A. L.; Schoppers, M. J.

1987-01-01

Progress made toward having an autonomous mobile robot reason and plan complex tasks in real-world environments is described. To cope with the dynamic and uncertain nature of the world, researchers use a highly reactive system to which is attributed attitudes of belief, desire, and intention. Because these attitudes are explicitly represented, they can be manipulated and reasoned about, resulting in complex goal-directed and reflective behaviors. Unlike most planning systems, the plans or intentions formed by the system need only be partly elaborated before it decides to act. This allows the system to avoid overly strong expectations about the environment, overly constrained plans of action, and other forms of over-commitment common to previous planners. In addition, the system is continuously reactive and has the ability to change its goals and intentions as situations warrant. Thus, while the system architecture allows for reasoning about means and ends in much the same way as traditional planners, it also posseses the reactivity required for survival in complex real-world domains. The system was tested using SRI's autonomous robot (Flakey) in a scenario involving navigation and the performance of an emergency task in a space station scenario.

Multiple estimation channel decoupling and optimization method based on inverse system

NASA Astrophysics Data System (ADS)

Wu, Peng; Mu, Rongjun; Zhang, Xin; Deng, Yanpeng

2018-03-01

This paper addressed the intelligent autonomous navigation request of intelligent deformation missile, based on the intelligent deformation missile dynamics and kinematics modeling, navigation subsystem solution method and error modeling, and then focuses on the corresponding data fusion and decision fusion technology, decouples the sensitive channel of the filter input through the inverse system of design dynamics to reduce the influence of sudden change of the measurement information on the filter input. Then carrying out a series of simulation experiments, which verified the feasibility of the inverse system decoupling algorithm effectiveness.

Autonomous choices among deterministic evolution-laws as source of uncertainty

NASA Astrophysics Data System (ADS)

Trujillo, Leonardo; Meyroneinc, Arnaud; Campos, Kilver; Rendón, Otto; Sigalotti, Leonardo Di G.

2018-03-01

We provide evidence of an extreme form of sensitivity to initial conditions in a family of one-dimensional self-ruling dynamical systems. We prove that some hyperchaotic sequences are closed-form expressions of the orbits of these pseudo-random dynamical systems. Each chaotic system in this family exhibits a sensitivity to initial conditions that encompasses the sequence of choices of the evolution rule in some collection of maps. This opens a possibility to extend current theories of complex behaviors on the basis of intrinsic uncertainty in deterministic chaos.

A practical application of the geometrical theory on fibered manifolds to an autonomous bicycle motion in mechanical system with nonholonomic constraints

NASA Astrophysics Data System (ADS)

Haddout, Soufiane

2018-01-01

The equations of motion of a bicycle are highly nonlinear and rolling of wheels without slipping can only be expressed by nonholonomic constraint equations. A geometrical theory of general nonholonomic constrained systems on fibered manifolds and their jet prolongations, based on so-called Chetaev-type constraint forces, was proposed and developed in the last decade by O. Krupková (Rossi) in 1990's. Her approach is suitable for study of all kinds of mechanical systems-without restricting to Lagrangian, time-independent, or regular ones, and is applicable to arbitrary constraints (holonomic, semiholonomic, linear, nonlinear or general nonholonomic). The goal of this paper is to apply Krupková's geometric theory of nonholonomic mechanical systems to study a concrete problem in nonlinear nonholonomic dynamics, i.e., autonomous bicycle. The dynamical model is preserved in simulations in its original nonlinear form without any simplifying. The results of numerical solutions of constrained equations of motion, derived within the theory, are in good agreement with measurements and thus they open the possibility of direct application of the theory to practical situations.

Dynamic Inversion based Control of a Docking Mechanism

NASA Technical Reports Server (NTRS)

Kulkarni, Nilesh V.; Ippolito, Corey; Krishnakumar, Kalmanje

2006-01-01

The problem of position and attitude control of the Stewart platform based docking mechanism is considered motivated by its future application in space missions requiring the autonomous docking capability. The control design is initiated based on the framework of the intelligent flight control architecture being developed at NASA Ames Research Center. In this paper, the baseline position and attitude control system is designed using dynamic inversion with proportional-integral augmentation. The inverse dynamics uses a Newton-Euler formulation that includes the platform dynamics, the dynamics of the individual legs along with viscous friction in the joints. Simulation results are presented using forward dynamics simulated by a commercial physics engine that builds the system as individual elements with appropriate joints and uses constrained numerical integration,

High-precision GPS autonomous platforms for sea ice dynamics and physical oceanography

NASA Astrophysics Data System (ADS)

Elosegui, P.; Wilkinson, J.; Olsson, M.; Rodwell, S.; James, A.; Hagan, B.; Hwang, B.; Forsberg, R.; Gerdes, R.; Johannessen, J.; Wadhams, P.; Nettles, M.; Padman, L.

2012-12-01

Project "Arctic Ocean sea ice and ocean circulation using satellite methods" (SATICE), is the first high-rate, high-precision, continuous GPS positioning experiment on sea ice in the Arctic Ocean. The SATICE systems collect continuous, dual-frequency carrier-phase GPS data while drifting on sea ice. Additional geophysical measurements also collected include ocean water pressure, ocean surface salinity, atmospheric pressure, snow-depth, air-ice-ocean temperature profiles, photographic imagery, and others, enabling sea ice drift, freeboard, weather, ice mass balance, and sea-level height determination. Relatively large volumes of data from each buoy are streamed over a satellite link to a central computer on the Internet in near real time, where they are processed to estimate the time-varying buoy positions. SATICE system obtains continuous GPS data at sub-minute intervals with a positioning precision of a few centimetres in all three dimensions. Although monitoring of sea ice motions goes back to the early days of satellite observations, these autonomous platforms bring out a level of spatio-temporal detail that has never been seen before, especially in the vertical axis. These high-resolution data allows us to address new polar science questions and challenge our present understanding of both sea ice dynamics and Arctic oceanography. We will describe the technology behind this new autonomous platform, which could also be adapted to other applications that require high resolution positioning information with sustained operations and observations in the polar marine environment, and present results pertaining to sea ice dynamics and physical oceanography.

Autonomous terrain characterization and modelling for dynamic control of unmanned vehicles

NASA Technical Reports Server (NTRS)

Talukder, A.; Manduchi, R.; Castano, R.; Owens, K.; Matthies, L.; Castano, A.; Hogg, R.

2002-01-01

This end-to-end obstacle negotiation system is envisioned to be useful in optimized path planning and vehicle navigation in terrain conditions cluttered with vegetation, bushes, rocks, etc. Results on natural terrain with various natural materials are presented.

A three-dimensional autonomous nonlinear dynamical system modelling equatorial ocean flows

NASA Astrophysics Data System (ADS)

Ionescu-Kruse, Delia

2018-04-01

We investigate a nonlinear three-dimensional model for equatorial flows, finding exact solutions that capture the most relevant geophysical features: depth-dependent currents, poleward or equatorial surface drift and a vertical mixture of upward and downward motions.

Control of Crazyflie nano quadcopter using Simulink

NASA Astrophysics Data System (ADS)

Gopabhat Madhusudhan, Meghana

This thesis focuses on developing a mathematical model in Simulink to Crazyflie, an open source platform. Attitude, altitude and position controllers of a Crazyflie are designed in the mathematical model. The mathematical model is developed based on the quadcopter system dynamics using a non-linear approach. The parameters of translational and rotational dynamics of the quadcopter system are linearized and tuned individually. The tuned attitude and altitude controllers from the mathematical model are implemented on real time Crazyflie Simulink model to achieve autonomous and controlled flight.

Application of neural networks to autonomous rendezvous and docking of space vehicles

NASA Technical Reports Server (NTRS)

Dabney, Richard W.

1992-01-01

NASA-Marshall has investigated the feasibility of numerous autonomous rendezvous and docking (ARD) candidate techniques. Neural networks have been studied as a viable basis for such systems' implementation, due to their intrinsic representation of such nonlinear functions as those for which analytical solutions are either difficult or nonexistent. Neural networks are also able to recognize and adapt to changes in their dynamic environment, thereby enhancing redundancy and fault tolerance. Outstanding performance has been obtained from ARD azimuth, elevation, and roll networks of this type.

Development of Lidar Sensor Systems for Autonomous Safe Landing on Planetary Bodies

NASA Technical Reports Server (NTRS)

Amzajerdian, Farzin; Pierottet, Diego F.; Petway, Larry B.; Vanek, Michael D.

2010-01-01

Lidar has been identified by NASA as a key technology for enabling autonomous safe landing of future robotic and crewed lunar landing vehicles. NASA LaRC has been developing three laser/lidar sensor systems under the ALHAT project. The capabilities of these Lidar sensor systems were evaluated through a series of static tests using a calibrated target and through dynamic tests aboard helicopters and a fixed wing aircraft. The airborne tests were performed over Moon-like terrain in the California and Nevada deserts. These tests provided the necessary data for the development of signal processing software, and algorithms for hazard detection and navigation. The tests helped identify technology areas needing improvement and will also help guide future technology advancement activities.

Knowledge/geometry-based Mobile Autonomous Robot Simulator (KMARS)

NASA Technical Reports Server (NTRS)

Cheng, Linfu; Mckendrick, John D.; Liu, Jeffrey

1990-01-01

Ongoing applied research is focused on developing guidance system for robot vehicles. Problems facing the basic research needed to support this development (e.g., scene understanding, real-time vision processing, etc.) are major impediments to progress. Due to the complexity and the unpredictable nature of a vehicle's area of operation, more advanced vehicle control systems must be able to learn about obstacles within the range of its sensor(s). A better understanding of the basic exploration process is needed to provide critical support to developers of both sensor systems and intelligent control systems which can be used in a wide spectrum of autonomous vehicles. Elcee Computek, Inc. has been working under contract to the Flight Dynamics Laboratory, Wright Research and Development Center, Wright-Patterson AFB, Ohio to develop a Knowledge/Geometry-based Mobile Autonomous Robot Simulator (KMARS). KMARS has two parts: a geometry base and a knowledge base. The knowledge base part of the system employs the expert-system shell CLIPS ('C' Language Integrated Production System) and necessary rules that control both the vehicle's use of an obstacle detecting sensor and the overall exploration process. The initial phase project has focused on the simulation of a point robot vehicle operating in a 2D environment.

An Approach to Model Based Testing of Multiagent Systems

PubMed Central

Nadeem, Aamer

2015-01-01

Autonomous agents perform on behalf of the user to achieve defined goals or objectives. They are situated in dynamic environment and are able to operate autonomously to achieve their goals. In a multiagent system, agents cooperate with each other to achieve a common goal. Testing of multiagent systems is a challenging task due to the autonomous and proactive behavior of agents. However, testing is required to build confidence into the working of a multiagent system. Prometheus methodology is a commonly used approach to design multiagents systems. Systematic and thorough testing of each interaction is necessary. This paper proposes a novel approach to testing of multiagent systems based on Prometheus design artifacts. In the proposed approach, different interactions between the agent and actors are considered to test the multiagent system. These interactions include percepts and actions along with messages between the agents which can be modeled in a protocol diagram. The protocol diagram is converted into a protocol graph, on which different coverage criteria are applied to generate test paths that cover interactions between the agents. A prototype tool has been developed to generate test paths from protocol graph according to the specified coverage criterion. PMID:25874263

How Can Music Influence the Autonomic Nervous System Response in Patients with Severe Disorder of Consciousness?

PubMed

Riganello, Francesco; Cortese, Maria D; Arcuri, Francesco; Quintieri, Maria; Dolce, Giuliano

2015-01-01

Activations to pleasant and unpleasant musical stimuli were observed within an extensive neuronal network and different brain structures, as well as in the processing of the syntactic and semantic aspects of the music. Previous studies evidenced a correlation between autonomic activity and emotion evoked by music listening in patients with Disorders of Consciousness (DoC). In this study, we analyzed retrospectively the autonomic response to musical stimuli by mean of normalized units of Low Frequency (nuLF) and Sample Entropy (SampEn) of Heart Rate Variability (HRV) parameters, and their possible correlation to the different complexity of four musical samples (i.e., Mussorgsky, Tchaikovsky, Grieg, and Boccherini) in Healthy subjects and Vegetative State/Unresponsive Wakefulness Syndrome (VS/UWS) patients. The complexity of musical sample was based on Formal Complexity and General Dynamics parameters defined by Imberty's semiology studies. The results showed a significant difference between the two groups for SampEn during the listening of Mussorgsky's music and for nuLF during the listening of Boccherini and Mussorgsky's music. Moreover, the VS/UWS group showed a reduction of nuLF as well as SampEn comparing music of increasing Formal Complexity and General Dynamics. These results put in evidence how the internal structure of the music can change the autonomic response in patients with DoC. Further investigations are required to better comprehend how musical stimulation can modify the autonomic response in DoC patients, in order to administer the stimuli in a more effective way.

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2004-01-01

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation thru the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The application of many different types of AI techniques for flight will be explored during this research effort. The research concentration will be directed to the application of different AI methods within the UAV arena. By evaluating AI approaches, which will include Expert Systems, Neural Networks, Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI techniques applied to achieving true autonomous operation of these systems thus providing new intellectual merit to this research field. The major area of discussion will be limited to the UAV. The systems of interest include small aircraft, insects, and miniature aircraft. Although flight systems will be explored, the benefits should apply to many Unmanned Vehicles such as: Rovers, Ocean Explorers, Robots, and autonomous operation systems. The flight system will be broken down into control agents that will represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework of applying a Security Overseer will be added in an attempt to address errors, emergencies, failures, damage, or over dynamic environment. The chosen control problem was the landing phase of UAV operation. The initial results from simulation in FlightGear are presented.

Monitoring fetal maturation—objectives, techniques and indices of autonomic function*

PubMed Central

Hoyer, Dirk; Żebrowski, Jan; Cysarz, Dirk; Gonçalves, Hernâni; Pytlik, Adelina; Amorim-Costa, Célia; Bernardes, João; Ayres-de-Campos, Diogo; Witte, Otto W; Schleußner, Ekkehard; Stroux, Lisa; Redman, Christopher; Georgieva, Antoniya; Payne, Stephen; Clifford, Gari; Signorini, Maria G; Magenes, Giovanni; Andreotti, Fernando; Malberg, Hagen; Zaunseder, Sebastian; Lakhno, Igor; Schneider, Uwe

2017-01-01

Objective Monitoring the fetal behavior does not only have implications for acute care but also for identifying developmental disturbances that burden the entire later life. The concept, of ‘fetal programming’, also known as ‘developmental origins of adult disease hypothesis’, e.g. applies for cardiovascular, metabolic, hyperkinetic, cognitive disorders. Since the autonomic nervous system is involved in all of those systems, cardiac autonomic control may provide relevant functional diagnostic and prognostic information. Approach The fetal heart rate patterns (HRP) are one of the few functional signals in the prenatal period that relate to autonomic control and, therefore, is key to fetal autonomic assessment. The development of sensitive markers of fetal maturation and its disturbances requires the consideration of physiological fundamentals, recording technology and HRP parameters of autonomic control. Main Results Based on the ESGCO2016 special session on monitoring the fetal maturation we herein report the most recent results on: (i) functional fetal autonomic brain age score (fABAS), Recurrence Quantitative Analysis and Binary Symbolic Dynamics of complex HRP resolve specific maturation periods, (ii) magnetocardiography (MCG) based fABAS was validated for cardiotocography (CTG), (iii) 30 min recordings are sufficient for obtaining episodes of high variability, important for intrauterine growth restriction (IUGR) detection in handheld Doppler, (iv) novel parameters from PRSA to identify Intra IUGR fetuses, (v) evaluation of fetal electrocardiographic (ECG) recordings, (vi) correlation between maternal and fetal HRV is disturbed in pre-eclampsia. Significance The reported novel developments significantly extend the possibilities for the established CTG methodology. Novel HRP indices improve the accuracy of assessment due to their more appropriate consideration of complex autonomic processes across the recording technologies (CTG, handheld Doppler, MCG, ECG). The ultimate objective is their dissemination into routine practice and studies of fetal developmental disturbances with implications for programming of adult diseases. PMID:28186000

Visibility graph analysis on heartbeat dynamics of meditation training

NASA Astrophysics Data System (ADS)

Jiang, Sen; Bian, Chunhua; Ning, Xinbao; Ma, Qianli D. Y.

2013-06-01

We apply the visibility graph analysis to human heartbeat dynamics by constructing the complex networks of heartbeat interval time series and investigating the statistical properties of the network before and during chi and yoga meditation. The experiment results show that visibility graph analysis can reveal the dynamical changes caused by meditation training manifested as regular heartbeat, which is closely related to the adjustment of autonomous neural system, and visibility graph analysis is effective to evaluate the effect of meditation.

Initial Results from an Energy-Aware Airborne Dynamic, Data-Driven Application System Performing Sampling in Coherent Boundary-Layer Structures

NASA Astrophysics Data System (ADS)

Frew, E.; Argrow, B. M.; Houston, A. L.; Weiss, C.

2014-12-01

The energy-aware airborne dynamic, data-driven application system (EA-DDDAS) performs persistent sampling in complex atmospheric conditions by exploiting wind energy using the dynamic data-driven application system paradigm. The main challenge for future airborne sampling missions is operation with tight integration of physical and computational resources over wireless communication networks, in complex atmospheric conditions. The physical resources considered here include sensor platforms, particularly mobile Doppler radar and unmanned aircraft, the complex conditions in which they operate, and the region of interest. Autonomous operation requires distributed computational effort connected by layered wireless communication. Onboard decision-making and coordination algorithms can be enhanced by atmospheric models that assimilate input from physics-based models and wind fields derived from multiple sources. These models are generally too complex to be run onboard the aircraft, so they need to be executed in ground vehicles in the field, and connected over broadband or other wireless links back to the field. Finally, the wind field environment drives strong interaction between the computational and physical systems, both as a challenge to autonomous path planning algorithms and as a novel energy source that can be exploited to improve system range and endurance. Implementation details of a complete EA-DDDAS will be provided, along with preliminary flight test results targeting coherent boundary-layer structures.

A fuzzy logic control in adjustable autonomy of a multi-agent system for an automated elderly movement monitoring application.

PubMed

Mostafa, Salama A; Mustapha, Aida; Mohammed, Mazin Abed; Ahmad, Mohd Sharifuddin; Mahmoud, Moamin A

2018-04-01

Autonomous agents are being widely used in many systems, such as ambient assisted-living systems, to perform tasks on behalf of humans. However, these systems usually operate in complex environments that entail uncertain, highly dynamic, or irregular workload. In such environments, autonomous agents tend to make decisions that lead to undesirable outcomes. In this paper, we propose a fuzzy-logic-based adjustable autonomy (FLAA) model to manage the autonomy of multi-agent systems that are operating in complex environments. This model aims to facilitate the autonomy management of agents and help them make competent autonomous decisions. The FLAA model employs fuzzy logic to quantitatively measure and distribute autonomy among several agents based on their performance. We implement and test this model in the Automated Elderly Movements Monitoring (AEMM-Care) system, which uses agents to monitor the daily movement activities of elderly users and perform fall detection and prevention tasks in a complex environment. The test results show that the FLAA model improves the accuracy and performance of these agents in detecting and preventing falls. Copyright © 2018 Elsevier B.V. All rights reserved.

Pulse-density modulation control of chemical oscillation far from equilibrium in a droplet open-reactor system

PubMed Central

Sugiura, Haruka; Ito, Manami; Okuaki, Tomoya; Mori, Yoshihito; Kitahata, Hiroyuki; Takinoue, Masahiro

2016-01-01

The design, construction and control of artificial self-organized systems modelled on dynamical behaviours of living systems are important issues in biologically inspired engineering. Such systems are usually based on complex reaction dynamics far from equilibrium; therefore, the control of non-equilibrium conditions is required. Here we report a droplet open-reactor system, based on droplet fusion and fission, that achieves dynamical control over chemical fluxes into/out of the reactor for chemical reactions far from equilibrium. We mathematically reveal that the control mechanism is formulated as pulse-density modulation control of the fusion–fission timing. We produce the droplet open-reactor system using microfluidic technologies and then perform external control and autonomous feedback control over autocatalytic chemical oscillation reactions far from equilibrium. We believe that this system will be valuable for the dynamical control over self-organized phenomena far from equilibrium in chemical and biomedical studies. PMID:26786848

Pulse-density modulation control of chemical oscillation far from equilibrium in a droplet open-reactor system.

PubMed

Sugiura, Haruka; Ito, Manami; Okuaki, Tomoya; Mori, Yoshihito; Kitahata, Hiroyuki; Takinoue, Masahiro

2016-01-20

The design, construction and control of artificial self-organized systems modelled on dynamical behaviours of living systems are important issues in biologically inspired engineering. Such systems are usually based on complex reaction dynamics far from equilibrium; therefore, the control of non-equilibrium conditions is required. Here we report a droplet open-reactor system, based on droplet fusion and fission, that achieves dynamical control over chemical fluxes into/out of the reactor for chemical reactions far from equilibrium. We mathematically reveal that the control mechanism is formulated as pulse-density modulation control of the fusion-fission timing. We produce the droplet open-reactor system using microfluidic technologies and then perform external control and autonomous feedback control over autocatalytic chemical oscillation reactions far from equilibrium. We believe that this system will be valuable for the dynamical control over self-organized phenomena far from equilibrium in chemical and biomedical studies.

Mind-body relationships in elite apnea divers during breath holding: a study of autonomic responses to acute hypoxemia

PubMed Central

Laurino, Marco; Menicucci, Danilo; Mastorci, Francesca; Allegrini, Paolo; Piarulli, Andrea; Scilingo, Enzo P.; Bedini, Remo; Pingitore, Alessandro; Passera, Mirko; L'Abbate, Antonio; Gemignani, Angelo

2011-01-01

The mental control of ventilation with all associated phenomena, from relaxation to modulation of emotions, from cardiovascular to metabolic adaptations, constitutes a psychophysiological condition characterizing voluntary breath-holding (BH). BH induces several autonomic responses, involving both autonomic cardiovascular and cutaneous pathways, whose characterization is the main aim of this study. Electrocardiogram and skin conductance (SC) recordings were collected from 14 elite divers during three conditions: free breathing (FB), normoxic phase of BH (NPBH) and hypoxic phase of BH (HPBH). Thus, we compared a set of features describing signal dynamics between the three experimental conditions: from heart rate variability (HRV) features (in time and frequency-domains and by using nonlinear methods) to rate and shape of spontaneous SC responses (SCRs). The main result of the study rises by applying a Factor Analysis to the subset of features significantly changed in the two BH phases. Indeed, the Factor Analysis allowed to uncover the structure of latent factors which modeled the autonomic response: a factor describing the autonomic balance (AB), one the information increase rate (IIR), and a latter the central nervous system driver (CNSD). The BH did not disrupt the FB factorial structure, and only few features moved among factors. Factor Analysis indicates that during BH (1) only the SC described the emotional output, (2) the sympathetic tone on heart did not change, (3) the dynamics of interbeats intervals showed an increase of long-range correlation that anticipates the HPBH, followed by a drop to a random behavior. In conclusion, data show that the autonomic control on heart rate and SC are differentially modulated during BH, which could be related to a more pronounced effect on emotional control induced by the mental training to BH. PMID:22461774

AGARD Flight Test Techniques Series. Volume 2. Identification of Dynamic Systems

DTIC Science & Technology

1985-01-01

should not depend upon it to solve the problem autonomously. The analyst’s strong point is in formulating the problem; the computer’s strength is in...of derivation for the output-error method is to reduce the problem to the static form of Chapter 5. We will see that the dinamic system make- the

Multistability and hidden attractors in a relay system with hysteresis

NASA Astrophysics Data System (ADS)

Zhusubaliyev, Zhanybai T.; Mosekilde, Erik; Rubanov, Vasily G.; Nabokov, Roman A.

2015-06-01

For nonlinear dynamic systems with switching control, the concept of a "hidden attractor" naturally applies to a stable dynamic state that either (1) coexists with the stable switching cycle or (2), if the switching cycle is unstable, has a basin of attraction that does not intersect with the neighborhood of that cycle. We show how the equilibrium point of a relay system disappears in a boundary-equilibrium bifurcation as the system enters the region of autonomous switching dynamics and demonstrate experimentally how a relay system can exhibit large amplitude chaotic oscillations at high values of the supply voltage. By investigating a four-dimensional model of the experimental relay system we finally show how a variety of hidden periodic, quasiperiodic and chaotic attractors arise, transform and disappear through different bifurcations.

Attractors of equations of non-Newtonian fluid dynamics

NASA Astrophysics Data System (ADS)

Zvyagin, V. G.; Kondrat'ev, S. K.

2014-10-01

This survey describes a version of the trajectory-attractor method, which is applied to study the limit asymptotic behaviour of solutions of equations of non-Newtonian fluid dynamics. The trajectory-attractor method emerged in papers of the Russian mathematicians Vishik and Chepyzhov and the American mathematician Sell under the condition that the corresponding trajectory spaces be invariant under the translation semigroup. The need for such an approach was caused by the fact that for many equations of mathematical physics for which the Cauchy initial-value problem has a global (weak) solution with respect to the time, the uniqueness of such a solution has either not been established or does not hold. In particular, this is the case for equations of fluid dynamics. At the same time, trajectory spaces invariant under the translation semigroup could not be constructed for many equations of non-Newtonian fluid dynamics. In this connection, a different approach to the construction of trajectory attractors for dissipative systems was proposed in papers of Zvyagin and Vorotnikov without using invariance of trajectory spaces under the translation semigroup and is based on the topological lemma of Shura-Bura. This paper presents examples of equations of non-Newtonian fluid dynamics (the Jeffreys system describing movement of the Earth's crust, the model of motion of weak aqueous solutions of polymers, a system with memory) for which the aforementioned construction is used to prove the existence of attractors in both the autonomous and the non-autonomous cases. At the beginning of the paper there is also a brief exposition of the results of Ladyzhenskaya on the existence of attractors of the two-dimensional Navier-Stokes system and the result of Vishik and Chepyzhov for the case of attractors of the three-dimensional Navier-Stokes system. Bibliography: 34 titles.

Optimization design about gimbal structure of high-precision autonomous celestial navigation tracking mirror system

NASA Astrophysics Data System (ADS)

Huang, Wei; Yang, Xiao-xu; Han, Jun-feng; Wei, Yu; Zhang, Jing; Xie, Mei-lin; Yue, Peng

2016-01-01

High precision tracking platform of celestial navigation with control mirror servo structure form, to solve the disadvantages of big volume and rotational inertia, slow response speed, and so on. It improved the stability and tracking accuracy of platform. Due to optical sensor and mirror are installed on the middle-gimbal, stiffness and resonant frequency requirement for high. Based on the application of finite element modality analysis theory, doing Research on dynamic characteristics of the middle-gimbal, and ANSYS was used for the finite element dynamic emulator analysis. According to the result of the computer to find out the weak links of the structure, and Put forward improvement suggestions and reanalysis. The lowest resonant frequency of optimization middle-gimbal avoid the bandwidth of the platform servo mechanism, and much higher than the disturbance frequency of carrier aircraft, and reduces mechanical resonance of the framework. Reaching provides a theoretical basis for the whole machine structure optimization design of high-precision of autonomous Celestial navigation tracking mirror system.

Automated Aerial Refueling Hitches a Ride on AFF

NASA Technical Reports Server (NTRS)

Hansen, Jennifer L.; Murray, James E.; Bever, Glenn; Campos, Norma V.; Schkolnik, Gerard

2007-01-01

The recent introduction of uninhabited aerial vehicles [UAVs (basically, remotely piloted or autonomous aircraft)] has spawned new developments in autonomous operation and posed new challenges. Automated aerial refueling (AAR) is a capability that will enable UAVs to travel greater distances and loiter longer over targets. NASA Dryden Flight Research Center, in cooperation with the Defense Advanced Research Projects Agency (DARPA), the Naval Air Systems Command (NAVAIR), the Naval Air Force Pacific Fleet, and the Air Force Research Laboratory, rapidly conceived and accomplished an AAR flight research project focused on collecting a unique, high-quality database on the dynamics of the hose and drogue of an aerial refueling system. This flight-derived database would be used to validate mathematical models of the dynamics in support of design and analysis of AAR systems for future UAVs. The project involved the use of two Dryden F/A-18 airplanes and an S-3 hose-drogue refueling store on loan from the Navy. In this year-long project, which was started on October 1, 2002, 583 research maneuvers were completed during 23 flights.

UPenn Multi-Robot Unmanned Vehicle System (MAGIC)

DTIC Science & Technology

2014-05-05

unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 UPenn Multi-Robot Unmanned Vehicle System (MAGIC) AFOSR Final Report PI... user interface, the Strategy/Plan operator allows the system to autonomously task the nearest available UGVs to plan and coordinate their movements and...threats in a dynamic urban environment with minimal human guidance. The custom hardware systems consist of robust and complementary sensors, integrated

Performance analysis of Integrated Communication and Control System networks

NASA Technical Reports Server (NTRS)

Halevi, Y.; Ray, A.

1990-01-01

This paper presents statistical analysis of delays in Integrated Communication and Control System (ICCS) networks that are based on asynchronous time-division multiplexing. The models are obtained in closed form for analyzing control systems with randomly varying delays. The results of this research are applicable to ICCS design for complex dynamical processes like advanced aircraft and spacecraft, autonomous manufacturing plants, and chemical and processing plants.

Itinerancy of money

NASA Astrophysics Data System (ADS)

Yasutomi, Ayumu

2003-09-01

Previously, I studied [Physica D 82, 180-194 (1995)] the emergence and collapse of money in a computer simulation model. In this paper I will revisit the same topic, building a model in the same line. I discuss this problem from the viewpoint of chaotic itinerancy. Money is the most popular system for evading the difficulty of exchange under division of labor. It emerges autonomously from exchanges among selfish agents which behave as automata. And such emergent money collapses autonomously. I describe money as a structure in economic space, explaining its autonomous emergence and collapse as two phases of the same phenomenon. The key element in this phenomenon is the switch of the meaning of strategies. This is caused by the drastic change of environment caused by the emergence of a structure. This dynamics shares some aspects with chaotic itinerancy.

Real-time sensor validation and fusion for distributed autonomous sensors

NASA Astrophysics Data System (ADS)

Yuan, Xiaojing; Li, Xiangshang; Buckles, Bill P.

2004-04-01

Multi-sensor data fusion has found widespread applications in industrial and research sectors. The purpose of real time multi-sensor data fusion is to dynamically estimate an improved system model from a set of different data sources, i.e., sensors. This paper presented a systematic and unified real time sensor validation and fusion framework (RTSVFF) based on distributed autonomous sensors. The RTSVFF is an open architecture which consists of four layers - the transaction layer, the process fusion layer, the control layer, and the planning layer. This paradigm facilitates distribution of intelligence to the sensor level and sharing of information among sensors, controllers, and other devices in the system. The openness of the architecture also provides a platform to test different sensor validation and fusion algorithms and thus facilitates the selection of near optimal algorithms for specific sensor fusion application. In the version of the model presented in this paper, confidence weighted averaging is employed to address the dynamic system state issue noted above. The state is computed using an adaptive estimator and dynamic validation curve for numeric data fusion and a robust diagnostic map for decision level qualitative fusion. The framework is then applied to automatic monitoring of a gas-turbine engine, including a performance comparison of the proposed real-time sensor fusion algorithms and a traditional numerical weighted average.

Intelligent control and adaptive systems; Proceedings of the Meeting, Philadelphia, PA, Nov. 7, 8, 1989

NASA Technical Reports Server (NTRS)

Rodriguez, Guillermo (Editor)

1990-01-01

Various papers on intelligent control and adaptive systems are presented. Individual topics addressed include: control architecture for a Mars walking vehicle, representation for error detection and recovery in robot task plans, real-time operating system for robots, execution monitoring of a mobile robot system, statistical mechanics models for motion and force planning, global kinematics for manipulator planning and control, exploration of unknown mechanical assemblies through manipulation, low-level representations for robot vision, harmonic functions for robot path construction, simulation of dual behavior of an autonomous system. Also discussed are: control framework for hand-arm coordination, neural network approach to multivehicle navigation, electronic neural networks for global optimization, neural network for L1 norm linear regression, planning for assembly with robot hands, neural networks in dynamical systems, control design with iterative learning, improved fuzzy process control of spacecraft autonomous rendezvous using a genetic algorithm.

Various Types of Coexisting Attractors in a New 4D Autonomous Chaotic System

NASA Astrophysics Data System (ADS)

Lai, Qiang; Akgul, Akif; Zhao, Xiao-Wen; Pei, Huiqin

An unique 4D autonomous chaotic system with signum function term is proposed in this paper. The system has four unstable equilibria and various types of coexisting attractors appear. Four-wing and four-scroll strange attractors are observed in the system and they will be broken into two coexisting butterfly attractors and two coexisting double-scroll attractors with the variation of the parameters. Numerical simulation shows that the system has various types of multiple coexisting attractors including two butterfly attractors with four limit cycles, two double-scroll attractors with a limit cycle, four single-scroll strange attractors, four limit cycles with regard to different parameters and initial values. The coexistence of the attractors is determined by the bifurcation diagrams. The chaotic and hyperchaotic properties of the attractors are verified by the Lyapunov exponents. Moreover, we present an electronic circuit to experimentally realize the dynamic behavior of the system.

A Benchmark Problem for Development of Autonomous Structural Modal Identification

NASA Technical Reports Server (NTRS)

Pappa, Richard S.; Woodard, Stanley E.; Juang, Jer-Nan

1996-01-01

This paper summarizes modal identification results obtained using an autonomous version of the Eigensystem Realization Algorithm on a dynamically complex, laboratory structure. The benchmark problem uses 48 of 768 free-decay responses measured in a complete modal survey test. The true modal parameters of the structure are well known from two previous, independent investigations. Without user involvement, the autonomous data analysis identified 24 to 33 structural modes with good to excellent accuracy in 62 seconds of CPU time (on a DEC Alpha 4000 computer). The modal identification technique described in the paper is the baseline algorithm for NASA's Autonomous Dynamics Determination (ADD) experiment scheduled to fly on International Space Station assembly flights in 1997-1999.

Automation of orbit determination functions for National Aeronautics and Space Administration (NASA)-supported satellite missions

NASA Technical Reports Server (NTRS)

Mardirossian, H.; Beri, A. C.; Doll, C. E.

1990-01-01

The Flight Dynamics Facility (FDF) at Goddard Space Flight Center (GSFC) provides spacecraft trajectory determination for a wide variety of National Aeronautics and Space Administration (NASA)-supported satellite missions, using the Tracking Data Relay Satellite System (TDRSS) and Ground Spaceflight and Tracking Data Network (GSTDN). To take advantage of computerized decision making processes that can be used in spacecraft navigation, the Orbit Determination Automation System (ODAS) was designed, developed, and implemented as a prototype system to automate orbit determination (OD) and orbit quality assurance (QA) functions performed by orbit operations. Based on a machine-resident generic schedule and predetermined mission-dependent QA criteria, ODAS autonomously activates an interface with the existing trajectory determination system using a batch least-squares differential correction algorithm to perform the basic OD functions. The computational parameters determined during the OD are processed to make computerized decisions regarding QA, and a controlled recovery process is activated when the criteria are not satisfied. The complete cycle is autonomous and continuous. ODAS was extensively tested for performance under conditions resembling actual operational conditions and found to be effective and reliable for extended autonomous OD. Details of the system structure and function are discussed, and test results are presented.

Automation of orbit determination functions for National Aeronautics and Space Administration (NASA)-supported satellite missions

NASA Technical Reports Server (NTRS)

Mardirossian, H.; Heuerman, K.; Beri, A.; Samii, M. V.; Doll, C. E.

1989-01-01

The Flight Dynamics Facility (FDF) at Goddard Space Flight Center (GSFC) provides spacecraft trajectory determination for a wide variety of National Aeronautics and Space Administration (NASA)-supported satellite missions, using the Tracking Data Relay Satellite System (TDRSS) and Ground Spaceflight and Tracking Data Network (GSTDN). To take advantage of computerized decision making processes that can be used in spacecraft navigation, the Orbit Determination Automation System (ODAS) was designed, developed, and implemented as a prototype system to automate orbit determination (OD) and orbit quality assurance (QA) functions performed by orbit operations. Based on a machine-resident generic schedule and predetermined mission-dependent QA criteria, ODAS autonomously activates an interface with the existing trajectory determination system using a batch least-squares differential correction algorithm to perform the basic OD functions. The computational parameters determined during the OD are processed to make computerized decisions regarding QA, and a controlled recovery process isactivated when the criteria are not satisfied. The complete cycle is autonomous and continuous. ODAS was extensively tested for performance under conditions resembling actual operational conditions and found to be effective and reliable for extended autonomous OD. Details of the system structure and function are discussed, and test results are presented.

Neural dynamic optimization for control systems. I. Background.

PubMed

Seong, C Y; Widrow, B

2001-01-01

The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper mainly describes the background and motivations for the development of NDO, while the two other subsequent papers of this topic present the theory of NDO and demonstrate the method with several applications including control of autonomous vehicles and of a robot arm, respectively.

Neural dynamic optimization for control systems.III. Applications.

PubMed

Seong, C Y; Widrow, B

2001-01-01

For pt.II. see ibid., p. 490-501. The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper demonstrates NDO with several applications including control of autonomous vehicles and of a robot-arm, while the two other companion papers of this topic describes the background for the development of NDO and present the theory of the method, respectively.

Neural dynamic optimization for control systems.II. Theory.

PubMed

Seong, C Y; Widrow, B

2001-01-01

The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper mainly describes the theory of NDO, while the two other companion papers of this topic explain the background for the development of NDO and demonstrate the method with several applications including control of autonomous vehicles and of a robot arm, respectively.

Research on Production Scheduling System with Bottleneck Based on Multi-agent

NASA Astrophysics Data System (ADS)

Zhenqiang, Bao; Weiye, Wang; Peng, Wang; Pan, Quanke

Aimed at the imbalance problem of resource capacity in Production Scheduling System, this paper uses Production Scheduling System based on multi-agent which has been constructed, and combines the dynamic and autonomous of Agent; the bottleneck problem in the scheduling is solved dynamically. Firstly, this paper uses Bottleneck Resource Agent to find out the bottleneck resource in the production line, analyses the inherent mechanism of bottleneck, and describes the production scheduling process based on bottleneck resource. Bottleneck Decomposition Agent harmonizes the relationship of job's arrival time and transfer time in Bottleneck Resource Agent and Non-Bottleneck Resource Agents, therefore, the dynamic scheduling problem is simplified as the single machine scheduling of each resource which takes part in the scheduling. Finally, the dynamic real-time scheduling problem is effectively solved in Production Scheduling System.

Task-level control for autonomous robots

NASA Technical Reports Server (NTRS)

Simmons, Reid

1994-01-01

Task-level control refers to the integration and coordination of planning, perception, and real-time control to achieve given high-level goals. Autonomous mobile robots need task-level control to effectively achieve complex tasks in uncertain, dynamic environments. This paper describes the Task Control Architecture (TCA), an implemented system that provides commonly needed constructs for task-level control. Facilities provided by TCA include distributed communication, task decomposition and sequencing, resource management, monitoring and exception handling. TCA supports a design methodology in which robot systems are developed incrementally, starting first with deliberative plans that work in nominal situations, and then layering them with reactive behaviors that monitor plan execution and handle exceptions. To further support this approach, design and analysis tools are under development to provide ways of graphically viewing the system and validating its behavior.

Robust adaptive relative position and attitude control for spacecraft autonomous proximity.

PubMed

Sun, Liang; Huo, Wei; Jiao, Zongxia

2016-07-01

This paper provides new results of the dynamical modeling and controller designing for autonomous close proximity phase during rendezvous and docking in the presence of kinematic couplings and model uncertainties. A globally defined relative motion mechanical model for close proximity operations is introduced firstly. Then, in spite of the kinematic couplings and thrust misalignment between relative rotation and relative translation, robust adaptive relative position and relative attitude controllers are designed successively. Finally, stability of the overall system is proved that the relative position and relative attitude are uniformly ultimately bounded, and the size of the ultimate bound can be regulated small enough by control system parameters. Performance of the controlled overall system is demonstrated via a representative numerical example. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Translational neurocardiology: preclinical models and cardioneural integrative aspects

PubMed Central

Andresen, M. C.; Armour, J. A.; Billman, G. E.; Chen, P.‐S.; Foreman, R. D.; Herring, N.; O'Leary, D. S.; Sabbah, H. N.; Schultz, H. D.; Sunagawa, K.; Zucker, I. H.

2016-01-01

Abstract Neuronal elements distributed throughout the cardiac nervous system, from the level of the insular cortex to the intrinsic cardiac nervous system, are in constant communication with one another to ensure that cardiac output matches the dynamic process of regional blood flow demand. Neural elements in their various ‘levels’ become differentially recruited in the transduction of sensory inputs arising from the heart, major vessels, other visceral organs and somatic structures to optimize neuronal coordination of regional cardiac function. This White Paper will review the relevant aspects of the structural and functional organization for autonomic control of the heart in normal conditions, how these systems remodel/adapt during cardiac disease, and finally how such knowledge can be leveraged in the evolving realm of autonomic regulation therapy for cardiac therapeutics. PMID:27098459

Multifractal Analysis of Human Heartbeat in Sleep

NASA Astrophysics Data System (ADS)

Ding, Liang-Jing; Peng, Hu; Cai, Shi-Min; Zhou, Pei-Ling

2007-07-01

We study the dynamical properties of heart rate variability (HRV) in sleep by analysing the scaling behaviour with the multifractal detrended fluctuation analysis method. It is well known that heart rate is regulated by the interaction of two branches of the autonomic nervous system: the parasympathetic and sympathetic nervous systems. By investigating the multifractal properties of light, deep, rapid-eye-movement (REM) sleep and wake stages, we firstly find an increasing multifractal behaviour during REM sleep which may be caused by augmented sympathetic activities relative to non-REM sleep. In addition, the investigation of long-range correlations of HRV in sleep with second order detrended fluctuation analysis presents irregular phenomena. These findings may be helpful to understand the underlying regulating mechanism of heart rate by autonomic nervous system during wake-sleep transitions.

A new transiently chaotic flow with ellipsoid equilibria

NASA Astrophysics Data System (ADS)

Panahi, Shirin; Aram, Zainab; Jafari, Sajad; Pham, Viet-Thanh; Volos, Christos; Rajagopal, Karthikeyan

2018-03-01

In this article, a simple autonomous transiently chaotic flow with cubic nonlinearities is proposed. This system represents some unusual features such as having a surface of equilibria. We shall describe some dynamical properties and behaviours of this system in terms of eigenvalue structures, bifurcation diagrams, time series, and phase portraits. Various behaviours of this system such as periodic and transiently chaotic dynamics can be shown by setting special parameters in proper values. Our system belongs to a newly introduced category of transiently chaotic systems: systems with hidden attractors. Transiently chaotic behaviour of our proposed system has been implemented and tested by the OrCAD-PSpise software. We have found a proper qualitative similarity between circuit and simulation results.

Real time health monitoring and control system methodology for flexible space structures

NASA Astrophysics Data System (ADS)

Jayaram, Sanjay

This dissertation is concerned with the Near Real-time Autonomous Health Monitoring of Flexible Space Structures. The dynamics of multi-body flexible systems is uncertain due to factors such as high non-linearity, consideration of higher modal frequencies, high dimensionality, multiple inputs and outputs, operational constraints, as well as unexpected failures of sensors and/or actuators. Hence a systematic framework of developing a high fidelity, dynamic model of a flexible structural system needs to be understood. The fault detection mechanism that will be an integrated part of an autonomous health monitoring system comprises the detection of abnormalities in the sensors and/or actuators and correcting these detected faults (if possible). Applying the robust control law and the robust measures that are capable of detecting and recovering/replacing the actuators rectifies the actuator faults. The fault tolerant concept applied to the sensors will be in the form of an Extended Kalman Filter (EKF). The EKF is going to weigh the information coming from multiple sensors (redundant sensors used to measure the same information) and automatically identify the faulty sensors and weigh the best estimate from the remaining sensors. The mechanization is comprised of instrumenting flexible deployable panels (solar array) with multiple angular position and rate sensors connected to the data acquisition system. The sensors will give position and rate information of the solar panel in all three axes (i.e. roll, pitch and yaw). The position data corresponds to the steady state response and the rate data will give better insight on the transient response of the system. This is a critical factor for real-time autonomous health monitoring. MATLAB (and/or C++) software will be used for high fidelity modeling and fault tolerant mechanism.

The Role of Trust in Information Science and Technology.

ERIC Educational Resources Information Center

Marsh, Stephen; Dibben, Mark R.

2003-01-01

Discusses the notion of trust as it relates to information science and technology, specifically user interfaces, autonomous agents, and information systems. Highlights include theoretical meaning of trust; trust and levels of analysis, including organizational trust; electronic commerce, user interfaces, and static trust; dynamic trust; and trust…

Using the centre of percussion to design a steering controller for an autonomous race car

NASA Astrophysics Data System (ADS)

Kritayakirana, Krisada; Gerdes, J. Christian

2012-01-01

Understanding how a race car driver controls a vehicle at its friction limits can provide insights into the development of vehicle safety systems. In this paper, a race car driver's behaviour inspires the design of an autonomous racing controller. The resulting controller uses the vehicle's centre of percussion (COP) to design feedforward and feedback steering. At the COP, the effects of rotation and translation from the rear tire force cancel each other out; consequently, the feedforward steering command is robust to the disturbances from the rear tire force. Using the COP also simplifies the equations of motion, as the vehicle's lateral motion is decoupled from the vehicle's yaw motion and highlights the challenge of controlling a vehicle when the rear tires are highly saturated. The resulting dynamics can be controlled with a linear state feedback based on a lane-keeping system with additional yaw damping. Utilising Lyapunov theory, the closed-loop system is shown to remain stable even when the rear tires are highly saturated. The experimental results demonstrate that an autonomous vehicle can operate at its limits while maintaining a minimal lateral error.

Gaussian Processes for Data-Efficient Learning in Robotics and Control.

PubMed

Deisenroth, Marc Peter; Fox, Dieter; Rasmussen, Carl Edward

2015-02-01

Autonomous learning has been a promising direction in control and robotics for more than a decade since data-driven learning allows to reduce the amount of engineering knowledge, which is otherwise required. However, autonomous reinforcement learning (RL) approaches typically require many interactions with the system to learn controllers, which is a practical limitation in real systems, such as robots, where many interactions can be impractical and time consuming. To address this problem, current learning approaches typically require task-specific knowledge in form of expert demonstrations, realistic simulators, pre-shaped policies, or specific knowledge about the underlying dynamics. In this paper, we follow a different approach and speed up learning by extracting more information from data. In particular, we learn a probabilistic, non-parametric Gaussian process transition model of the system. By explicitly incorporating model uncertainty into long-term planning and controller learning our approach reduces the effects of model errors, a key problem in model-based learning. Compared to state-of-the art RL our model-based policy search method achieves an unprecedented speed of learning. We demonstrate its applicability to autonomous learning in real robot and control tasks.

An in-silico walker

NASA Astrophysics Data System (ADS)

Xiao, Qiran; Chen, Yanping; Bereau, Tristan; Shi, Yunfeng

2016-08-01

The paradox of biomimetic research is to perform bio-functionality, usually associated with sophisticated structures optimized by nature, with minimal structural complexity for the ease of fabrication. Here we show that a three-particle trimer can exhibit kinesin-like autonomous walk on a track via reactive molecular dynamics simulations. The autonomous motion is due to imbalanced transitions resulting from exothermic catalytic reactions, and the spatial asymmetry from the track. This molecular design can be realized by reproducing the particle-particle interactions in functionalized nano- or colloidal particles. Our results open up the possibility of fabricating bio-mimetic nano-systems in a minimalist approach.

A Symbolic and Graphical Computer Representation of Dynamical Systems

NASA Astrophysics Data System (ADS)

Gould, Laurence I.

2005-04-01

AUTONO is a Macsyma/Maxima program, designed at the University of Hartford, for solving autonomous systems of differential equations as well as for relating Lagrangians and Hamiltonians to their associated dynamical equations. AUTONO can be used in a number of fields to decipher a variety of complex dynamical systems with ease, producing their Lagrangian and Hamiltonian equations in seconds. These equations can then be incorporated into VisSim, a modeling and simulation program, which yields graphical representations of motion in a given system through easily chosen input parameters. The program, along with the VisSim differential-equations graphical package, allows for resolution and easy understanding of complex problems in a relatively short time; thus enabling quicker and more advanced computing of dynamical systems on any number of platforms---from a network of sensors on a space probe, to the behavior of neural networks, to the effects of an electromagnetic field on components in a dynamical system. A flowchart of AUTONO, along with some simple applications and VisSim output, will be shown.

Chaotic Behavior of a Generalized Sprott E Differential System

NASA Astrophysics Data System (ADS)

Oliveira, Regilene; Valls, Claudia

A chaotic system with only one equilibrium, a stable node-focus, was introduced by Wang and Chen [2012]. This system was found by adding a nonzero constant b to the Sprott E system [Sprott, 1994]. The coexistence of three types of attractors in this autonomous system was also considered by Braga and Mello [2013]. Adding a second parameter to the Sprott E differential system, we get the autonomous system ẋ = ayz + b,ẏ = x2 - y,ż = 1 - 4x, where a,b ∈ ℝ are parameters and a≠0. In this paper, we consider theoretically some global dynamical aspects of this system called here the generalized Sprott E differential system. This polynomial differential system is relevant because it is the first polynomial differential system in ℝ3 with two parameters exhibiting, besides the point attractor and chaotic attractor, coexisting stable limit cycles, demonstrating that this system is truly complicated and interesting. More precisely, we show that for b sufficiently small this system can exhibit two limit cycles emerging from the classical Hopf bifurcation at the equilibrium point p = (1/4, 1/16, 0). We also give a complete description of its dynamics on the Poincaré sphere at infinity by using the Poincaré compactification of a polynomial vector field in ℝ3, and we show that it has no first integrals in the class of Darboux functions.

User's instructions for the Guyton circulatory dynamics model using the Univac 1110 batch and demand processing (with graphic capabilities)

NASA Technical Reports Server (NTRS)

Archer, G. T.

1974-01-01

The model presents a systems analysis of a human circulatory regulation based almost entirely on experimental data and cumulative present knowledge of the many facets of the circulatory system. The model itself consists of eighteen different major systems that enter into circulatory control. These systems are grouped into sixteen distinct subprograms that are melded together to form the total model. The model develops circulatory and fluid regulation in a simultaneous manner. Thus, the effects of hormonal and autonomic control, electrolyte regulation, and excretory dynamics are all important and are all included in the model.

The mathematical model of dynamic stabilization system for autonomous car

NASA Astrophysics Data System (ADS)

Saikin, A. M.; Buznikov, S. E.; Shabanov, N. S.; Elkin, D. S.

2018-02-01

Leading foreign companies and domestic enterprises carry out extensive researches and developments in the field of control systems for autonomous cars and in the field of improving driver assistance systems. The search for technical solutions, as a rule, is based on heuristic methods and does not always lead to satisfactory results. The purpose of this research is to formalize the road safety problem in the terms of modern control theory, to construct the adequate mathematical model for solving it, including the choice of software and hardware environment. For automatic control of the object, it is necessary to solve the problem of dynamic stabilization in the most complete formulation. The solution quality of the problem on a finite time interval is estimated by the value of the quadratic functional. Car speed, turn angle and additional yaw rate (during car drift or skidding) measurements are performed programmatically by the original virtual sensors. The limit speeds at which drift, skidding or rollover begins are calculated programmatically taking into account the friction coefficient identified in motion. The analysis of the results confirms both the adequacy of the mathematical models and the algorithms and the possibility of implementing the system in the minimal technical configuration.

Symmetries and solutions of the non-autonomous von Bertalanffy equation

NASA Astrophysics Data System (ADS)

Edwards, Maureen P.; Anderssen, Robert S.

2015-05-01

For growth in a closed environment, which is indicative of the situation in laboratory experiments, autonomous ODE models do not necessarily capture the dynamics under investigation. The importance and impact of a closed environment arise when the question under examination relates, for example, to the number of the surviving microbes, such as in a study of the spoilage and contamination of food, the gene silencing activity of fungi or the production of a chemical compound by bacteria or fungi. Autonomous ODE models are inappropriate as they assume that only the current size of the population controls the growth-decay dynamics. This is reflected in the fact that, asymptotically, their solutions can only grow or decay monotonically or asymptote. Non-autonomous ODE models are not so constrained. A natural strategy for the choice of non-autonomous ODEs is to take appropriate autonomous ones and change them to be non-autonomous through the introduction of relevant non-autonomous terms. This is the approach in this paper with the focus being the von Bertalanffy equation. Since this equation has independent importance in relation to practical applications in growth modelling, it is natural to explore the deeper relationships between the introduced non-autonomous terms through a symmetry analysis, which is the purpose and goal of the current paper. Infinitesimals are derived which allow particular forms of the non-autonomous von Bertalanffy equation to be transformed into autonomous forms for which some new analytic solutions have been found.

Intelligent Adaptive Systems: Literature Research of Design Guidance for Intelligent Adaptive Automation and Interfaces

DTIC Science & Technology

2007-09-01

behaviour based on past experience of interacting with the operator), and mobile (i.e., can move themselves from one machine to another). Edwards argues that...Sofge, D., Bugajska, M., Adams, W., Perzanowski, D., and Schultz, A. (2003). Agent-based Multimodal Interface for Dynamically Autonomous Mobile Robots...based architecture can provide a natural and scalable approach to implementing a multimodal interface to control mobile robots through dynamic

An autonomous rendezvous and docking system using cruise missile technology

NASA Technical Reports Server (NTRS)

Jones, ED; Nicholson, Bruce

1991-01-01

In November 1990 General Dynamics demonstrated an AR&D system for members of the Strategic Avionics Technology Working Group. This simulation utilized prototype hardware derived from the Cruise Missile and Centaur avionics systems. The object of this proof of concept demonstration was to show that all the accuracy, reliability, and operational requirements established for a spacecraft to dock with Space Station Freedom could be met by the proposed AR&D system.

Autonomous Agents for Dynamic Process Planning in the Flexible Manufacturing System

NASA Astrophysics Data System (ADS)

Nik Nejad, Hossein Tehrani; Sugimura, Nobuhiro; Iwamura, Koji; Tanimizu, Yoshitaka

Rapid changes of market demands and pressures of competition require manufacturers to maintain highly flexible manufacturing systems to cope with a complex manufacturing environment. This paper deals with development of an agent-based architecture of dynamic systems for incremental process planning in the manufacturing systems. In consideration of alternative manufacturing processes and machine tools, the process plans and the schedules of the manufacturing resources are generated incrementally and dynamically. A negotiation protocol is discussed, in this paper, to generate suitable process plans for the target products real-timely and dynamically, based on the alternative manufacturing processes. The alternative manufacturing processes are presented by the process plan networks discussed in the previous paper, and the suitable process plans are searched and generated to cope with both the dynamic changes of the product specifications and the disturbances of the manufacturing resources. We initiatively combine the heuristic search algorithms of the process plan networks with the negotiation protocols, in order to generate suitable process plans in the dynamic manufacturing environment.

Evolving Systems and Adaptive Key Component Control

NASA Technical Reports Server (NTRS)

Frost, Susan A.; Balas, Mark J.

2009-01-01

We propose a new framework called Evolving Systems to describe the self-assembly, or autonomous assembly, of actively controlled dynamical subsystems into an Evolved System with a higher purpose. An introduction to Evolving Systems and exploration of the essential topics of the control and stability properties of Evolving Systems is provided. This chapter defines a framework for Evolving Systems, develops theory and control solutions for fundamental characteristics of Evolving Systems, and provides illustrative examples of Evolving Systems and their control with adaptive key component controllers.

Bifurcation and Nonlinear Oscillations.

DTIC Science & Technology

1980-09-28

Structural stability and bifurcation theory. pp. 549-560 in Dinamical Systems (Ed. MI. Peixoto), Academic Press, 1973. [211 J. Sotomayor, Generic one...Dynamical Systems Brown University ELECTP" 71, Providence, R. I. 02912 1EC 2 4 1980j //C -*)’ Septabe-4., 1980 / -A + This research was supported in...problems are discussed. The first one deals with the characterization of the flow for a periodic planar system which is the perturbation of an autonomous

Brief Report: Development of a Robotic Intervention Platform for Young Children with ASD

ERIC Educational Resources Information Center

Warren, Zachary; Zheng, Zhi; Das, Shuvajit; Young, Eric M.; Swanson, Amy; Weitlauf, Amy; Sarkar, Nilanjan

2015-01-01

Increasingly researchers are attempting to develop robotic technologies for children with autism spectrum disorder (ASD). This pilot study investigated the development and application of a novel robotic system capable of dynamic, adaptive, and autonomous interaction during imitation tasks with embedded real-time performance evaluation and…

Cosmological dynamics with non-minimally coupled scalar field and a constant potential function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hrycyna, Orest; Szydłowski, Marek, E-mail: orest.hrycyna@ncbj.gov.pl, E-mail: marek.szydlowski@uj.edu.pl

2015-11-01

Dynamical systems methods are used to investigate global behaviour of the spatially flat Friedmann-Robertson-Walker cosmological model in gravitational theory with a non-minimally coupled scalar field and a constant potential function. We show that the system can be reduced to an autonomous three-dimensional dynamical system and additionally is equipped with an invariant manifold corresponding to an accelerated expansion of the universe. Using this invariant manifold we find an exact solution of the reduced dynamics. We investigate all solutions for all admissible initial conditions using theory of dynamical systems to obtain a classification of all evolutional paths. The right-hand sides of themore » dynamical system depend crucially on the value of the non-minimal coupling constant therefore we study bifurcation values of this parameter under which the structure of the phase space changes qualitatively. We found a special bifurcation value of the non-minimal coupling constant which is distinguished by dynamics of the model and may suggest some additional symmetry in matter sector of the theory.« less

Enzyme-free nucleic acid dynamical systems.

PubMed

Srinivas, Niranjan; Parkin, James; Seelig, Georg; Winfree, Erik; Soloveichik, David

2017-12-15

Chemistries exhibiting complex dynamics-from inorganic oscillators to gene regulatory networks-have been long known but either cannot be reprogrammed at will or rely on the sophisticated enzyme chemistry underlying the central dogma. Can simpler molecular mechanisms, designed from scratch, exhibit the same range of behaviors? Abstract chemical reaction networks have been proposed as a programming language for complex dynamics, along with their systematic implementation using short synthetic DNA molecules. We developed this technology for dynamical systems by identifying critical design principles and codifying them into a compiler automating the design process. Using this approach, we built an oscillator containing only DNA components, establishing that Watson-Crick base-pairing interactions alone suffice for complex chemical dynamics and that autonomous molecular systems can be designed via molecular programming languages. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Overview of the Autonomic Nervous System

MedlinePlus

... be reversible or progressive. Anatomy of the autonomic nervous system The autonomic nervous system is the part of ... organs they connect with. Function of the autonomic nervous system The autonomic nervous system controls internal body processes ...

Even parasites have parasites: oscillatory population dynamics of mobile genetic elements in your genome

NASA Astrophysics Data System (ADS)

Xue, Chi; Goldenfeld, Nigel

Transposable elements (TEs), or transposons, are a class of mobile genetic elements that can either move or duplicate themselves in the genome, sometimes interfering with gene expression as a result. Some TEs can code all necessary enzymes for their transposition and are thus autonomous, while non-autonomous TEs are parasitic and must depend on the machinery of autonomous ones. I present and solve a stochastic model to describe the dynamics of non-autonomous/autonomous pairs of retrotransposons in the human genome that proliferate by a copy-and-paste mechanism. We predict noise-induced persistent oscillations in their copy numbers, analogous to predator-prey dynamics in an ecosystem. We discuss if it is experimentally feasible to measure these phenomena in the laboratory and to observe them over evolutionary time through bioinformatics. This work shows that it is fruitful to regard the genome as an ecosystem that is host to diverse interacting populations. This work was partially supported by the National Science Foundation through Grant No. PHY-1430124, and by the National Aeronautics and Space Administration Astrobiology Institute (NAI) under Cooperative Agreement No. NNA13AA91A.

Proceedings of the 1989 CESAR/CEA (Center for Engineering Systems Advanced Research/Commissariat a l'Energie Atomique) workshop on autonomous mobile robots (May 30--June 1, 1989)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harber, K.S.; Pin, F.G.

1990-03-01

The US DOE Center for Engineering Systems Advanced Research (CESAR) at the Oak Ridge National Laboratory (ORNL) and the Commissariat a l'Energie Atomique's (CEA) Office de Robotique et Productique within the Directorat a la Valorization are working toward a long-term cooperative agreement and relationship in the area of Intelligent Systems Research (ISR). This report presents the proceedings of the first CESAR/CEA Workshop on Autonomous Mobile Robots which took place at ORNL on May 30, 31 and June 1, 1989. The purpose of the workshop was to present and discuss methodologies and algorithms under development at the two facilities in themore » area of perception and navigation for autonomous mobile robots in unstructured environments. Experimental demonstration of the algorithms and comparison of some of their features were proposed to take place within the framework of a previously mutually agreed-upon demonstration scenario or base-case.'' The base-case scenario described in detail in Appendix A, involved autonomous navigation by the robot in an a priori unknown environment with dynamic obstacles, in order to reach a predetermined goal. From the intermediate goal location, the robot had to search for and locate a control panel, move toward it, and dock in front of the panel face. The CESAR demonstration was successfully accomplished using the HERMIES-IIB robot while subsets of the CEA demonstration performed using the ARES robot simulation and animation system were presented. The first session of the workshop focused on these experimental demonstrations and on the needs and considerations for establishing benchmarks'' for testing autonomous robot control algorithms.« less

Dynamical system analysis for DBI dark energy interacting with dark matter

NASA Astrophysics Data System (ADS)

Mahata, Nilanjana; Chakraborty, Subenoy

2015-01-01

A dynamical system analysis related to Dirac-Born-Infeld (DBI) cosmological model has been investigated in this present work. For spatially flat FRW spacetime, the Einstein field equation for DBI scenario has been used to study the dynamics of DBI dark energy interacting with dark matter. The DBI dark energy model is considered as a scalar field with a nonstandard kinetic energy term. An interaction between the DBI dark energy and dark matter is considered through a phenomenological interaction between DBI scalar field and the dark matter fluid. The field equations are reduced to an autonomous dynamical system by a suitable redefinition of the basic variables. The potential of the DBI scalar field is assumed to be exponential. Finally, critical points are determined, their nature have been analyzed and corresponding cosmological scenario has been discussed.

First Results from a Hardware-in-the-Loop Demonstration of Closed-Loop Autonomous Formation Flying

NASA Technical Reports Server (NTRS)

Gill, E.; Naasz, Bo; Ebinuma, T.

2003-01-01

A closed-loop system for the demonstration of autonomous satellite formation flying technologies using hardware-in-the-loop has been developed. Making use of a GPS signal simulator with a dual radio frequency outlet, the system includes two GPS space receivers as well as a powerful onboard navigation processor dedicated to the GPS-based guidance, navigation, and control of a satellite formation in real-time. The closed-loop system allows realistic simulations of autonomous formation flying scenarios, enabling research in the fields of tracking and orbit control strategies for a wide range of applications. The autonomous closed-loop formation acquisition and keeping strategy is based on Lyapunov's direct control method as applied to the standard set of Keplerian elements. This approach not only assures global and asymptotic stability of the control but also maintains valuable physical insight into the applied control vectors. Furthermore, the approach can account for system uncertainties and effectively avoids a computationally expensive solution of the two point boundary problem, which renders the concept particularly attractive for implementation in onboard processors. A guidance law has been developed which strictly separates the relative from the absolute motion, thus avoiding the numerical integration of a target trajectory in the onboard processor. Moreover, upon using precise kinematic relative GPS solutions, a dynamical modeling or filtering is avoided which provides for an efficient implementation of the process on an onboard processor. A sample formation flying scenario has been created aiming at the autonomous transition of a Low Earth Orbit satellite formation from an initial along-track separation of 800 m to a target distance of 100 m. Assuming a low-thrust actuator which may be accommodated on a small satellite, a typical control accuracy of less than 5 m has been achieved which proves the applicability of autonomous formation flying techniques to formations of satellites as close as 50 m.

Autonomous selection of PDE inpainting techniques vs. exemplar inpainting techniques for void fill of high resolution digital surface models

NASA Astrophysics Data System (ADS)

Rahmes, Mark; Yates, J. Harlan; Allen, Josef DeVaughn; Kelley, Patrick

2007-04-01

High resolution Digital Surface Models (DSMs) may contain voids (missing data) due to the data collection process used to obtain the DSM, inclement weather conditions, low returns, system errors/malfunctions for various collection platforms, and other factors. DSM voids are also created during bare earth processing where culture and vegetation features have been extracted. The Harris LiteSite TM Toolkit handles these void regions in DSMs via two novel techniques. We use both partial differential equations (PDEs) and exemplar based inpainting techniques to accurately fill voids. The PDE technique has its origin in fluid dynamics and heat equations (a particular subset of partial differential equations). The exemplar technique has its origin in texture analysis and image processing. Each technique is optimally suited for different input conditions. The PDE technique works better where the area to be void filled does not have disproportionately high frequency data in the neighborhood of the boundary of the void. Conversely, the exemplar based technique is better suited for high frequency areas. Both are autonomous with respect to detecting and repairing void regions. We describe a cohesive autonomous solution that dynamically selects the best technique as each void is being repaired.

Autonomous docking ground demonstration

NASA Technical Reports Server (NTRS)

Lamkin, Steve L.; Le, Thomas Quan; Othon, L. T.; Prather, Joseph L.; Eick, Richard E.; Baxter, Jim M.; Boyd, M. G.; Clark, Fred D.; Spehar, Peter T.; Teters, Rebecca T.

1991-01-01

The Autonomous Docking Ground Demonstration is an evaluation of the laser sensor system to support the docking phase (12 ft to contact) when operated in conjunction with the guidance, navigation, and control (GN&C) software. The docking mechanism being used was developed for the Apollo/Soyuz Test Program. This demonstration will be conducted using the 6-DOF Dynamic Test System (DTS). The DTS simulates the Space Station Freedom as the stationary or target vehicle and the Orbiter as the active or chase vehicle. For this demonstration, the laser sensor will be mounted on the target vehicle and the retroflectors will be on the chase vehicle. This arrangement was chosen to prevent potential damage to the laser. The laser sensor system, GN&C, and 6-DOF DTS will be operated closed-loop. Initial conditions to simulate vehicle misalignments, translational and rotational, will be introduced within the constraints of the systems involved.

Chemical roots of biological evolution: the origins of life as a process of development of autonomous functional systems

PubMed Central

Ruiz-Mirazo, Kepa; Briones, Carlos

2017-01-01

In recent years, an extension of the Darwinian framework is being considered for the study of prebiotic chemical evolution, shifting the attention from homogeneous populations of naked molecular species to populations of heterogeneous, compartmentalized and functionally integrated assemblies of molecules. Several implications of this shift of perspective are analysed in this critical review, both in terms of the individual units, which require an adequate characterization as self-maintaining systems with an internal organization, and also in relation to their collective and long-term evolutionary dynamics, based on competition, collaboration and selection processes among those complex individuals. On these lines, a concrete proposal for the set of molecular control mechanisms that must be coupled to bring about autonomous functional systems, at the interface between chemistry and biology, is provided. PMID:28446711

Chemical roots of biological evolution: the origins of life as a process of development of autonomous functional systems.

PubMed

Ruiz-Mirazo, Kepa; Briones, Carlos; de la Escosura, Andrés

2017-04-01

In recent years, an extension of the Darwinian framework is being considered for the study of prebiotic chemical evolution, shifting the attention from homogeneous populations of naked molecular species to populations of heterogeneous, compartmentalized and functionally integrated assemblies of molecules. Several implications of this shift of perspective are analysed in this critical review, both in terms of the individual units, which require an adequate characterization as self-maintaining systems with an internal organization, and also in relation to their collective and long-term evolutionary dynamics, based on competition, collaboration and selection processes among those complex individuals. On these lines, a concrete proposal for the set of molecular control mechanisms that must be coupled to bring about autonomous functional systems, at the interface between chemistry and biology, is provided. © 2017 The Authors.

Translational neurocardiology: preclinical models and cardioneural integrative aspects.

PubMed

Ardell, J L; Andresen, M C; Armour, J A; Billman, G E; Chen, P-S; Foreman, R D; Herring, N; O'Leary, D S; Sabbah, H N; Schultz, H D; Sunagawa, K; Zucker, I H

2016-07-15

Neuronal elements distributed throughout the cardiac nervous system, from the level of the insular cortex to the intrinsic cardiac nervous system, are in constant communication with one another to ensure that cardiac output matches the dynamic process of regional blood flow demand. Neural elements in their various 'levels' become differentially recruited in the transduction of sensory inputs arising from the heart, major vessels, other visceral organs and somatic structures to optimize neuronal coordination of regional cardiac function. This White Paper will review the relevant aspects of the structural and functional organization for autonomic control of the heart in normal conditions, how these systems remodel/adapt during cardiac disease, and finally how such knowledge can be leveraged in the evolving realm of autonomic regulation therapy for cardiac therapeutics. © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.

Autonomous Navigation of the SSTI/Lewis Spacecraft Using the Global Positioning System (GPS)

NASA Technical Reports Server (NTRS)

Hart, R. C.; Long, A. C.; Lee, T.

1997-01-01

The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) Flight Dynamics Division (FDD) is pursuing the application of Global Positioning System (GPS) technology to improve the accuracy and economy of spacecraft navigation. High-accuracy autonomous navigation algorithms are being flight qualified in conjunction with GSFC's GPS Attitude Determination Flyer (GADFLY) experiment on the Small Satellite Technology Initiative (SSTI) Lewis spacecraft, which is scheduled for launch in 1997. Preflight performance assessments indicate that these algorithms can provide a real-time total position accuracy of better than 10 meters (1 sigma) and velocity accuracy of better than 0.01 meter per second (1 sigma), with selective availability at typical levels. This accuracy is projected to improve to the 2-meter level if corrections to be provided by the GPS Wide Area Augmentation System (WAAS) are included.

Dynamical Integration of Language and Behavior in a Recurrent Neural Network for Human-Robot Interaction.

PubMed

Yamada, Tatsuro; Murata, Shingo; Arie, Hiroaki; Ogata, Tetsuya

2016-01-01

To work cooperatively with humans by using language, robots must not only acquire a mapping between language and their behavior but also autonomously utilize the mapping in appropriate contexts of interactive tasks online. To this end, we propose a novel learning method linking language to robot behavior by means of a recurrent neural network. In this method, the network learns from correct examples of the imposed task that are given not as explicitly separated sets of language and behavior but as sequential data constructed from the actual temporal flow of the task. By doing this, the internal dynamics of the network models both language-behavior relationships and the temporal patterns of interaction. Here, "internal dynamics" refers to the time development of the system defined on the fixed-dimensional space of the internal states of the context layer. Thus, in the execution phase, by constantly representing where in the interaction context it is as its current state, the network autonomously switches between recognition and generation phases without any explicit signs and utilizes the acquired mapping in appropriate contexts. To evaluate our method, we conducted an experiment in which a robot generates appropriate behavior responding to a human's linguistic instruction. After learning, the network actually formed the attractor structure representing both language-behavior relationships and the task's temporal pattern in its internal dynamics. In the dynamics, language-behavior mapping was achieved by the branching structure. Repetition of human's instruction and robot's behavioral response was represented as the cyclic structure, and besides, waiting to a subsequent instruction was represented as the fixed-point attractor. Thanks to this structure, the robot was able to interact online with a human concerning the given task by autonomously switching phases.

Agent autonomy approach to probabilistic physics-of-failure modeling of complex dynamic systems with interacting failure mechanisms

NASA Astrophysics Data System (ADS)

Gromek, Katherine Emily

A novel computational and inference framework of the physics-of-failure (PoF) reliability modeling for complex dynamic systems has been established in this research. The PoF-based reliability models are used to perform a real time simulation of system failure processes, so that the system level reliability modeling would constitute inferences from checking the status of component level reliability at any given time. The "agent autonomy" concept is applied as a solution method for the system-level probabilistic PoF-based (i.e. PPoF-based) modeling. This concept originated from artificial intelligence (AI) as a leading intelligent computational inference in modeling of multi agents systems (MAS). The concept of agent autonomy in the context of reliability modeling was first proposed by M. Azarkhail [1], where a fundamentally new idea of system representation by autonomous intelligent agents for the purpose of reliability modeling was introduced. Contribution of the current work lies in the further development of the agent anatomy concept, particularly the refined agent classification within the scope of the PoF-based system reliability modeling, new approaches to the learning and the autonomy properties of the intelligent agents, and modeling interacting failure mechanisms within the dynamic engineering system. The autonomous property of intelligent agents is defined as agent's ability to self-activate, deactivate or completely redefine their role in the analysis. This property of agents and the ability to model interacting failure mechanisms of the system elements makes the agent autonomy fundamentally different from all existing methods of probabilistic PoF-based reliability modeling. 1. Azarkhail, M., "Agent Autonomy Approach to Physics-Based Reliability Modeling of Structures and Mechanical Systems", PhD thesis, University of Maryland, College Park, 2007.

Stability enhancement of high Prandtl number chaotic convection in an anisotropic porous layer with feedback control

NASA Astrophysics Data System (ADS)

Mahmud, M. N.

2018-04-01

The chaotic dynamical behaviour of thermal convection in an anisotropic porous layer subject to gravity, heated from below and cooled from above, is studied based on theory of dynamical system in the presence of feedback control. The extended Darcy model, which includes the time derivative has been employed in the momentum equation to derive a low dimensional Lorenz-like equation by using Galerkin-truncated approximation. The classical fourth-order Runge-Kutta method is used to obtain the numerical solution in order to exemplify the dynamics of the nonlinear autonomous system. The results show that stability enhancement of chaotic convection is feasible via feedback control.

Autonomous Dynamically Self-Organizing and Self-Healing Distributed Hardware Architecture - the eDNA Concept

NASA Technical Reports Server (NTRS)

Boesen, Michael Reibel; Madsen, Jan; Keymeulen, Didier

2011-01-01

This paper presents the current state of the autonomous dynamically self-organizing and self-healing electronic DNA (eDNA) hardware architecture (patent pending). In its current prototype state, the eDNA architecture is capable of responding to multiple injected faults by autonomously reconfiguring itself to accommodate the fault and keep the application running. This paper will also disclose advanced features currently available in the simulation model only. These features are future work and will soon be implemented in hardware. Finally we will describe step-by-step how an application is implemented on the eDNA architecture.

UAV Swarm Mission Planning Development Using Evolutionary Algorithms - Part I

DTIC Science & Technology

2008-05-01

desired behaviors in autonomous vehicles is a difficult problem at best and in general prob- ably impossible to completely resolve in complex dynamic...associated behaviors. Various techniques inspired by biological self-organized systems as found in forging insects and flocking birds, revolve around...swarms of heterogeneous vehicles in a distributed simulation system with animated graphics. Statistical measurements and observations indicate that bio

X-38 Application of Dynamic Inversion Flight Control

NASA Technical Reports Server (NTRS)

Wacker, Roger; Munday, Steve; Merkle, Scott

2001-01-01

This paper summarizes the application of a nonlinear dynamic inversion (DI) flight control system (FCS) to an autonomous flight test vehicle in NASA's X-38 Project, a predecessor to the International Space Station (ISS) Crew Return Vehicle (CRV). Honeywell's Multi-Application Control-H (MACH) is a parameterized FCS design architecture including both model-based DI rate-compensation and classical P+I command-tracking. MACH was adopted by X-38 in order to shorten the design cycle time for different vehicle shapes and flight envelopes and evolving aerodynamic databases. Specific design issues and analysis results are presented for the application of MACH to the 3rd free flight (FF3) of X-38 Vehicle 132 (V132). This B-52 drop test, occurring on March 30, 2000, represents the first flight test of MACH and one of the first few known applications of DI in the primary FCS of an autonomous flight test vehicle.

Video Guidance, Landing, and Imaging system (VGLIS) for space missions

NASA Technical Reports Server (NTRS)

Schappell, R. T.; Knickerbocker, R. L.; Tietz, J. C.; Grant, C.; Flemming, J. C.

1975-01-01

The feasibility of an autonomous video guidance system that is capable of observing a planetary surface during terminal descent and selecting the most acceptable landing site was demonstrated. The system was breadboarded and "flown" on a physical simulator consisting of a control panel and monitor, a dynamic simulator, and a PDP-9 computer. The breadboard VGLIS consisted of an image dissector camera and the appropriate processing logic. Results are reported.

Static and Dynamic Autonomic Response with Increasing Nausea Perception

PubMed Central

LaCount, Lauren T; Barbieri, Riccardo; Park, Kyungmo; Kim, Jieun; Brown, Emery N; Kuo, Braden; Napadow, Vitaly

2011-01-01

Background Nausea is a commonly occurring symptom typified by epigastric discomfort with urge to vomit. The relationship between autonomic nervous system (ANS) outflow and increasing nausea perception is not fully understood. Methods Our study employed a nauseogenic visual stimulus (horizontally translating stripes) while 17 female subjects freely rated transitions in nausea level and autonomic outflow was measured (heart rate, HR, heart rate variability, HRV, skin conductance response, SCR, respiratory rate). We also adopted a recent approach to continuous high frequency (HF) HRV estimation to evaluate dynamic cardiovagal modulation. Results HR increased from baseline for all increasing nausea transitions, especially transition to strong nausea (15.0±11.4 bpm), but decreased (−6.6±4.6 bpm) once the visual stimulus ceased. SCR also increased for all increasing nausea transitions, especially transition to strong nausea (1.76±1.68 μS), but continued to increase (0.52 ± 0.65 μS) once visual stimulation ceased. LF/HF HRV increased following transition to moderate (1.54±2.11 a.u.) and strong (2.57±3.49 a.u.) nausea, suggesting a sympathetic shift in sympathovagal balance. However, dynamic HF HRV suggested that bursts of cardiovagal modulation precede transitions to higher nausea, perhaps influencing subjects to rate higher levels of nausea. No significant change in respiration rate was found. Conclusions Our results suggest that increasing nausea perception is associated with both increased sympathetic and decreased parasympathetic ANS modulation. These findings corroborate past ANS studies of nausea, applying percept-linked analyses and dynamic estimation of cardiovagal modulation in response to nausea. PMID:21485400

Clustering Heart Rate Dynamics Is Associated with β-Adrenergic Receptor Polymorphisms: Analysis by Information-Based Similarity Index

PubMed Central

Yang, Albert C.; Tsai, Shih-Jen; Hong, Chen-Jee; Wang, Cynthia; Chen, Tai-Jui; Liou, Ying-Jay; Peng, Chung-Kang

2011-01-01

Background Genetic polymorphisms in the gene encoding the β-adrenergic receptors (β-AR) have a pivotal role in the functions of the autonomic nervous system. Using heart rate variability (HRV) as an indicator of autonomic function, we present a bottom-up genotype–phenotype analysis to investigate the association between β-AR gene polymorphisms and heart rate dynamics. Methods A total of 221 healthy Han Chinese adults (59 males and 162 females, aged 33.6±10.8 years, range 19 to 63 years) were recruited and genotyped for three common β-AR polymorphisms: β1-AR Ser49Gly, β2-AR Arg16Gly and β2-AR Gln27Glu. Each subject underwent two hours of electrocardiogram monitoring at rest. We applied an information-based similarity (IBS) index to measure the pairwise dissimilarity of heart rate dynamics among study subjects. Results With the aid of agglomerative hierarchical cluster analysis, we categorized subjects into major clusters, which were found to have significantly different distributions of β2-AR Arg16Gly genotype. Furthermore, the non-randomness index, a nonlinear HRV measure derived from the IBS method, was significantly lower in Arg16 homozygotes than in Gly16 carriers. The non-randomness index was negatively correlated with parasympathetic-related HRV variables and positively correlated with those HRV indices reflecting a sympathovagal shift toward sympathetic activity. Conclusions We demonstrate a bottom-up categorization approach combining the IBS method and hierarchical cluster analysis to detect subgroups of subjects with HRV phenotypes associated with β-AR polymorphisms. Our results provide evidence that β2-AR polymorphisms are significantly associated with the acceleration/deceleration pattern of heart rate oscillation, reflecting the underlying mode of autonomic nervous system control. PMID:21573230

An ambulatory recording system for the assessment of autonomic changes across multiple days

NASA Astrophysics Data System (ADS)

Sollers, John J., III; Yonezawa, Yoshiharu; Silver, Rebecca A.; Merritt, Marcellus M.; Thayer, Julian F.

2005-05-01

Recent evidence indicates that poor autonomic regulation, indexed by decreased heart period variability (HPV), is associated with decreased working memory. HPV analyses are computed on the interbeat interval time series derived from the electrocardiogram (EKG). Unfortunately, the duration of the data collection and the issue of the size of ambulatory monitors with sufficient storage capacity for multi-day records is somewhat problematic. In the present paper we describe a system that allows for the collection of large amounts of high quality data using a small data collection device. The recording system consists of a miniature, single-module electrocardiogram-recording device. This module consists of an integrated three-electrode device that is attached to the chest of the subject. A low power 8-bit micro-controller detects the R-spike and stores the time between R-spikes in milliseconds on a 512 KB EEPROM. This system can record continuously for over four days. This system will allow the recording of cardio-dynamics in the field and provide highly reliable data across multiple days. The use of this device to assess physiological function in military operations would allow researchers to examine longer data records across several contexts and to understand the role of changes in autonomic function as they relate to performance.

Dynamic Task Assignment of Autonomous Distributed AGV in an Intelligent FMS Environment

NASA Astrophysics Data System (ADS)

Fauadi, Muhammad Hafidz Fazli Bin Md; Lin, Hao Wen; Murata, Tomohiro

The need of implementing distributed system is growing significantly as it is proven to be effective for organization to be flexible against a highly demanding market. Nevertheless, there are still large technical gaps need to be addressed to gain significant achievement. We propose a distributed architecture to control Automated Guided Vehicle (AGV) operation based on multi-agent architecture. System architectures and agents' functions have been designed to support distributed control of AGV. Furthermore, enhanced agent communication protocol has been configured to accommodate dynamic attributes of AGV task assignment procedure. Result proved that the technique successfully provides a better solution.

Dynamical analysis on f(R, G) cosmology

NASA Astrophysics Data System (ADS)

Santos da Costa, S.; Roig, F. V.; Alcaniz, J. S.; Capozziello, S.; De Laurentis, M.; Benetti, M.

2018-04-01

We use a dynamical system approach to study the cosmological viability of f(R, G) gravity theories. The method consists of formulating the evolution equations as an autonomous system of ordinary differential equations, using suitable variables. The formalism is applied to a class of models in which f(R, G)\\propto RnG1-n and its solutions and corresponding stability are analysed in detail. New accelerating solutions that can be attractors in the phase space are found. We also find that this class of models does not exhibit a matter-dominated epoch, a solution which is inconsistent with current cosmological observations.

Detecting changes in forced climate attractors with Wasserstein distance

NASA Astrophysics Data System (ADS)

Robin, Yoann; Yiou, Pascal; Naveau, Philippe

2017-07-01

The climate system can been described by a dynamical system and its associated attractor. The dynamics of this attractor depends on the external forcings that influence the climate. Such forcings can affect the mean values or variances, but regions of the attractor that are seldom visited can also be affected. It is an important challenge to measure how the climate attractor responds to different forcings. Currently, the Euclidean distance or similar measures like the Mahalanobis distance have been favored to measure discrepancies between two climatic situations. Those distances do not have a natural building mechanism to take into account the attractor dynamics. In this paper, we argue that a Wasserstein distance, stemming from optimal transport theory, offers an efficient and practical way to discriminate between dynamical systems. After treating a toy example, we explore how the Wasserstein distance can be applied and interpreted to detect non-autonomous dynamics from a Lorenz system driven by seasonal cycles and a warming trend.

Opportunistic Behavior in Motivated Learning Agents.

PubMed

Graham, James; Starzyk, Janusz A; Jachyra, Daniel

2015-08-01

This paper focuses on the novel motivated learning (ML) scheme and opportunistic behavior of an intelligent agent. It extends previously developed ML to opportunistic behavior in a multitask situation. Our paper describes the virtual world implementation of autonomous opportunistic agents learning in a dynamically changing environment, creating abstract goals, and taking advantage of arising opportunities to improve their performance. An opportunistic agent achieves better results than an agent based on ML only. It does so by minimizing the average value of all need signals rather than a dominating need. This paper applies to the design of autonomous embodied systems (robots) learning in real-time how to operate in a complex environment.

Psychophysiology of neural, cognitive and affective integration: fMRI and autonomic indicants

PubMed Central

Critchley, Hugo D.

2009-01-01

Behaviour is shaped by environmental challenge in the context of homoeostatic need. Emotional and cognitive processes evoke patterned changes in bodily state that may signal emotional state to others. This dynamic modulation of visceral state is neurally mediated by sympathetic and parasympathetic divisions of the autonomic nervous system. Moreover neural afferents convey representations of the internal state of the body back to the brain to further influence emotion and cognition. Neuroimaging and lesion studies implicate specific regions of limbic forebrain in the behavioural generation of autonomic arousal states. Activity within these regions may predict emotion-specific autonomic response patterns within and between bodily organs, with implications for psychosomatic medicine. Feedback from the viscera is mapped hierarchically in the brain to influence efferent signals, and ultimately at the cortical level to engender and reinforce affective responses and subjective feeling states. Again neuroimaging and patient studies suggest discrete neural substrates for these representations, notably regions of insula and orbitofrontal cortex. Individual differences in conscious access to these interoceptive representations predict differences in emotional experience, but equally the misperception of heightened arousal level may evoke changes in emotional behaviour through engagement of the same neural centres. Perturbation of feedback may impair emotional reactivity and, in the context of inflammatory states give rise to cognitive, affective and psychomotor expressions of illness. Changes in visceral state during emotion may be mirrored in the responses of others, permitting a corresponding representation in the observer. The degree to which individuals are susceptible to this ‘contagion’ predicts individual differences in questionnaire ratings of empathy. Together these neuroimaging and clinical studies highlight the dynamic relationship between mind and body and help identify neural substrates that may translate thoughts into autonomic arousal and bodily states into feelings that can be shared. PMID:19414044

Autonomous Mission Operations for Sensor Webs

NASA Astrophysics Data System (ADS)

Underbrink, A.; Witt, K.; Stanley, J.; Mandl, D.

2008-12-01

We present interim results of a 2005 ROSES AIST project entitled, "Using Intelligent Agents to Form a Sensor Web for Autonomous Mission Operations", or SWAMO. The goal of the SWAMO project is to shift the control of spacecraft missions from a ground-based, centrally controlled architecture to a collaborative, distributed set of intelligent agents. The network of intelligent agents intends to reduce management requirements by utilizing model-based system prediction and autonomic model/agent collaboration. SWAMO agents are distributed throughout the Sensor Web environment, which may include multiple spacecraft, aircraft, ground systems, and ocean systems, as well as manned operations centers. The agents monitor and manage sensor platforms, Earth sensing systems, and Earth sensing models and processes. The SWAMO agents form a Sensor Web of agents via peer-to-peer coordination. Some of the intelligent agents are mobile and able to traverse between on-orbit and ground-based systems. Other agents in the network are responsible for encapsulating system models to perform prediction of future behavior of the modeled subsystems and components to which they are assigned. The software agents use semantic web technologies to enable improved information sharing among the operational entities of the Sensor Web. The semantics include ontological conceptualizations of the Sensor Web environment, plus conceptualizations of the SWAMO agents themselves. By conceptualizations of the agents, we mean knowledge of their state, operational capabilities, current operational capacities, Web Service search and discovery results, agent collaboration rules, etc. The need for ontological conceptualizations over the agents is to enable autonomous and autonomic operations of the Sensor Web. The SWAMO ontology enables automated decision making and responses to the dynamic Sensor Web environment and to end user science requests. The current ontology is compatible with Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) Sensor Model Language (SensorML) concepts and structures. The agents are currently deployed on the U.S. Naval Academy MidSTAR-1 satellite and are actively managing the power subsystem on-orbit without the need for human intervention.

A Spectral Approach for Quenched Limit Theorems for Random Expanding Dynamical Systems

NASA Astrophysics Data System (ADS)

Dragičević, D.; Froyland, G.; González-Tokman, C.; Vaienti, S.

2018-06-01

We prove quenched versions of (i) a large deviations principle (LDP), (ii) a central limit theorem (CLT), and (iii) a local central limit theorem for non-autonomous dynamical systems. A key advance is the extension of the spectral method, commonly used in limit laws for deterministic maps, to the general random setting. We achieve this via multiplicative ergodic theory and the development of a general framework to control the regularity of Lyapunov exponents of twisted transfer operator cocycles with respect to a twist parameter. While some versions of the LDP and CLT have previously been proved with other techniques, the local central limit theorem is, to our knowledge, a completely new result, and one that demonstrates the strength of our method. Applications include non-autonomous (piecewise) expanding maps, defined by random compositions of the form {T_{σ^{n-1} ω} circ\\cdotscirc T_{σω}circ T_ω}. An important aspect of our results is that we only assume ergodicity and invertibility of the random driving {σ:Ω\\toΩ} ; in particular no expansivity or mixing properties are required.

A Spectral Approach for Quenched Limit Theorems for Random Expanding Dynamical Systems

NASA Astrophysics Data System (ADS)

Dragičević, D.; Froyland, G.; González-Tokman, C.; Vaienti, S.

2018-01-01

We prove quenched versions of (i) a large deviations principle (LDP), (ii) a central limit theorem (CLT), and (iii) a local central limit theorem for non-autonomous dynamical systems. A key advance is the extension of the spectral method, commonly used in limit laws for deterministic maps, to the general random setting. We achieve this via multiplicative ergodic theory and the development of a general framework to control the regularity of Lyapunov exponents of twisted transfer operator cocycles with respect to a twist parameter. While some versions of the LDP and CLT have previously been proved with other techniques, the local central limit theorem is, to our knowledge, a completely new result, and one that demonstrates the strength of our method. Applications include non-autonomous (piecewise) expanding maps, defined by random compositions of the form {T_{σ^{n-1} ω} circ\\cdotscirc T_{σω}circ T_ω} . An important aspect of our results is that we only assume ergodicity and invertibility of the random driving {σ:Ω\\toΩ} ; in particular no expansivity or mixing properties are required.

Stochastic climate dynamics: Stochastic parametrizations and their global effects

NASA Astrophysics Data System (ADS)

Ghil, Michael

2010-05-01

A well-known difficulty in modeling the atmosphere and oceans' general circulation is the limited, albeit increasing resolution possible in the numerical solution of the governing partial differential equations. While the mass, energy and momentum of an individual cloud, in the atmosphere, or convection chimney, in the oceans, is negligible, their combined effects over long times are not. Until recently, small, subgrid-scale processes were represented in general circulation models (GCMs) by deterministic "parametrizations." While A. Arakawa and associates had realized over three decades ago the conceptual need for ensembles of clouds in such parametrizations, it is only very recently that truly stochastic parametrizations have been introduced into GCMs and weather prediction models. These parametrizations essentially transform a deterministic autonomous system into a non-autonomous one, subject to random forcing. To study systematically the long-term effects of such a forcing has to rely on theory of random dynamical systems (RDS). This theory allows one to consider the detailed geometric structure of the random attractors associated with nonlinear, stochastically perturbed systems. These attractors extend the concept of strange attractors from autonomous dynamical systems to non-autonomous systems with random forcing. To illustrate the essence of the theory, its concepts and methods, we carry out a high-resolution numerical study of two "toy" models in their respective phase spaces. This study allows one to obtain a good approximation of their global random attractors, as well as of the time-dependent invariant measures supported by these attractors. The first of the two models studied herein is the Arnol'd family of circle maps in the presence of noise. The maps' fine-grained, resonant landscape --- associated with Arnol'd tongues --- is smoothed by the noise, thus permitting a comparison with the observable aspects of the "Devil's staircase" that arises in modeling the El Nino-Southern Oscillation (ENSO). These results are confirmed by studying a "French garden" that is obtained by smoothing a "Devil's quarry." Such a quarry results from coupling two circle maps, and random forcing leads to a smoothed version thereof. We thus suspect that stochastic parametrizations will stabilize the sensitive dependence on parameters that has been noticed in the development of GCMs. This talk represents joint work with Mickael D. Chekroun, D. Kondrashov, Eric Simonnet and I. Zaliapin. Several other talks and posters complement the results presented here and provide further insights into RDS theory and its application to the geosciences.

A multi-harmonic generalized energy balance method for studying autonomous oscillations of nonlinear conservative systems

NASA Astrophysics Data System (ADS)

Balaji, Nidish Narayanaa; Krishna, I. R. Praveen; Padmanabhan, C.

2018-05-01

The Harmonic Balance Method (HBM) is a frequency-domain based approximation approach used for obtaining the steady state periodic behavior of forced dynamical systems. Intrinsically these systems are non-autonomous and the method offers many computational advantages over time-domain methods when the fundamental period of oscillation is known (generally fixed as the forcing period itself or a corresponding sub-harmonic if such behavior is expected). In the current study, a modified approach, based on He's Energy Balance Method (EBM), is applied to obtain the periodic solutions of conservative systems. It is shown that by this approach, periodic solutions of conservative systems on iso-energy manifolds in the phase space can be obtained very efficiently. The energy level provides the additional constraint on the HBM formulation, which enables the determination of the period of the solutions. The method is applied to the linear harmonic oscillator, a couple of nonlinear oscillators, the elastic pendulum and the Henon-Heiles system. The approach is used to trace the bifurcations of the periodic solutions of the last two, being 2 degree-of-freedom systems demonstrating very rich dynamical behavior. In the process, the advantages offered by the current formulation of the energy balance is brought out. A harmonic perturbation approach is used to evaluate the stability of the solutions for the bifurcation diagram.

Dynamic edge warping - An experimental system for recovering disparity maps in weakly constrained systems

NASA Technical Reports Server (NTRS)

Boyer, K. L.; Wuescher, D. M.; Sarkar, S.

1991-01-01

Dynamic edge warping (DEW), a technique for recovering reasonably accurate disparity maps from uncalibrated stereo image pairs, is presented. No precise knowledge of the epipolar camera geometry is assumed. The technique is embedded in a system including structural stereopsis on the front end and robust estimation in digital photogrammetry on the other for the purpose of self-calibrating stereo image pairs. Once the relative camera orientation is known, the epipolar geometry is computed and the system can use this information to refine its representation of the object space. Such a system will find application in the autonomous extraction of terrain maps from stereo aerial photographs, for which camera position and orientation are unknown a priori, and for online autonomous calibration maintenance for robotic vision applications, in which the cameras are subject to vibration and other physical disturbances after calibration. This work thus forms a component of an intelligent system that begins with a pair of images and, having only vague knowledge of the conditions under which they were acquired, produces an accurate, dense, relative depth map. The resulting disparity map can also be used directly in some high-level applications involving qualitative scene analysis, spatial reasoning, and perceptual organization of the object space. The system as a whole substitutes high-level information and constraints for precise geometric knowledge in driving and constraining the early correspondence process.

A linguistic geometry for 3D strategic planning

NASA Technical Reports Server (NTRS)

Stilman, Boris

1995-01-01

This paper is a new step in the development and application of the Linguistic Geometry. This formal theory is intended to discover the inner properties of human expert heuristics, which have been successful in a certain class of complex control systems, and apply them to different systems. In this paper we investigate heuristics extracted in the form of hierarchical networks of planning paths of autonomous agents. Employing Linguistic Geometry tools the dynamic hierarchy of networks is represented as a hierarchy of formal attribute languages. The main ideas of this methodology are shown in this paper on the new pilot example of the solution of the extremely complex 3D optimization problem of strategic planning for the space combat of autonomous vehicles. This example demonstrates deep and highly selective search in comparison with conventional search algorithms.

Collaborating with Autonomous Agents

NASA Technical Reports Server (NTRS)

Trujillo, Anna C.; Cross, Charles D.; Fan, Henry; Hempley, Lucas E.; Motter, Mark A.; Neilan, James H.; Qualls, Garry D.; Rothhaar, Paul M.; Tran, Loc D.; Allen, B. Danette

2015-01-01

With the anticipated increase of small unmanned aircraft systems (sUAS) entering into the National Airspace System, it is highly likely that vehicle operators will be teaming with fleets of small autonomous vehicles. The small vehicles may consist of sUAS, which are 55 pounds or less that typically will y at altitudes 400 feet and below, and small ground vehicles typically operating in buildings or defined small campuses. Typically, the vehicle operators are not concerned with manual control of the vehicle; instead they are concerned with the overall mission. In order for this vision of high-level mission operators working with fleets of vehicles to come to fruition, many human factors related challenges must be investigated and solved. First, the interface between the human operator and the autonomous agent must be at a level that the operator needs and the agents can understand. This paper details the natural language human factors e orts that NASA Langley's Autonomy Incubator is focusing on. In particular these e orts focus on allowing the operator to interact with the system using speech and gestures rather than a mouse and keyboard. With this ability of the system to understand both speech and gestures, operators not familiar with the vehicle dynamics will be able to easily plan, initiate, and change missions using a language familiar to them rather than having to learn and converse in the vehicle's language. This will foster better teaming between the operator and the autonomous agent which will help lower workload, increase situation awareness, and improve performance of the system as a whole.

Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors.

PubMed

Villaverde, Monica; Perez, David; Moreno, Felix

2015-11-17

The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor's infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

Intelligent mobility research for robotic locomotion in complex terrain

NASA Astrophysics Data System (ADS)

Trentini, Michael; Beckman, Blake; Digney, Bruce; Vincent, Isabelle; Ricard, Benoit

2006-05-01

The objective of the Autonomous Intelligent Systems Section of Defence R&D Canada - Suffield is best described by its mission statement, which is "to augment soldiers and combat systems by developing and demonstrating practical, cost effective, autonomous intelligent systems capable of completing military missions in complex operating environments." The mobility requirement for ground-based mobile systems operating in urban settings must increase significantly if robotic technology is to augment human efforts in these roles and environments. The intelligence required for autonomous systems to operate in complex environments demands advances in many fields of robotics. This has resulted in large bodies of research in areas of perception, world representation, and navigation, but the problem of locomotion in complex terrain has largely been ignored. In order to achieve its objective, the Autonomous Intelligent Systems Section is pursuing research that explores the use of intelligent mobility algorithms designed to improve robot mobility. Intelligent mobility uses sensing, control, and learning algorithms to extract measured variables from the world, control vehicle dynamics, and learn by experience. These algorithms seek to exploit available world representations of the environment and the inherent dexterity of the robot to allow the vehicle to interact with its surroundings and produce locomotion in complex terrain. The primary focus of the paper is to present the intelligent mobility research within the framework of the research methodology, plan and direction defined at Defence R&D Canada - Suffield. It discusses the progress and future direction of intelligent mobility research and presents the research tools, topics, and plans to address this critical research gap. This research will create effective intelligence to improve the mobility of ground-based mobile systems operating in urban settings to assist the Canadian Forces in their future urban operations.

Stochastic modeling indicates that aging and somatic evolution in the hematopoetic system are driven by non-cell-autonomous processes.

PubMed

Rozhok, Andrii I; Salstrom, Jennifer L; DeGregori, James

2014-12-01

Age-dependent tissue decline and increased cancer incidence are widely accepted to be rate-limited by the accumulation of somatic mutations over time. Current models of carcinogenesis are dominated by the assumption that oncogenic mutations have defined advantageous fitness effects on recipient stem and progenitor cells, promoting and rate-limiting somatic evolution. However, this assumption is markedly discrepant with evolutionary theory, whereby fitness is a dynamic property of a phenotype imposed upon and widely modulated by environment. We computationally modeled dynamic microenvironment-dependent fitness alterations in hematopoietic stem cells (HSC) within the Sprengel-Liebig system known to govern evolution at the population level. Our model for the first time integrates real data on age-dependent dynamics of HSC division rates, pool size, and accumulation of genetic changes and demonstrates that somatic evolution is not rate-limited by the occurrence of mutations, but instead results from aged microenvironment-driven alterations in the selective/fitness value of previously accumulated genetic changes. Our results are also consistent with evolutionary models of aging and thus oppose both somatic mutation-centric paradigms of carcinogenesis and tissue functional decline. In total, we demonstrate that aging directly promotes HSC fitness decline and somatic evolution via non-cell-autonomous mechanisms.

Local versus global interactions in nonequilibrium transitions: A model of social dynamics

NASA Astrophysics Data System (ADS)

González-Avella, J. C.; Eguíluz, V. M.; Cosenza, M. G.; Klemm, K.; Herrera, J. L.; San Miguel, M.

2006-04-01

A nonequilibrium system of locally interacting elements in a lattice with an absorbing order-disorder phase transition is studied under the effect of additional interacting fields. These fields are shown to produce interesting effects in the collective behavior of this system. Both for autonomous and external fields, disorder grows in the system when the probability of the elements to interact with the field is increased. There exists a threshold value of this probability beyond which the system is always disordered. The domain of parameters of the ordered regime is larger for nonuniform local fields than for spatially uniform fields. However, the zero field limit is discontinous. In the limit of vanishingly small probability of interaction with the field, autonomous or external fields are able to order a system that would fall in a disordered phase under local interactions of the elements alone. We consider different types of fields which are interpreted as forms of mass media acting on a social system in the context of Axelrod’s model for cultural dissemination.

Local versus global interactions in nonequilibrium transitions: A model of social dynamics.

PubMed

González-Avella, J C; Eguíluz, V M; Cosenza, M G; Klemm, K; Herrera, J L; San Miguel, M

2006-04-01

A nonequilibrium system of locally interacting elements in a lattice with an absorbing order-disorder phase transition is studied under the effect of additional interacting fields. These fields are shown to produce interesting effects in the collective behavior of this system. Both for autonomous and external fields, disorder grows in the system when the probability of the elements to interact with the field is increased. There exists a threshold value of this probability beyond which the system is always disordered. The domain of parameters of the ordered regime is larger for nonuniform local fields than for spatially uniform fields. However, the zero field limit is discontinous. In the limit of vanishingly small probability of interaction with the field, autonomous or external fields are able to order a system that would fall in a disordered phase under local interactions of the elements alone. We consider different types of fields which are interpreted as forms of mass media acting on a social system in the context of Axelrod's model for cultural dissemination.

An Autonomous Distributed Fault-Tolerant Local Positioning System

NASA Technical Reports Server (NTRS)

Malekpour, Mahyar R.

2017-01-01

We describe a fault-tolerant, GPS-independent (Global Positioning System) distributed autonomous positioning system for static/mobile objects and present solutions for providing highly-accurate geo-location data for the static/mobile objects in dynamic environments. The reliability and accuracy of a positioning system fundamentally depends on two factors; its timeliness in broadcasting signals and the knowledge of its geometry, i.e., locations and distances of the beacons. Existing distributed positioning systems either synchronize to a common external source like GPS or establish their own time synchrony using a scheme similar to a master-slave by designating a particular beacon as the master and other beacons synchronize to it, resulting in a single point of failure. Another drawback of existing positioning systems is their lack of addressing various fault manifestations, in particular, communication link failures, which, as in wireless networks, are increasingly dominating the process failures and are typically transient and mobile, in the sense that they typically affect different messages to/from different processes over time.

Dynamic multisensor fusion for mobile robot navigation in an indoor environment

NASA Astrophysics Data System (ADS)

Jin, Taeseok; Lee, Jang-Myung; Luk, Bing L.; Tso, Shiu K.

2001-10-01

In this study, as the preliminary step for developing a multi-purpose Autonomous robust carrier mobile robot to transport trolleys or heavy goods and serve as robotic nursing assistant in hospital wards. The aim of this paper is to present the use of multi-sensor data fusion such as sonar, CCD camera dn IR sensor for map-building mobile robot to navigate, and presents an experimental mobile robot designed to operate autonomously within both indoor and outdoor environments. Smart sensory systems are crucial for successful autonomous systems. We will give an explanation for the robot system architecture designed and implemented in this study and a short review of existing techniques, since there exist several recent thorough books and review paper on this paper. Instead we will focus on the main results with relevance to the intelligent service robot project at the Centre of Intelligent Design, Automation & Manufacturing (CIDAM). We will conclude by discussing some possible future extensions of the project. It is first dealt with the general principle of the navigation and guidance architecture, then the detailed functions recognizing environments updated, obstacle detection and motion assessment, with the first results form the simulations run.

Advanced Mobility Testbed for Dynamic Semi-Autonomous Unmanned Ground Vehicles

DTIC Science & Technology

2015-04-24

constraint, effectively hiding them from the dynamics solver. Thus the resulting system topology is once again a tree with only inter-body hinges and...the geometry of wheel sinkage (left) and stress distribution under the wheel (right) from reference [24]. With τmax(θ) = c+σ(θ) tan (φ). the shear...sliding). The transversal deflection α or lateral slip angle and the lateral slip coefficient Sα are Sα = tan (α) = −vy vx (12) The comprehensive slip ratio

Design of a dynamic test platform for autonomous robot vision systems

NASA Technical Reports Server (NTRS)

Rich, G. C.

1980-01-01

The concept and design of a dynamic test platform for development and evluation of a robot vision system is discussed. The platform is to serve as a diagnostic and developmental tool for future work with the RPI Mars Rover's multi laser/multi detector vision system. The platform allows testing of the vision system while its attitude is varied, statically or periodically. The vision system is mounted on the test platform. It can then be subjected to a wide variety of simulated can thus be examined in a controlled, quantitative fashion. Defining and modeling Rover motions and designing the platform to emulate these motions are also discussed. Individual aspects of the design process are treated separately, as structural, driving linkages, and motors and transmissions.

Predictive Multiple Model Switching Control with the Self-Organizing Map

NASA Technical Reports Server (NTRS)

Motter, Mark A.

2000-01-01

A predictive, multiple model control strategy is developed by extension of self-organizing map (SOM) local dynamic modeling of nonlinear autonomous systems to a control framework. Multiple SOMs collectively model the global response of a nonautonomous system to a finite set of representative prototype controls. Each SOM provides a codebook representation of the dynamics corresponding to a prototype control. Different dynamic regimes are organized into topological neighborhoods where the adjacent entries in the codebook represent the global minimization of a similarity metric. The SOM is additionally employed to identify the local dynamical regime, and consequently implements a switching scheme that selects the best available model for the applied control. SOM based linear models are used to predict the response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal.

Biologically inspired dynamic material systems.

PubMed

Studart, André R

2015-03-09

Numerous examples of material systems that dynamically interact with and adapt to the surrounding environment are found in nature, from hair-based mechanoreceptors in animals to self-shaping seed dispersal units in plants to remodeling bone in vertebrates. Inspired by such fascinating biological structures, a wide range of synthetic material systems have been created to replicate the design concepts of dynamic natural architectures. Examples of biological structures and their man-made counterparts are herein revisited to illustrate how dynamic and adaptive responses emerge from the intimate microscale combination of building blocks with intrinsic nanoscale properties. By using top-down photolithographic methods and bottom-up assembly approaches, biologically inspired dynamic material systems have been created 1) to sense liquid flow with hair-inspired microelectromechanical systems, 2) to autonomously change shape by utilizing plantlike heterogeneous architectures, 3) to homeostatically influence the surrounding environment through self-regulating adaptive surfaces, and 4) to spatially concentrate chemical species by using synthetic microcompartments. The ever-increasing complexity and remarkable functionalities of such synthetic systems offer an encouraging perspective to the rich set of dynamic and adaptive properties that can potentially be implemented in future man-made material systems. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Developing a Framework for Control of Agile Aircraft Platforms in Autonomous Hover

DTIC Science & Technology

2009-03-01

profiles. Two dynamical systems are considered, a scale YAK -54 aerobatic remote control aircraft and the Flexrotor concept developed by Aerovel. Both models...System [28]. . . . . . . 2 1.2 A YAK -54 in hover in the Real Flight RC Simulator [24]. . . . . . . . 3 1.3 The Aerovel Flexrotor concept...17 3.1 A three-view of the YAK -54 showing all geometry and dimensions (in mm) [15

Evaluating the Dynamics of Agent-Environment Interaction

DTIC Science & Technology

2001-05-01

a color sensor in the gripper, a radio transmitter/receiver for communication and data gathering, and an ultrasound /radio triangulation system for...Cooperative Mobile Robot Control’, Autonomous Robots 4(4), 387{403. Vaughan, R. T., Sty, K., Sukhatme, G. S. & Mataric, M. J. (2000), Whistling in the Dark...sensor in the gripper, a radio transmitter/receiver for communication and data gathering, and an ultrasound /radio triangu- lation system for

A Robust Compositional Architecture for Autonomous Systems

NASA Technical Reports Server (NTRS)

Brat, Guillaume; Deney, Ewen; Farrell, Kimberley; Giannakopoulos, Dimitra; Jonsson, Ari; Frank, Jeremy; Bobby, Mark; Carpenter, Todd; Estlin, Tara

2006-01-01

Space exploration applications can benefit greatly from autonomous systems. Great distances, limited communications and high costs make direct operations impossible while mandating operations reliability and efficiency beyond what traditional commanding can provide. Autonomous systems can improve reliability and enhance spacecraft capability significantly. However, there is reluctance to utilizing autonomous systems. In part this is due to general hesitation about new technologies, but a more tangible concern is that of reliability of predictability of autonomous software. In this paper, we describe ongoing work aimed at increasing robustness and predictability of autonomous software, with the ultimate goal of building trust in such systems. The work combines state-of-the-art technologies and capabilities in autonomous systems with advanced validation and synthesis techniques. The focus of this paper is on the autonomous system architecture that has been defined, and on how it enables the application of validation techniques for resulting autonomous systems.

Challenges in Ocean Data Assimilation for the US West Coast

NASA Astrophysics Data System (ADS)

Li, Z.; Chao, Y.; Farrara, J.; Wang, X.

2006-12-01

A three-dimensional variational data assimilation (3DVAR) system has been developed for the Regional Ocean Modeling System (ROMS), and it is called ROMS-DAS. This system provides a capability of predicting meso- to small-scale variations with temporal scales from hours to days in the coastal oceans. To cope with the particular difficulties that result from complex coastlines and bottom topography, unbalanced flows and sparse observations, ROMS-DAS utilizes several novel strategies. These strategies include the implementation of three-dimensional anisotropic and inhomogeneous error correlations, application of particular weak dynamic constraints, and implementation of efficient and reliable algorithms for minimizing the cost function. The ROMS-DAS system was applied in field experiments for Monterey Bay during both 2003 (Autonomous Ocean Sampling Network - AOSN) and 2006 (MB06). These two experiments included intensive data collection from a variety of observational platforms, including satellites, airplanes, High Frequency radars, Acoustic Doppler Current Profilers, ships, drifters, buoys, autonomous underwater vehicles (AUV), and particularly a fleet of undersea gliders. Using these data sets, various data assimilation experiments were performed to address several major data assimilation challenges that arise from multi-scales structures, inhomogeneous properties, dynamical imbalance of the flow, and tides. Basing on these experiments, a set of strategies were formulated to deal with those challenges.

Integrated communication and control systems. I - Analysis

NASA Technical Reports Server (NTRS)

Halevi, Yoram; Ray, Asok

1988-01-01

The paper presents the results of an ICCS analysis focusing on discrete-time control systems subject to time-varying delays. The present analytical technique is applicable to integrated dynamic systems such as those encountered in advanced aircraft, spacecraft, and the real-time control of robots and machine tools via a high-speed network within an autonomous manufacturing environment. The significance of data latency and missynchronization between individual system components in ICCS networks is discussed in view of the time-varying delays.

Nonlinear analysis of pupillary dynamics.

PubMed

Onorati, Francesco; Mainardi, Luca Tommaso; Sirca, Fabiola; Russo, Vincenzo; Barbieri, Riccardo

2016-02-01

Pupil size reflects autonomic response to different environmental and behavioral stimuli, and its dynamics have been linked to other autonomic correlates such as cardiac and respiratory rhythms. The aim of this study is to assess the nonlinear characteristics of pupil size of 25 normal subjects who participated in a psychophysiological experimental protocol with four experimental conditions, namely “baseline”, “anger”, “joy”, and “sadness”. Nonlinear measures, such as sample entropy, correlation dimension, and largest Lyapunov exponent, were computed on reconstructed signals of spontaneous fluctuations of pupil dilation. Nonparametric statistical tests were performed on surrogate data to verify that the nonlinear measures are an intrinsic characteristic of the signals. We then developed and applied a piecewise linear regression model to detrended fluctuation analysis (DFA). Two joinpoints and three scaling intervals were identified: slope α0, at slow time scales, represents a persistent nonstationary long-range correlation, whereas α1 and α2, at middle and fast time scales, respectively, represent long-range power-law correlations, similarly to DFA applied to heart rate variability signals. Of the computed complexity measures, α0 showed statistically significant differences among experimental conditions (p<0.001). Our results suggest that (a) pupil size at constant light condition is characterized by nonlinear dynamics, (b) three well-defined and distinct long-memory processes exist at different time scales, and (c) autonomic stimulation is partially reflected in nonlinear dynamics. (c) autonomic stimulation is partially reflected in nonlinear dynamics.

Successful Detection of Floods in Real Time Onboard EO1 Through NASA's ST6 Autonomous Sciencecraft Experiment (ASE)

NASA Astrophysics Data System (ADS)

Ip, F.; Dohm, J. M.; Baker, V. R.; Castano, R.; Cichy, B.; Chien, S.; Davies, A.; Doggett, T.; Greeley, R.

2004-12-01

For the first time, a spacecraft has the ability to autonomously detect and react to flood events. Flood detection and the investigation of flooding dynamics in real time from space have never been done before at least not until now. Part of the challenge for the hydrological community has been the difficulty of obtaining cloud-free scenes from orbit at sufficient temporal and spatial resolutions to accurately assess flooding. In addition, the large spatial extent of drainage networks coupled with the size of the data sets necessary to be downlinked from satellites add to the difficulty of monitoring flooding from space. Technology developed as part of the Autonomous Sciencecraft Experiment (ASE) creates the new capability to autonomously detect, assess, and react to dynamic events, thereby enabling the monitoring of transient processes such as flooding in real time. In addition to being able to autonomously process the imaged data onboard the spacecraft for the first time and search the data for specific spectral features, the ASE Science Team has developed and tested change detection algorithms for the Hyperion spectrometer on EO-1. For flood events, if a change is detected in the onboard processed image (i.e. an increase in the number of ¡wet¡" pixels relative to a baseline image where the system is in normal flow condition or relatively dry), the spacecraft is autonomously retasked to obtain additional scenes. For instance, in February 2004 a rare flooding of the Australian Diamantina River was captured by EO-1. In addition, in August during ASE onboard testing a Zambezi River scene in Central Africa was successfully triggered by the classifier to autonomously take another observation. Yet another successful trigger-response flooding test scenario of the Yellow River in China was captured by ASE on 8/18/04. These exciting results pave the way for future smart reconnaissance missions of transient processes on Earth and beyond. Acknowledgments: We are grateful to the City of Tucson and Tucson Water for their support and cooperation.

Target Trailing With Safe Navigation for Maritime Autonomous Surface Vehicles

NASA Technical Reports Server (NTRS)

Wolf, Michael; Kuwata, Yoshiaki; Zarzhitsky, Dimitri V.

2013-01-01

This software implements a motion-planning module for a maritime autonomous surface vehicle (ASV). The module trails a given target while also avoiding static and dynamic surface hazards. When surface hazards are other moving boats, the motion planner must apply International Regulations for Avoiding Collisions at Sea (COLREGS). A key subset of these rules has been implemented in the software. In case contact with the target is lost, the software can receive and follow a "reacquisition route," provided by a complementary system, until the target is reacquired. The programmatic intention is that the trailed target is a submarine, although any mobile naval platform could serve as the target. The algorithmic approach to combining motion with a (possibly moving) goal location, while avoiding local hazards, may be applicable to robotic rovers, automated landing systems, and autonomous airships. The software operates in JPL s CARACaS (Control Architecture for Robotic Agent Command and Sensing) software architecture and relies on other modules for environmental perception data and information on the predicted detectability of the target, as well as the low-level interface to the boat controls.

Human Guidance Behavior Decomposition and Modeling

NASA Astrophysics Data System (ADS)

Feit, Andrew James

Trained humans are capable of high performance, adaptable, and robust first-person dynamic motion guidance behavior. This behavior is exhibited in a wide variety of activities such as driving, piloting aircraft, skiing, biking, and many others. Human performance in such activities far exceeds the current capability of autonomous systems in terms of adaptability to new tasks, real-time motion planning, robustness, and trading safety for performance. The present work investigates the structure of human dynamic motion guidance that enables these performance qualities. This work uses a first-person experimental framework that presents a driving task to the subject, measuring control inputs, vehicle motion, and operator visual gaze movement. The resulting data is decomposed into subspace segment clusters that form primitive elements of action-perception interactive behavior. Subspace clusters are defined by both agent-environment system dynamic constraints and operator control strategies. A key contribution of this work is to define transitions between subspace cluster segments, or subgoals, as points where the set of active constraints, either system or operator defined, changes. This definition provides necessary conditions to determine transition points for a given task-environment scenario that allow a solution trajectory to be planned from known behavior elements. In addition, human gaze behavior during this task contains predictive behavior elements, indicating that the identified control modes are internally modeled. Based on these ideas, a generative, autonomous guidance framework is introduced that efficiently generates optimal dynamic motion behavior in new tasks. The new subgoal planning algorithm is shown to generate solutions to certain tasks more quickly than existing approaches currently used in robotics.

Autonomy in robots and other agents.

PubMed

Smithers, T

1997-06-01

The word "autonomous" has become widely used in artificial intelligence, robotics, and, more recently, artificial life and is typically used to qualify types of systems, agents, or robots: we see terms like "autonomous systems," "autonomous agents," and "autonomous robots." Its use in these fields is, however, both weak, with no distinctions being made that are not better and more precisely made with other existing terms, and varied, with no single underlying concept being involved. This ill-disciplined usage contrasts strongly with the use of the same term in other fields such as biology, philosophy, ethics, law, and human rights, for example. In all these quite different areas the concept of autonomy is essentially the same, though the language used and the aspects and issues of concern, of course, differ. In all these cases the underlying notion is one of self-law making and the closely related concept of self-identity. In this paper I argue that the loose and varied use of the term autonomous in artificial intelligence, robotics, and artificial life has effectively robbed these fields of an important concept. A concept essentially the same as we find it in biology, philosophy, ethics, and law, and one that is needed to distinguish a particular kind of agent or robot from those developed and built so far. I suggest that robots and other agents will have to be autonomous, i.e., self-law making, not just self-regulating, if they are to be able effectively to deal with the kinds of environments in which we live and work: environments which have significant large scale spatial and temporal invariant structure, but which also have large amounts of local spatial and temporal dynamic variation and unpredictability, and which lead to the frequent occurrence of previously unexperienced situations for the agents that interact with them.

Using machine learning to replicate chaotic attractors and calculate Lyapunov exponents from data

NASA Astrophysics Data System (ADS)

Pathak, Jaideep; Lu, Zhixin; Hunt, Brian R.; Girvan, Michelle; Ott, Edward

2017-12-01

We use recent advances in the machine learning area known as "reservoir computing" to formulate a method for model-free estimation from data of the Lyapunov exponents of a chaotic process. The technique uses a limited time series of measurements as input to a high-dimensional dynamical system called a "reservoir." After the reservoir's response to the data is recorded, linear regression is used to learn a large set of parameters, called the "output weights." The learned output weights are then used to form a modified autonomous reservoir designed to be capable of producing an arbitrarily long time series whose ergodic properties approximate those of the input signal. When successful, we say that the autonomous reservoir reproduces the attractor's "climate." Since the reservoir equations and output weights are known, we can compute the derivatives needed to determine the Lyapunov exponents of the autonomous reservoir, which we then use as estimates of the Lyapunov exponents for the original input generating system. We illustrate the effectiveness of our technique with two examples, the Lorenz system and the Kuramoto-Sivashinsky (KS) equation. In the case of the KS equation, we note that the high dimensional nature of the system and the large number of Lyapunov exponents yield a challenging test of our method, which we find the method successfully passes.

Biologically-Inspired Concepts for Autonomic Self-Protection in Multiagent Systems

NASA Technical Reports Server (NTRS)

Sterritt, Roy; Hinchey, Mike

2006-01-01

Biologically-inspired autonomous and autonomic systems (AAS) are essentially concerned with creating self-directed and self-managing systems based on metaphors &om nature and the human body, such as the autonomic nervous system. Agent technologies have been identified as a key enabler for engineering autonomy and autonomicity in systems, both in terms of retrofitting into legacy systems and in designing new systems. Handing over responsibility to systems themselves raises concerns for humans with regard to safety and security. This paper reports on the continued investigation into a strand of research on how to engineer self-protection mechanisms into systems to assist in encouraging confidence regarding security when utilizing autonomy and autonomicity. This includes utilizing the apoptosis and quiescence metaphors to potentially provide a self-destruct or self-sleep signal between autonomic agents when needed, and an ALice signal to facilitate self-identification and self-certification between anonymous autonomous agents and systems.

Adaptable mission planning for kino-dynamic systems

NASA Astrophysics Data System (ADS)

Bush, Lawrence A. M.; Jimenez, Tony R.; Williams, Brian C.

Autonomous systems can perform tasks that are dangerous, monotonous, or even impossible for humans. To approach the problem of planning for Unmanned Aerial Vehicles (UAVs) we present a hierarchical method that combines a high-level planner with a low-level planner. We pose the problem of high-level planning as a Selective Traveling Salesman Problem (STSP) and select the order in which to visit our science sites. We then use a kino-dynamic path planner to create a large number of intermediate waypoints. This is a complete system that combines high and low level planning to achieve a goal. This paper demonstrates the benefits gained by adaptable high-level plans versus static and greedy plans.

Advancing Underwater Acoustic Communication for Autonomous Distributed Networks via Sparse Channel Sensing, Coding, and Navigation Support

DTIC Science & Technology

2014-09-30

underwater acoustic communication technologies for autonomous distributed underwater networks , through innovative signal processing, coding, and...4. TITLE AND SUBTITLE Advancing Underwater Acoustic Communication for Autonomous Distributed Networks via Sparse Channel Sensing, Coding, and...coding: 3) OFDM modulated dynamic coded cooperation in underwater acoustic channels; 3 Localization, Networking , and Testbed: 4) On-demand

Neurodynamics in the Sensorimotor Loop: Representing Behavior Relevant External Situations

PubMed Central

Pasemann, Frank

2017-01-01

In the context of the dynamical system approach to cognition and supposing that brains or brain-like systems controlling the behavior of autonomous systems are permanently driven by their sensor signals, the paper approaches the question of neurodynamics in the sensorimotor loop in a purely formal way. This is carefully done by addressing the problem in three steps, using the time-discrete dynamics of standard neural networks and a fiber space representation for better clearness. Furthermore, concepts like meta-transients, parametric stability and dynamical forms are introduced, where meta-transients describe the effect of realistic sensor inputs, parametric stability refers to a class of sensor inputs all generating the “same type” of dynamic behavior, and a dynamical form comprises the corresponding class of parametrized dynamical systems. It is argued that dynamical forms are the essential internal representatives of behavior relevant external situations. Consequently, it is suggested that dynamical forms are the basis for a memory of these situations. Finally, based on the observation that not all brain process have a direct effect on the motor activity, a natural splitting of neurodynamics into vertical (internal) and horizontal (effective) parts is introduced. PMID:28217092

DOE Office of Scientific and Technical Information (OSTI.GOV)

Raymond, David W.; Blankenship, Douglas A.; Buerger, Stephen

The dynamic stability of deep drillstrings is challenged by an inability to impart controllability with ever-changing conditions introduced by geology, depth, structural dynamic properties and operating conditions. A multi-organizational LDRD project team at Sandia National Laboratories successfully demonstrated advanced technologies for mitigating drillstring vibrations to improve the reliability of drilling systems used for construction of deep, high-value wells. Using computational modeling and dynamic substructuring techniques, the benefit of controllable actuators at discrete locations in the drillstring is determined. Prototype downhole tools were developed and evaluated in laboratory test fixtures simulating the structural dynamic response of a deep drillstring. A laboratory-basedmore » drilling applicability demonstration was conducted to demonstrate the benefit available from deployment of an autonomous, downhole tool with self-actuation capabilities in response to the dynamic response of the host drillstring. A concept is presented for a prototype drilling tool based upon the technical advances. The technology described herein is the subject of U.S. Patent Application No. 62219481, entitled "DRILLING SYSTEM VIBRATION SUPPRESSION SYSTEMS AND METHODS", filed September 16, 2015.« less

Sampling-based real-time motion planning under state uncertainty for autonomous micro-aerial vehicles in GPS-denied environments.

PubMed

Li, Dachuan; Li, Qing; Cheng, Nong; Song, Jingyan

2014-11-18

This paper presents a real-time motion planning approach for autonomous vehicles with complex dynamics and state uncertainty. The approach is motivated by the motion planning problem for autonomous vehicles navigating in GPS-denied dynamic environments, which involves non-linear and/or non-holonomic vehicle dynamics, incomplete state estimates, and constraints imposed by uncertain and cluttered environments. To address the above motion planning problem, we propose an extension of the closed-loop rapid belief trees, the closed-loop random belief trees (CL-RBT), which incorporates predictions of the position estimation uncertainty, using a factored form of the covariance provided by the Kalman filter-based estimator. The proposed motion planner operates by incrementally constructing a tree of dynamically feasible trajectories using the closed-loop prediction, while selecting candidate paths with low uncertainty using efficient covariance update and propagation. The algorithm can operate in real-time, continuously providing the controller with feasible paths for execution, enabling the vehicle to account for dynamic and uncertain environments. Simulation results demonstrate that the proposed approach can generate feasible trajectories that reduce the state estimation uncertainty, while handling complex vehicle dynamics and environment constraints.

Sampling-Based Real-Time Motion Planning under State Uncertainty for Autonomous Micro-Aerial Vehicles in GPS-Denied Environments

PubMed Central

Li, Dachuan; Li, Qing; Cheng, Nong; Song, Jingyan

2014-01-01

This paper presents a real-time motion planning approach for autonomous vehicles with complex dynamics and state uncertainty. The approach is motivated by the motion planning problem for autonomous vehicles navigating in GPS-denied dynamic environments, which involves non-linear and/or non-holonomic vehicle dynamics, incomplete state estimates, and constraints imposed by uncertain and cluttered environments. To address the above motion planning problem, we propose an extension of the closed-loop rapid belief trees, the closed-loop random belief trees (CL-RBT), which incorporates predictions of the position estimation uncertainty, using a factored form of the covariance provided by the Kalman filter-based estimator. The proposed motion planner operates by incrementally constructing a tree of dynamically feasible trajectories using the closed-loop prediction, while selecting candidate paths with low uncertainty using efficient covariance update and propagation. The algorithm can operate in real-time, continuously providing the controller with feasible paths for execution, enabling the vehicle to account for dynamic and uncertain environments. Simulation results demonstrate that the proposed approach can generate feasible trajectories that reduce the state estimation uncertainty, while handling complex vehicle dynamics and environment constraints. PMID:25412217

Nonalgebraic integrability of one reversible dynamical system of the Cremona type

NASA Astrophysics Data System (ADS)

Rerikh, K. V.

1998-05-01

A reversible dynamical system (RDS) and a system of nonlinear functional equations, defined by a certain rational quadratic Cremona mapping and arising from the static model of the dispersion approach in the theory of strong interactions [the Chew-Low-type equations with crossing-symmetry matrix A(l,1)], are considered. This RDS is split into one- and two-dimensional ones. An explicit Cremona transformation that completely determines the exact solution of the two-dimensional system is found. This solution depends on an odd function satisfying a nonlinear autonomous three-point functional equation. Nonalgebraic integrability of RDS under consideration is proved using the method of Poincaré normal forms and the Siegel theorem on biholomorphic linearization of a mapping at a nonresonant fixed point.

Dynamical Motor Control Learned with Deep Deterministic Policy Gradient

PubMed Central

2018-01-01

Conventional models of motor control exploit the spatial representation of the controlled system to generate control commands. Typically, the control command is gained with the feedback state of a specific instant in time, which behaves like an optimal regulator or spatial filter to the feedback state. Yet, recent neuroscience studies found that the motor network may constitute an autonomous dynamical system and the temporal patterns of the control command can be contained in the dynamics of the motor network, that is, the dynamical system hypothesis (DSH). Inspired by these findings, here we propose a computational model that incorporates this neural mechanism, in which the control command could be unfolded from a dynamical controller whose initial state is specified with the task parameters. The model is trained in a trial-and-error manner in the framework of deep deterministic policy gradient (DDPG). The experimental results show that the dynamical controller successfully learns the control policy for arm reaching movements, while the analysis of the internal activities of the dynamical controller provides the computational evidence to the DSH of the neural coding in motor cortices. PMID:29666634

Dynamical Motor Control Learned with Deep Deterministic Policy Gradient.

PubMed

Shi, Haibo; Sun, Yaoru; Li, Jie

2018-01-01

Conventional models of motor control exploit the spatial representation of the controlled system to generate control commands. Typically, the control command is gained with the feedback state of a specific instant in time, which behaves like an optimal regulator or spatial filter to the feedback state. Yet, recent neuroscience studies found that the motor network may constitute an autonomous dynamical system and the temporal patterns of the control command can be contained in the dynamics of the motor network, that is, the dynamical system hypothesis (DSH). Inspired by these findings, here we propose a computational model that incorporates this neural mechanism, in which the control command could be unfolded from a dynamical controller whose initial state is specified with the task parameters. The model is trained in a trial-and-error manner in the framework of deep deterministic policy gradient (DDPG). The experimental results show that the dynamical controller successfully learns the control policy for arm reaching movements, while the analysis of the internal activities of the dynamical controller provides the computational evidence to the DSH of the neural coding in motor cortices.

Autonomous control of production networks using a pheromone approach

NASA Astrophysics Data System (ADS)

Armbruster, D.; de Beer, C.; Freitag, M.; Jagalski, T.; Ringhofer, C.

2006-04-01

The flow of parts through a production network is usually pre-planned by a central control system. Such central control fails in presence of highly fluctuating demand and/or unforeseen disturbances. To manage such dynamic networks according to low work-in-progress and short throughput times, an autonomous control approach is proposed. Autonomous control means a decentralized routing of the autonomous parts themselves. The parts’ decisions base on backward propagated information about the throughput times of finished parts for different routes. So, routes with shorter throughput times attract parts to use this route again. This process can be compared to ants leaving pheromones on their way to communicate with following ants. The paper focuses on a mathematical description of such autonomously controlled production networks. A fluid model with limited service rates in a general network topology is derived and compared to a discrete-event simulation model. Whereas the discrete-event simulation of production networks is straightforward, the formulation of the addressed scenario in terms of a fluid model is challenging. Here it is shown, how several problems in a fluid model formulation (e.g. discontinuities) can be handled mathematically. Finally, some simulation results for the pheromone-based control with both the discrete-event simulation model and the fluid model are presented for a time-dependent influx.

The SSM/PMAD automated test bed project

NASA Technical Reports Server (NTRS)

Lollar, Louis F.

1991-01-01

The Space Station Module/Power Management and Distribution (SSM/PMAD) autonomous subsystem project was initiated in 1984. The project's goal has been to design and develop an autonomous, user-supportive PMAD test bed simulating the SSF Hab/Lab module(s). An eighteen kilowatt SSM/PMAD test bed model with a high degree of automated operation has been developed. This advanced automation test bed contains three expert/knowledge based systems that interact with one another and with other more conventional software residing in up to eight distributed 386-based microcomputers to perform the necessary tasks of real-time and near real-time load scheduling, dynamic load prioritizing, and fault detection, isolation, and recovery (FDIR).

In Situ Surveying of Saturn's Rings

NASA Astrophysics Data System (ADS)

Clark, P. E.; Rilee, M. L.; Curtis, S. A.; Cheung, C.

2004-03-01

Saturn Autonomous Ring Array (SARA) mission concept is an application for the Autonomous Nano-Technology Swarm (ANTS) architecture that would perform in situ observations of compositional and dynamic properties of ring particles, a challenge unachievable by previous mission designs.

System identification and the modeling of sailing yachts

NASA Astrophysics Data System (ADS)

Legursky, Katrina

This research represents an exploration of sailing yacht dynamics with full-scale sailing motion data, physics-based models, and system identification techniques. The goal is to provide a method of obtaining and validating suitable physics-based dynamics models for use in control system design on autonomous sailing platforms, which have the capacity to serve as mobile, long range, high endurance autonomous ocean sensing platforms. The primary contributions of this study to the state-of-the-art are the formulation of a five degree-of-freedom (DOF) linear multi-input multi-output (MIMO) state space model of sailing yacht dynamics, the process for identification of this model from full-scale data, a description of the maneuvers performed during on-water tests, and an analysis method to validate estimated models. The techniques and results described herein can be directly applied to and tested on existing autonomous sailing platforms. A full-scale experiment on a 23ft monohull sailing yacht is developed to collect motion data for physics-based model identification. Measurements include 3 axes of accelerations, velocities, angular rates, and attitude angles in addition to apparent wind speed and direction. The sailing yacht herein is treated as a dynamic system with two control inputs, the rudder angle, deltaR, and the mainsail angle, delta B, which are also measured. Over 20 hours of full scale sailing motion data is collected, representing three sail configurations corresponding to a range of wind speeds: the Full Main and Genoa (abbrev. Genoa) for lower wind speeds, the Full Main and Jib (abbrev. Jib) for mid-range wind speeds, and the Reefed Main and Jib (abbrev. Reef) for the highest wind speeds. The data also covers true wind angles from upwind through a beam reach. A physics-based non-linear model to describe sailing yacht motion is outlined, including descriptions of methods to model the aerodynamics and hydrodynamics of a sailing yacht in surge, sway, roll, and yaw. Existing aerodynamic models for sailing yachts are unsuitable for control system design as they do not include a physical description of the sails' dynamic effect on the system. A new aerodynamic model is developed and validated using the full-scale sailing data which includes sail deflection as a control input to the system. The Maximum Likelihood Estimation (MLE) algorithm is used with non-linear simulation data to successfully estimate a set of hydrodynamic derivatives for a sailing yacht. It is shown that all sailing yacht models will contain a second order mode (referred to herein as Mode 1A.S or 4B.S) which is dependent upon trimmed roll angle. For the test yacht it is concluded that for this mode when the trimmed roll angle is, roll rate and roll angle are the dominant motion variables, and for surge velocity and yaw rate dominate. This second order mode is dynamically stable for . It transitions from stability in the higher values of to instability in the region defined by. These conclusions align with other work which has also found roll angle to be a driving factor in the dynamic behavior of a tall-ship (Johnson, Miles, Lasher, & Womack, 2009). It is also shown that all linear models also contain a first order mode, (referred to herein as Mode 3A.F or 1B.F), which lies very close to the origin of the complex plane indicating a long time constant. Measured models have indicated this mode can be stable or unstable. The eigenvector analysis reveals that the mode is stable if the surge contribution is < 40% and the sway contribution is > 20%. The small set of maneuvers necessary for model identification, quick OSLS estimation method, and detailed modal analysis of estimated models outlined in this work are immediately applicable to existing autonomous mono-hull sailing yachts, and could readily be adapted for use with other wind-powered vessel configurations such as wing-sails, catamarans, and tri-marans. (Abstract shortened by UMI.)

Non-autonomous multi-rogue waves for spin-1 coupled nonlinear Gross-Pitaevskii equation and management by external potentials.

PubMed

Li, Li; Yu, Fajun

2017-09-06

We investigate non-autonomous multi-rogue wave solutions in a three-component(spin-1) coupled nonlinear Gross-Pitaevskii(GP) equation with varying dispersions, higher nonlinearities, gain/loss and external potentials. The similarity transformation allows us to relate certain class of multi-rogue wave solutions of the spin-1 coupled nonlinear GP equation to the solutions of integrable coupled nonlinear Schrödinger(CNLS) equation. We study the effect of time-dependent quadratic potential on the profile and dynamic of non-autonomous rogue waves. With certain requirement on the backgrounds, some non-autonomous multi-rogue wave solutions exhibit the different shapes with two peaks and dip in bright-dark rogue waves. Then, the managements with external potential and dynamic behaviors of these solutions are investigated analytically. The results could be of interest in such diverse fields as Bose-Einstein condensates, nonlinear fibers and super-fluids.

Optimal rotation sequences for active perception

NASA Astrophysics Data System (ADS)

Nakath, David; Rachuy, Carsten; Clemens, Joachim; Schill, Kerstin

2016-05-01

One major objective of autonomous systems navigating in dynamic environments is gathering information needed for self localization, decision making, and path planning. To account for this, such systems are usually equipped with multiple types of sensors. As these sensors often have a limited field of view and a fixed orientation, the task of active perception breaks down to the problem of calculating alignment sequences which maximize the information gain regarding expected measurements. Action sequences that rotate the system according to the calculated optimal patterns then have to be generated. In this paper we present an approach for calculating these sequences for an autonomous system equipped with multiple sensors. We use a particle filter for multi- sensor fusion and state estimation. The planning task is modeled as a Markov decision process (MDP), where the system decides in each step, what actions to perform next. The optimal control policy, which provides the best action depending on the current estimated state, maximizes the expected cumulative reward. The latter is computed from the expected information gain of all sensors over time using value iteration. The algorithm is applied to a manifold representation of the joint space of rotation and time. We show the performance of the approach in a spacecraft navigation scenario where the information gain is changing over time, caused by the dynamic environment and the continuous movement of the spacecraft

Dynamic bin packing problem

NASA Technical Reports Server (NTRS)

Dikshit, Piyush; Guimaraes, Katia; Ramamurthy, Maya; Agrawala, Ashok K.; Larsen, Ronald L.

1989-01-01

In a previous work we have defined a general architecture model for autonomous systems, which can be mapped easily to describe the functions of any automated system (SDAG-86-01). In this note, we use the model to describe the problem of thermal management in space stations. First we briefly review the architecture, then we present the environment of our application, and finally we detail the specific function for each functional block of the architecture for that environment.

Dynamic reasoning in a knowledge-based system

NASA Technical Reports Server (NTRS)

Rao, Anand S.; Foo, Norman Y.

1988-01-01

Any space based system, whether it is a robot arm assembling parts in space or an onboard system monitoring the space station, has to react to changes which cannot be foreseen. As a result, apart from having domain-specific knowledge as in current expert systems, a space based AI system should also have general principles of change. This paper presents a modal logic which can not only represent change but also reason with it. Three primitive operations, expansion, contraction and revision are introduced and axioms which specify how the knowledge base should change when the external world changes are also specified. Accordingly the notion of dynamic reasoning is introduced, which unlike the existing forms of reasoning, provide general principles of change. Dynamic reasoning is based on two main principles, namely minimize change and maximize coherence. A possible-world semantics which incorporates the above two principles is also discussed. The paper concludes by discussing how the dynamic reasoning system can be used to specify actions and hence form an integral part of an autonomous reasoning and planning system.

INL Autonomous Navigation System

DOE Office of Scientific and Technical Information (OSTI.GOV)

2005-03-30

The INL Autonomous Navigation System provides instructions for autonomously navigating a robot. The system permits high-speed autonomous navigation including obstacle avoidance, waypoing navigation and path planning in both indoor and outdoor environments.

Dynamics of Sequential Decision Making

NASA Astrophysics Data System (ADS)

Rabinovich, Mikhail I.; Huerta, Ramón; Afraimovich, Valentin

2006-11-01

We suggest a new paradigm for intelligent decision-making suitable for dynamical sequential activity of animals or artificial autonomous devices that depends on the characteristics of the internal and external world. To do it we introduce a new class of dynamical models that are described by ordinary differential equations with a finite number of possibilities at the decision points, and also include rules solving this uncertainty. Our approach is based on the competition between possible cognitive states using their stable transient dynamics. The model controls the order of choosing successive steps of a sequential activity according to the environment and decision-making criteria. Two strategies (high-risk and risk-aversion conditions) that move the system out of an erratic environment are analyzed.

An intelligent training system for payload-assist module deploys

NASA Technical Reports Server (NTRS)

Loftin, R. Bowen; Wang, Lui; Baffes, Paul; Rua, Monica

1987-01-01

An autonomous intelligent training system which integrates expert system technology with training/teaching methodologies is described. The Payload-Assist Module Deploys/Intelligent Computer-Aided Training (PD/ICAT) system has, so far, proven to be a potentially valuable addition to the training tools available for training Flight Dynamics Officers in shuttle ground control. The authors are convinced that the basic structure of PD/ICAT can be extended to form a general architecture for intelligent training systems for training flight controllers and crew members in the performance of complex, mission-critical tasks.

Rhythmical massage improves autonomic nervous system function: a single-blind randomised controlled trial.

PubMed

Seifert, Georg; Kanitz, Jenny-Lena; Rihs, Carolina; Krause, Ingrid; Witt, Katharina; Voss, Andreas

2018-05-01

Rhythmical massage therapy (RMT) is a massage technique used in anthroposophic medicine. The authors aimed to investigate the physiological action of RMT on the cardiovascular system by analysing heart rate variability (HRV). This study was a randomised, controlled and single-blinded trial, involving 44 healthy women (mean age: (26.20 ± 4.71) years). The subjects were randomised to one of three arms: RMT with aromatic oil (RA), RMT without aromatic oil (RM) or standardised sham massage (SM). In the study the subjects were exposed to a standardised stress situation followed by one of the study techniques and Holter electrocardiograms (ECGs) were recorded for 24 h. HRV parameters were calculated from linear (time and frequency domain) and nonlinear dynamics (symbolic dynamics, Poincare plot analysis) of the 24-h Holter ECG records. Short- and long-term effects of massage on autonomic regulation differed significantly among the three groups. Immediately after an RMT session, stimulation of HRV was found in the groups RA and RM. The use of an aromatic oil produced greater short-term measurable changes in HRV compared with rhythmic massage alone, but after 24 h the effect was no longer distinguishable from the RM group. The lowest stimulation of HRV parameters was measured in the SM group. RMT causes specific and marked stimulation of the autonomic nervous system. Use of a medicinal aromatic oil had only a temporary effect on HRV, indicating that the RM causes the most relevant long-term effect. The effect is relatively specific, as the physiological effects seen in the group of subjects who received only SM were considerably less pronounced. Registration trial DRKS00004164 on DRKS. Copyright © 2018 Shanghai Changhai Hospital. Published by Elsevier B.V. All rights reserved.

Control Architecture for Robotic Agent Command and Sensing

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance; Aghazarian, Hrand; Estlin, Tara; Gaines, Daniel

2008-01-01

Control Architecture for Robotic Agent Command and Sensing (CARACaS) is a recent product of a continuing effort to develop architectures for controlling either a single autonomous robotic vehicle or multiple cooperating but otherwise autonomous robotic vehicles. CARACaS is potentially applicable to diverse robotic systems that could include aircraft, spacecraft, ground vehicles, surface water vessels, and/or underwater vessels. CARACaS incudes an integral combination of three coupled agents: a dynamic planning engine, a behavior engine, and a perception engine. The perception and dynamic planning en - gines are also coupled with a memory in the form of a world model. CARACaS is intended to satisfy the need for two major capabilities essential for proper functioning of an autonomous robotic system: a capability for deterministic reaction to unanticipated occurrences and a capability for re-planning in the face of changing goals, conditions, or resources. The behavior engine incorporates the multi-agent control architecture, called CAMPOUT, described in An Architecture for Controlling Multiple Robots (NPO-30345), NASA Tech Briefs, Vol. 28, No. 11 (November 2004), page 65. CAMPOUT is used to develop behavior-composition and -coordination mechanisms. Real-time process algebra operators are used to compose a behavior network for any given mission scenario. These operators afford a capability for producing a formally correct kernel of behaviors that guarantee predictable performance. By use of a method based on multi-objective decision theory (MODT), recommendations from multiple behaviors are combined to form a set of control actions that represents their consensus. In this approach, all behaviors contribute simultaneously to the control of the robotic system in a cooperative rather than a competitive manner. This approach guarantees a solution that is good enough with respect to resolution of complex, possibly conflicting goals within the constraints of the mission to be accomplished by the vehicle(s).

Towards an Autonomous Space In-Situ Marine Sensorweb

NASA Technical Reports Server (NTRS)

Chien, S.; Doubleday, J.; Tran, D.; Thompson, D.; Mahoney, G.; Chao, Y.; Castano, R.; Ryan, J.; Kudela, R.; Palacios, S.;

Simulation and Flight Control of an Aeroelastic Fixed Wing Micro Aerial Vehicle

NASA Technical Reports Server (NTRS)

Waszak, Martin; Davidson, John B.; Ifju, Peter G.

2002-01-01

Micro aerial vehicles have been the subject of continued interest and development over the last several years. The majority of current vehicle concepts rely on rigid fixed wings or rotors. An alternate design based on an aeroelastic membrane wing has also been developed that exhibits desired characteristics in flight test demonstrations, competition, and in prior aerodynamics studies. This paper presents a simulation model and an assessment of flight control characteristics of the vehicle. Linear state space models of the vehicle associated with typical trimmed level flight conditions and which are suitable for control system design are presented as well. The simulation is used as the basis for the design of a measurement based nonlinear dynamic inversion control system and outer loop guidance system. The vehicle/controller system is the subject of ongoing investigations of autonomous and collaborative control schemes. The results indicate that the design represents a good basis for further development of the micro aerial vehicle for autonomous and collaborative controls research.

A small, cheap, and portable reconnaissance robot

NASA Astrophysics Data System (ADS)

Kenyon, Samuel H.; Creary, D.; Thi, Dan; Maynard, Jeffrey

2005-05-01

While there is much interest in human-carriable mobile robots for defense/security applications, existing examples are still too large/heavy, and there are not many successful small human-deployable mobile ground robots, especially ones that can survive being thrown/dropped. We have developed a prototype small short-range teleoperated indoor reconnaissance/surveillance robot that is semi-autonomous. It is self-powered, self-propelled, spherical, and meant to be carried and thrown by humans into indoor, yet relatively unstructured, dynamic environments. The robot uses multiple channels for wireless control and feedback, with the potential for inter-robot communication, swarm behavior, or distributed sensor network capabilities. The primary reconnaissance sensor for this prototype is visible-spectrum video. This paper focuses more on the software issues, both the onboard intelligent real time control system and the remote user interface. The communications, sensor fusion, intelligent real time controller, etc. are implemented with onboard microcontrollers. We based the autonomous and teleoperation controls on a simple finite state machine scripting layer. Minimal localization and autonomous routines were designed to best assist the operator, execute whatever mission the robot may have, and promote its own survival. We also discuss the advantages and pitfalls of an inexpensive, rapidly-developed semi-autonomous robotic system, especially one that is spherical, and the importance of human-robot interaction as considered for the human-deployment and remote user interface.

Experimental results in autonomous landing approaches by dynamic machine vision

NASA Astrophysics Data System (ADS)

Dickmanns, Ernst D.; Werner, Stefan; Kraus, S.; Schell, R.

1994-07-01

The 4-D approach to dynamic machine vision, exploiting full spatio-temporal models of the process to be controlled, has been applied to on board autonomous landing approaches of aircraft. Aside from image sequence processing, for which it was developed initially, it is also used for data fusion from a range of sensors. By prediction error feedback an internal representation of the aircraft state relative to the runway in 3-D space and time is servo- maintained in the interpretation process, from which the control applications required are being derived. The validity and efficiency of the approach have been proven both in hardware- in-the-loop simulations and in flight experiments with a twin turboprop aircraft Do128 under perturbations from cross winds and wind gusts. The software package has been ported to `C' and onto a new transputer image processing platform; the system has been expanded for bifocal vision with two cameras of different focal length mounted fixed relative to each other on a two-axes platform for viewing direction control.

Flight Control System Development for the BURRO Autonomous UAV

NASA Technical Reports Server (NTRS)

Colbourne, Jason D.; Frost, Chad R.; Tischler, Mark B.; Ciolani, Luigi; Sahai, Ranjana; Tomoshofski, Chris; LaMontagne, Troy; Rutkowski, Michael (Technical Monitor)

2000-01-01

Developing autonomous flying vehicles has been a growing field in aeronautical research within the last decade and will continue into the next century. With concerns about safety, size, and cost of manned aircraft, several autonomous vehicle projects are currently being developed; uninhabited rotorcraft offer solutions to requirements for hover, vertical take-off and landing, as well as slung load transportation capabilities. The newness of the technology requires flight control engineers to question what design approaches, control law architectures, and performance criteria apply to control law development and handling quality evaluation. To help answer these questions, this paper documents the control law design process for Kaman Aerospace BURRO project. This paper will describe the approach taken to design control laws and develop math models which will be used to convert the manned K-MAX into the BURRO autonomous rotorcraft. With the ability of the K-MAX to lift its own weight (6000 lb) the load significantly affects the dynamics of the system; the paper addresses the additional design requirements for slung load autonomous flight. The approach taken in this design was to: 1) generate accurate math models of the K-MAX helicopter with and without slung loads, 2) select design specifications that would deliver good performance as well as satisfy mission criteria, and 3) develop and tune the control system architecture to meet the design specs and mission criteria. An accurate math model was desired for control system development. The Comprehensive Identification from Frequency Responses (CIFER(R)) software package was used to identify a linear math model for unloaded and loaded flight at hover, 50 kts, and 100 kts. The results of an eight degree-of-freedom CIFER(R)-identified linear model for the unloaded hover flight condition are presented herein, and the identification of the two-body slung-load configuration is in progress.

Asteroid Exploration with Autonomic Systems

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Rash, James; Rouff, Christopher; Hinchey, Mike

2004-01-01

NASA is studying advanced technologies for a future robotic exploration mission to the asteroid belt. The prospective ANTS (Autonomous Nano Technology Swarm) mission comprises autonomous agents including worker agents (small spacecra3) designed to cooperate in asteroid exploration under the overall authoriq of at least one ruler agent (a larger spacecraft) whose goal is to cause science data to be returned to Earth. The ANTS team (ruler plus workers and messenger agents), but not necessarily any individual on the team, will exhibit behaviors that qualify it as an autonomic system, where an autonomic system is defined as a system that self-reconfigures, self-optimizes, self-heals, and self-protects. Autonomic system concepts lead naturally to realistic, scalable architectures rich in capabilities and behaviors. In-depth consideration of a major mission like ANTS in terms of autonomic systems brings new insights into alternative definitions of autonomic behavior. This paper gives an overview of the ANTS mission and discusses the autonomic properties of the mission.

A Formal Investigation of the Organization of Guidance Behavior: Implications for Humans and Autonomous Guidance

NASA Astrophysics Data System (ADS)

Kong, Zhaodan

Guidance behavior generated either by artificial agents or humans has been actively studied in the fields of both robotics and cognitive science. The goals of these two fields are different. The former is the automatic generation of appropriate or even optimal behavior, while the latter is the understanding of the underlying mechanism. Their challenges, though, are closely related, the most important one being the lack of a unified, formal and grounded framework where the guidance behavior can be modeled and studied. This dissertation presents such a framework. In this framework, guidance behavior is analyzed as the closed-loop dynamics of the whole agent-environment system. The resulting dynamics give rise to interaction patterns. The central points of this dissertation are that: first of all, these patterns, which can be explained in terms of symmetries that are inherent to the guidance behavior, provide building blocks for the organization of behavior; second, the existence of these patterns and humans' organization of their guidance behavior based on these patterns are the reasons that humans can generate successful behavior in spite of all the complexities involved in the planning and control. This dissertation first gives an overview of the challenges existing in both scientific endeavors, such as human and animal spatial behavior study, and engineering endeavors, such as autonomous guidance system design. It then lays out the foundation for our formal framework, which states that guidance behavior should be interpreted as the collection of the closed-loop dynamics resulting from the agent's interaction with the environment. The following, illustrated by examples of three different UAVs, shows that the study of the closed-loop dynamics should not be done without the consideration of vehicle dynamics, as is the common practice in some of the studies in both autonomous guidance and human behavior analysis. The framework, the core concepts of which are symmetries and interaction patterns, is then elaborated on with the example of Dubins' vehicle's guidance behavior. The dissertation then describes the details of the agile human guidance experiments using miniature helicopters, the technique that is developed for the analysis of the experimental data and the analysis results. The results confirm that human guidance behavior indeed exhibits invariance as defined by interaction patterns. Subsequently, the behavior in each interaction pattern is investigated using piecewise affine model identification. Combined, the results provide a natural and formal decomposition of the behavior that can be unified under a hierarchical hidden Markov model. By employing the languages of dynamical system and control and by adopting algorithms from system identification and machine learning, the framework presented in this dissertation provides a fertile ground where these different disciplines can meet. It also promises multiple potential directions where future research can be headed.

[Effectiveness of transcranial magnetic therapy in the complex treatment of alcohol abstinent syndrome].

PubMed

Staroverov, A T; Zhukov, O B; Raĭgorodskiĭ, Iu M

2008-01-01

Fifty-four abstinent alcohol-dependent patients have been studied. Twenty-nine patients (a main group) received, along with basic therapy, a physiotherapeutic treatment (transcranial dynamic magnetic therapy) and 25 patients (a control group) received only basic therapy. The comparison of the efficacy of treatment in patients of the main and control groups revealed the benefits of transcranial dynamic magnetic therapy in CNS function, performance on memory and attention tests, state of autonomic nervous system and psychoemotional state of patients (the reduction of anxiety and depression).

Machine Learning Control For Highly Reconfigurable High-Order Systems

DTIC Science & Technology

2015-01-02

develop and flight test a Reinforcement Learning based approach for autonomous tracking of ground targets using a fixed wing Unmanned...Reinforcement Learning - based algorithms are developed for learning agents’ time dependent dynamics while also learning to control them. Three algorithms...to a wide range of engineering- based problems . Implementation of these solutions, however, is often complicated by the hysteretic, non-linear,

Characterizing psychological dimensions in non-pathological subjects through autonomic nervous system dynamics

PubMed Central

Nardelli, Mimma; Valenza, Gaetano; Cristea, Ioana A.; Gentili, Claudio; Cotet, Carmen; David, Daniel; Lanata, Antonio; Scilingo, Enzo P.

2015-01-01

The objective assessment of psychological traits of healthy subjects and psychiatric patients has been growing interest in clinical and bioengineering research fields during the last decade. Several experimental evidences strongly suggest that a link between Autonomic Nervous System (ANS) dynamics and specific dimensions such as anxiety, social phobia, stress, and emotional regulation might exist. Nevertheless, an extensive investigation on a wide range of psycho-cognitive scales and ANS non-invasive markers gathered from standard and non-linear analysis still needs to be addressed. In this study, we analyzed the discerning and correlation capabilities of a comprehensive set of ANS features and psycho-cognitive scales in 29 non-pathological subjects monitored during resting conditions. In particular, the state of the art of standard and non-linear analysis was performed on Heart Rate Variability, InterBreath Interval series, and InterBeat Respiration series, which were considered as monovariate and multivariate measurements. Experimental results show that each ANS feature is linked to specific psychological traits. Moreover, non-linear analysis outperforms the psychological assessment with respect to standard analysis. Considering that the current clinical practice relies only on subjective scores from interviews and questionnaires, this study provides objective tools for the assessment of psychological dimensions. PMID:25859212

Development of a Commercially Viable, Modular Autonomous Robotic Systems for Converting any Vehicle to Autonomous Control

NASA Technical Reports Server (NTRS)

Parish, David W.; Grabbe, Robert D.; Marzwell, Neville I.

1994-01-01

A Modular Autonomous Robotic System (MARS), consisting of a modular autonomous vehicle control system that can be retrofit on to any vehicle to convert it to autonomous control and support a modular payload for multiple applications is being developed. The MARS design is scalable, reconfigurable, and cost effective due to the use of modern open system architecture design methodologies, including serial control bus technology to simplify system wiring and enhance scalability. The design is augmented with modular, object oriented (C++) software implementing a hierarchy of five levels of control including teleoperated, continuous guidepath following, periodic guidepath following, absolute position autonomous navigation, and relative position autonomous navigation. The present effort is focused on producing a system that is commercially viable for routine autonomous patrolling of known, semistructured environments, like environmental monitoring of chemical and petroleum refineries, exterior physical security and surveillance, perimeter patrolling, and intrafacility transport applications.

The development of an autonomous rendezvous and docking simulation using rapid integration and prototyping technology

NASA Technical Reports Server (NTRS)

Shackelford, John H.; Saugen, John D.; Wurst, Michael J.; Adler, James

1991-01-01

A generic planar 3 degree of freedom simulation was developed that supports hardware in the loop simulations, guidance and control analysis, and can directly generate flight software. This simulation was developed in a small amount of time utilizing rapid prototyping techniques. The approach taken to develop this simulation tool, the benefits seen using this approach to development, and on-going efforts to improve and extend this capability are described. The simulation is composed of 3 major elements: (1) Docker dynamics model, (2) Dockee dynamics model, and (3) Docker Control System. The docker and dockee models are based on simple planar orbital dynamics equations using a spherical earth gravity model. The docker control system is based on a phase plane approach to error correction.

Robotic intelligence kernel

DOEpatents

Bruemmer, David J [Idaho Falls, ID

2009-11-17

A robot platform includes perceptors, locomotors, and a system controller. The system controller executes a robot intelligence kernel (RIK) that includes a multi-level architecture and a dynamic autonomy structure. The multi-level architecture includes a robot behavior level for defining robot behaviors, that incorporate robot attributes and a cognitive level for defining conduct modules that blend an adaptive interaction between predefined decision functions and the robot behaviors. The dynamic autonomy structure is configured for modifying a transaction capacity between an operator intervention and a robot initiative and may include multiple levels with at least a teleoperation mode configured to maximize the operator intervention and minimize the robot initiative and an autonomous mode configured to minimize the operator intervention and maximize the robot initiative. Within the RIK at least the cognitive level includes the dynamic autonomy structure.

Long-time uncertainty propagation using generalized polynomial chaos and flow map composition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luchtenburg, Dirk M., E-mail: dluchten@cooper.edu; Brunton, Steven L.; Rowley, Clarence W.

2014-10-01

We present an efficient and accurate method for long-time uncertainty propagation in dynamical systems. Uncertain initial conditions and parameters are both addressed. The method approximates the intermediate short-time flow maps by spectral polynomial bases, as in the generalized polynomial chaos (gPC) method, and uses flow map composition to construct the long-time flow map. In contrast to the gPC method, this approach has spectral error convergence for both short and long integration times. The short-time flow map is characterized by small stretching and folding of the associated trajectories and hence can be well represented by a relatively low-degree basis. The compositionmore » of these low-degree polynomial bases then accurately describes the uncertainty behavior for long integration times. The key to the method is that the degree of the resulting polynomial approximation increases exponentially in the number of time intervals, while the number of polynomial coefficients either remains constant (for an autonomous system) or increases linearly in the number of time intervals (for a non-autonomous system). The findings are illustrated on several numerical examples including a nonlinear ordinary differential equation (ODE) with an uncertain initial condition, a linear ODE with an uncertain model parameter, and a two-dimensional, non-autonomous double gyre flow.« less

Long-Term Simultaneous Localization and Mapping in Dynamic Environments

DTIC Science & Technology

2015-01-01

core competencies required for autonomous mobile robotics is the ability to use sensors to perceive the environment. From this noisy sensor data, the...and mapping (SLAM), is a prerequisite for almost all higher-level autonomous behavior in mobile robotics. By associating the robot???s sensory...distributed stochastic neighbor embedding x ABSTRACT One of the core competencies required for autonomous mobile robotics is the ability to use sensors

Cooperative Autonomous Observation of Volcanic Environments with sUAS

NASA Astrophysics Data System (ADS)

Ravela, S.

2015-12-01

The Cooperative Autonomous Observing System Project (CAOS) at the MIT Earth Signals and Systems Group has developed methodology and systems for dynamically mapping coherent fluids such as plumes using small unmanned aircraft systems (sUAS). In the CAOS approach, two classes of sUAS, one remote the other in-situ, implement a dynamic data-driven mapping system by closing the loop between Modeling, Estimation, Sampling, Planning and Control (MESPAC). The continually gathered measurements are assimilated to produce maps/analyses which also guide the sUAS network to adaptively resample the environment. Rather than scan the volume in fixed Eulerian or Lagrangian flight plans, the adaptive nature of the sampling process enables objectives for efficiency and resilience to be incorporated. Modeling includes realtime prediction using two types of reduced models, one based on nowcasting remote observations of plume tracer using scale-cascaded alignment, and another based on dynamically-deformable EOF/POD developed for coherent structures. Ensemble-based Information-theoretic machine learning approaches are used for the highly non-linear/non-Gaussian state/parameter estimation, and for planning. Control of the sUAS is based on model reference control coupled with hierarchical PID. MESPAC is implemented in part on a SkyCandy platform, and implements an airborne mesh that provides instantaneous situational awareness and redundant communication to an operating fleet. SkyCandy is deployed on Itzamna Aero's I9X/W UAS with low-cost sensors, and is currently being used to study the Popocatepetl volcano. Results suggest that operational communities can deploy low-cost sUAS to systematically monitor whilst optimizing for efficiency/maximizing resilience. The CAOS methodology is applicable to many other environments where coherent structures are present in the background. More information can be found at caos.mit.edu.

Why Computer-Based Systems Should be Autonomic

NASA Technical Reports Server (NTRS)

Sterritt, Roy; Hinchey, Mike

2005-01-01

The objective of this paper is to discuss why computer-based systems should be autonomic, where autonomicity implies self-managing, often conceptualized in terms of being self-configuring, self-healing, self-optimizing, self-protecting and self-aware. We look at motivations for autonomicity, examine how more and more systems are exhibiting autonomic behavior, and finally look at future directions.

Autonomous Preference-Aware Information Services Integration for High Response in Integrated Faded Information Field Systems

NASA Astrophysics Data System (ADS)

Lu, Xiaodong; Mori, Kinji

The market and users' requirements have been rapidly changing and diversified. Under these heterogeneous and dynamic situations, not only the system structure itself, but also the accessible information services would be changed constantly. To cope with the continuously changing conditions of service provision and utilization, Faded Information Field (FIF) has been proposed, which is a agent-based distributed information service system architecture. In the case of a mono-service request, the system is designed to improve users' access time and preserve load balancing through the information structure. However, with interdependent requests of multi-service increasing, adaptability and timeliness have to be assured by the system. In this paper, the relationship that exists among the correlated services and the users' preferences for separate and integrated services is clarified. Based on these factors, the autonomous preference-aware information services integration technology to provide one-stop service for users multi-service requests is proposed. As compared to the conventional system, we show that proposed technology is able to reduce the total access time.

Challenges in verification and validation of autonomous systems for space exploration

NASA Technical Reports Server (NTRS)

Brat, Guillaume; Jonsson, Ari

2005-01-01

Space exploration applications offer a unique opportunity for the development and deployment of autonomous systems, due to limited communications, large distances, and great expense of direct operation. At the same time, the risk and cost of space missions leads to reluctance to taking on new, complex and difficult-to-understand technology. A key issue in addressing these concerns is the validation of autonomous systems. In recent years, higher-level autonomous systems have been applied in space applications. In this presentation, we will highlight those autonomous systems, and discuss issues in validating these systems. We will then look to future demands on validating autonomous systems for space, identify promising technologies and open issues.

Generalized Synchronization in AN Array of Nonlinear Dynamic Systems with Applications to Chaotic Cnn

NASA Astrophysics Data System (ADS)

Min, Lequan; Chen, Guanrong

This paper establishes some generalized synchronization (GS) theorems for a coupled discrete array of difference systems (CDADS) and a coupled continuous array of differential systems (CCADS). These constructive theorems provide general representations of GS in CDADS and CCADS. Based on these theorems, one can design GS-driven CDADS and CCADS via appropriate (invertible) transformations. As applications, the results are applied to autonomous and nonautonomous coupled Chen cellular neural network (CNN) CDADS and CCADS, discrete bidirectional Lorenz CNN CDADS, nonautonomous bidirectional Chua CNN CCADS, and nonautonomously bidirectional Chen CNN CDADS and CCADS, respectively. Extensive numerical simulations show their complex dynamic behaviors. These theorems provide new means for understanding the GS phenomena of complex discrete and continuously differentiable networks.

Real-time, autonomous precise satellite orbit determination using the global positioning system

NASA Astrophysics Data System (ADS)

Goldstein, David Ben

2000-10-01

The desire for autonomously generated, rapidly available, and highly accurate satellite ephemeris is growing with the proliferation of constellations of satellites and the cost and overhead of ground tracking resources. Autonomous Orbit Determination (OD) may be done on the ground in a post-processing mode or in real-time on board a satellite and may be accomplished days, hours or immediately after observations are processed. The Global Positioning System (GPS) is now widely used as an alternative to ground tracking resources to supply observation data for satellite positioning and navigation. GPS is accurate, inexpensive, provides continuous coverage, and is an excellent choice for autonomous systems. In an effort to estimate precise satellite ephemeris in real-time on board a satellite, the Goddard Space Flight Center (GSFC) created the GPS Enhanced OD Experiment (GEODE) flight navigation software. This dissertation offers alternative methods and improvements to GEODE to increase on board autonomy and real-time total position accuracy and precision without increasing computational burden. First, GEODE is modified to include a Gravity Acceleration Approximation Function (GAAF) to replace the traditional spherical harmonic representation of the gravity field. Next, an ionospheric correction method called Differenced Range Versus Integrated Doppler (DRVID) is applied to correct for ionospheric errors in the GPS measurements used in GEODE. Then, Dynamic Model Compensation (DMC) is added to estimate unmodeled and/or mismodeled forces in the dynamic model and to provide an alternative process noise variance-covariance formulation. Finally, a Genetic Algorithm (GA) is implemented in the form of Genetic Model Compensation (GMC) to optimize DMC forcing noise parameters. Application of GAAF, DRVID and DMC improved GEODE's position estimates by 28.3% when applied to GPS/MET data collected in the presence of Selective Availability (SA), 17.5% when SA is removed from the GPS/MET data and 10.8% on SA free TOPEX data. Position estimates with RSS errors below I meter are now achieved using SA free TOPEX data. DRVID causes an increase in computational burden while GAAF and DMC reduce computational burden. The net effect of applying GAAF, DRVID and DMC is an improvement in GEODE's accuracy/precision without an increase in computational burden.

An Oceanographic Decision Support System for Scientific Field Experiments

NASA Astrophysics Data System (ADS)

Maughan, T.; Das, J.; McCann, M. P.; Rajan, K.

2011-12-01

Thom Maughan, Jnaneshwar Das, Mike McCann, Danelle Cline, Mike Godin, Fred Bahr, Kevin Gomes, Tom O'Reilly, Frederic Py, Monique Messie, John Ryan, Francisco Chavez, Jim Bellingham, Maria Fox, Kanna Rajan Monterey Bay Aquarium Research Institute Moss Lading, California, United States Many of the coastal ocean processes we wish to observe in order to characterize marine ecosystems have large spatial extant (tens of square km) and are dynamic moving kilometers in a day with biological processes spanning anywhere from minutes to days. Some like harmful algal blooms generate toxins which can significantly impact human health and coastal economies. In order to obtain a viable understanding of the biogeochemical processes which define their dynamics and ecology, it is necessary to persistently observe, track and sample within and near the dynamic fields using augmented methods of observation such as autonomous platforms like AUVs, gliders and surface craft. Field experiments to plan, execute and manage such multitude of assets are challenging. To alleviate this problem the autonomous systems group with its collaborators at MBARI and USC designed, built and fielded a prototype Oceanographic Decision Support System (ODSS) that provides situational awareness and a single portal to visualize and plan deployments for the large scale October 2010 CANON field program as well as a series of 2 week field programs in 2011. The field programs were conducted in Monterey Bay, a known 'red tide' incubator, and varied from as many as twenty autonomous platforms, four ships and 2 manned airplanes to coordinated AUV operations, drifters and a single ship. The ODSS web-based portal was used to assimilate information from a collection of sources at sea, including AUVs, moorings, radar data as well as remote sensing products generated by partner organizations to provide a synthesis of views useful to predict the movement of a chlorophyll patch in the confines of the northern Monterey Bay. The ODSS was used for automated shore-based control of mobile assets and was also used to compute safety bounds for operation of MBARI AUVs and provide projections of drifters advected [1,4] due to surface conditions. Scientist and operations teams use the ODSS during the daily planning meetings for situation awareness and real time access to data to support decisions on sampling strategies and platform logistics. References 1. J.Das, F. Py, T. Maughan, J Ryan , K. Rajan & G. Sukhatme, Simultaneous Tracking and Sampling of Dynamic Oceanographic Features with Autonomous Underwater Vehicles and Lagrangian Drifters, Accepted, Intnl. Symp. on Experimental Robotics (ISER), N. Delhi, India, Dec 2010. 2. S. Jiminez, F. Py & K. Rajan, Learning Identification Models for In-situ Sampling of Ocean features, Working notes of the RSS'10 Workshop on Active Learning for Robotics. Robotics Systems Sciences, Spain. 2010 3. Py, F. , Jiminez, S. , and Rajan, K. "Modeling dynamic coastal ocean features for in-situ identication and adaptive sampling", Journal of Atmospheric and Ocean Technology-Ocean(2010). Submitted, in Review. 4. J. Das, K. Rajan, S. Frolov, J. Ryan, F. Py, D. Caron & G. Sukhatme, Towards Marine Bloom Trajectory Prediction for AUV Mission Planning, ICRA, May 2010, Anchorage

Engineered cell-cell communication via DNA messaging

PubMed Central

2012-01-01

Background Evolution has selected for organisms that benefit from genetically encoded cell-cell communication. Engineers have begun to repurpose elements of natural communication systems to realize programmed pattern formation and coordinate other population-level behaviors. However, existing engineered systems rely on system-specific small molecules to send molecular messages among cells. Thus, the information transmission capacity of current engineered biological communication systems is physically limited by specific biomolecules that are capable of sending only a single message, typically “regulate transcription.” Results We have engineered a cell-cell communication platform using bacteriophage M13 gene products to autonomously package and deliver heterologous DNA messages of varying lengths and encoded functions. We demonstrate the decoupling of messages from a common communication channel via the autonomous transmission of various arbitrary genetic messages. Further, we increase the range of engineered DNA messaging across semisolid media by linking message transmission or receipt to active cellular chemotaxis. Conclusions We demonstrate decoupling of a communication channel from message transmission within engineered biological systems via the autonomous targeted transduction of user-specified heterologous DNA messages. We also demonstrate that bacteriophage M13 particle production and message transduction occurs among chemotactic bacteria. We use chemotaxis to improve the range of DNA messaging, increasing both transmission distance and communication bit rates relative to existing small molecule-based communication systems. We postulate that integration of different engineered cell-cell communication platforms will allow for more complex spatial programming of dynamic cellular consortia. PMID:22958599

Autonomous Satellite Operations Via Secure Virtual Mission Operations Center

NASA Technical Reports Server (NTRS)

Miller, Eric; Paulsen, Phillip E.; Pasciuto, Michael

2011-01-01

The science community is interested in improving their ability to respond to rapidly evolving, transient phenomena via autonomous rapid reconfiguration, which derives from the ability to assemble separate but collaborating sensors and data forecasting systems to meet a broad range of research and application needs. Current satellite systems typically require human intervention to respond to triggers from dissimilar sensor systems. Additionally, satellite ground services often need to be coordinated days or weeks in advance. Finally, the boundaries between the various sensor systems that make up such a Sensor Web are defined by such things as link delay and connectivity, data and error rate asymmetry, data reliability, quality of service provisions, and trust, complicating autonomous operations. Over the past ten years, researchers from the NASA Glenn Research Center (GRC), General Dynamics, Surrey Satellite Technology Limited (SSTL), Cisco, Universal Space Networks (USN), the U.S. Geological Survey (USGS), the Naval Research Laboratory, the DoD Operationally Responsive Space (ORS) Office, and others have worked collaboratively to develop a virtual mission operations capability. Called VMOC (Virtual Mission Operations Center), this new capability allows cross-system queuing of dissimilar mission unique systems through the use of a common security scheme and published application programming interfaces (APIs). Collaborative VMOC demonstrations over the last several years have supported the standardization of spacecraft to ground interfaces needed to reduce costs, maximize space effects to the user, and allow the generation of new tactics, techniques and procedures that lead to responsive space employment.

Using Model-Based Reasoning for Autonomous Instrument Operation - Lessons Learned From IMAGE/LENA

NASA Technical Reports Server (NTRS)

Johnson, Michael A.; Rilee, Michael L.; Truszkowski, Walt; Bailin, Sidney C.

2001-01-01

Model-based reasoning has been applied as an autonomous control strategy on the Low Energy Neutral Atom (LENA) instrument currently flying on board the Imager for Magnetosphere-to-Aurora Global Exploration (IMAGE) spacecraft. Explicit models of instrument subsystem responses have been constructed and are used to dynamically adapt the instrument to the spacecraft's environment. These functions are cast as part of a Virtual Principal Investigator (VPI) that autonomously monitors and controls the instrument. In the VPI's current implementation, LENA's command uplink volume has been decreased significantly from its previous volume; typically, no uplinks are required for operations. This work demonstrates that a model-based approach can be used to enhance science instrument effectiveness. The components of LENA are common in space science instrumentation, and lessons learned by modeling this system may be applied to other instruments. Future work involves the extension of these methods to cover more aspects of LENA operation and the generalization to other space science instrumentation.

Autonomous, agile micro-satellites and supporting technologies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Breitfeller, E; Dittman, M D; Gaughan, R J

1999-07-19

This paper updates the on-going effort at Lawrence Livermore National Laboratory to develop autonomous, agile micro-satellites (MicroSats). The objective of this development effort is to develop MicroSats weighing only a few tens of kilograms, that are able to autonomously perform precision maneuvers and can be used telerobotically in a variety of mission modes. The required capabilities include satellite rendezvous, inspection, proximity-operations, docking, and servicing. The MicroSat carries an integrated proximity-operations sensor-suite incorporating advanced avionics. A new self-pressurizing propulsion system utilizing a miniaturized pump and non-toxic mono-propellant hydrogen peroxide was successfully tested. This system can provide a nominal 25 kg MicroSatmore » with 200-300 m/s delta-v including a warm-gas attitude control system. The avionics is based on the latest PowerPC processor using a CompactPCI bus architecture, which is modular, high-performance and processor-independent. This leverages commercial-off-the-shelf (COTS) technologies and minimizes the effects of future changes in processors. The MicroSat software development environment uses the Vx-Works real-time operating system (RTOS) that provides a rapid development environment for integration of new software modules, allowing early integration and test. We will summarize results of recent integrated ground flight testing of our latest non-toxic pumped propulsion MicroSat testbed vehicle operated on our unique dynamic air-rail.« less

Synergetic computer and holonics - information dynamics of a semantic computer

NASA Astrophysics Data System (ADS)

Shimizu, H.; Yamaguchi, Y.

1987-12-01

The dynamics of semantic information in biosystem is studied based on holons, generators of mutual relations. Any biosystem has an internal world, a so-called "self", which has an intrinsic purpose rendering the system continuously alive and developed as much as possible against a fluctuating external world. External signals to the system through sensory organs are classified by the self into two basic categories, semantic information with some meaning and value for the purpose and inputs from background and noise sources. Due to this breaking of semantic symmetry, any input signals are transformed into a figure and background, respectively. As a typical example, the visual perception of vertebrates is studied. For such semantic transformation the external signal is first decomposed and converted into a number of elementary signs named "syntons" which are then transmitted into a sensory area of cortex corresponding to an image synthesizer. The synthesizer is a sort of autonomic parallel processor composed of autonomic units, "holons", which are characterized by many internal modes. Syntons are fed into the holons one by one. A set of the elementary meanings, the so-called "semons", provided to the synton are encoded in the internal modes of the holon; that is, each internal mode encodes a semon. A dynamic information theory for the transformation of external signals to semantic information is developed based on our model which we call holovision. Holovision is a dynamic model of visual perception that processes an autonomic ability to self-organize visual images. Autonomous oscillators are utilized as the line processors to encode line elements with specific orientations in their phases as semons. An information space is defined according to the assembly of holons; the spatial plane on which holons are arranged is a syntactic subspace while the internal modes of the holons span a semantic subspace in the orthogonal direction. In this information space, the image of a figure is self-organized - as a sort of spatiotemporal pattern - by autonomic coordinations of the holons that select relevant internal modes, accompanied with compression of irrelevant syntons that correspond to the background. Holons coded by a synton are relevantly connected by means of coherent relations, i.e., dynamic connections with time-coherence, in order to represent the image that varies in time depending on the instantaneous state of the external object. These connections depend on the internal modes that are cooperatively selectively selected by the holons. The image is regarded as a bridge between the external and internal world that has both external and internal consistency. The meaning of the image, i.e., transformed semantic information, is spontaneously transferred from semantic items that have a coherent relation with the image, and the external signal is perceived by the self through the image. We demonstrate that images are indeed self-organized in holovision in the previously described sense. Simulated processes of the creation of semantic information in holovision are shown to display typical features of the forgoing steps of information compression. Based on these results, we propose quantitative indices that represent the value of semantic information in the image processor as well as in the memory.

Autonomous vehicles: from paradigms to technology

NASA Astrophysics Data System (ADS)

Ionita, Silviu

2017-10-01

Mobility is a basic necessity of contemporary society and it is a key factor in global economic development. The basic requirements for the transport of people and goods are: safety and duration of travel, but also a number of additional criteria are very important: energy saving, pollution, passenger comfort. Due to advances in hardware and software, automation has penetrated massively in transport systems both on infrastructure and on vehicles, but man is still the key element in vehicle driving. However, the classic concept of ‘human-in-the-loop’ in terms of ‘hands on’ in driving the cars is competing aside from the self-driving startups working towards so-called ‘Level 4 autonomy’, which is defined as “a self-driving system that does not requires human intervention in most scenarios”. In this paper, a conceptual synthesis of the autonomous vehicle issue is made in connection with the artificial intelligence paradigm. It presents a classification of the tasks that take place during the driving of the vehicle and its modeling from the perspective of traditional control engineering and artificial intelligence. The issue of autonomous vehicle management is addressed on three levels: navigation, movement in traffic, respectively effective maneuver and vehicle dynamics control. Each level is then described in terms of specific tasks, such as: route selection, planning and reconfiguration, recognition of traffic signs and reaction to signaling and traffic events, as well as control of effective speed, distance and direction. The approach will lead to a better understanding of the way technology is moving when talking about autonomous cars, smart/intelligent cars or intelligent transport systems. Keywords: self-driving vehicle, artificial intelligence, deep learning, intelligent transport systems.

Various Attractors, Coexisting Attractors and Antimonotonicity in a Simple Fourth-Order Memristive Twin-T Oscillator

NASA Astrophysics Data System (ADS)

Zhou, Ling; Wang, Chunhua; Zhang, Xin; Yao, Wei

By replacing the resistor in a Twin-T network with a generalized flux-controlled memristor, this paper proposes a simple fourth-order memristive Twin-T oscillator. Rich dynamical behaviors can be observed in the dynamical system. The most striking feature is that this system has various periodic orbits and various chaotic attractors generated by adjusting parameter b. At the same time, coexisting attractors and antimonotonicity are also detected (especially, two full Feigenbaum remerging trees in series are observed in such autonomous chaotic systems). Their dynamical features are analyzed by phase portraits, Lyapunov exponents, bifurcation diagrams and basin of attraction. Moreover, hardware experiments on a breadboard are carried out. Experimental measurements are in accordance with the simulation results. Finally, a multi-channel random bit generator is designed for encryption applications. Numerical results illustrate the usefulness of the random bit generator.

Complex scenes and situations visualization in hierarchical learning algorithm with dynamic 3D NeoAxis engine

NASA Astrophysics Data System (ADS)

Graham, James; Ternovskiy, Igor V.

2013-06-01

We applied a two stage unsupervised hierarchical learning system to model complex dynamic surveillance and cyber space monitoring systems using a non-commercial version of the NeoAxis visualization software. The hierarchical scene learning and recognition approach is based on hierarchical expectation maximization, and was linked to a 3D graphics engine for validation of learning and classification results and understanding the human - autonomous system relationship. Scene recognition is performed by taking synthetically generated data and feeding it to a dynamic logic algorithm. The algorithm performs hierarchical recognition of the scene by first examining the features of the objects to determine which objects are present, and then determines the scene based on the objects present. This paper presents a framework within which low level data linked to higher-level visualization can provide support to a human operator and be evaluated in a detailed and systematic way.

Wind Turbine Contingency Control Through Generator De-Rating

NASA Technical Reports Server (NTRS)

Frost, Susan; Goebel, Kai; Balas, Mark

2013-01-01

Maximizing turbine up-time and reducing maintenance costs are key technology drivers for wind turbine operators. Components within wind turbines are subject to considerable stresses due to unpredictable environmental conditions resulting from rapidly changing local dynamics. In that context, systems health management has the aim to assess the state-of-health of components within a wind turbine, to estimate remaining life, and to aid in autonomous decision-making to minimize damage to the turbine. Advanced contingency control is one way to enable autonomous decision-making by providing the mechanism to enable safe and efficient turbine operation. The work reported herein explores the integration of condition monitoring of wind turbines with contingency control to balance the trade-offs between maintaining system health and energy capture. The contingency control involves de-rating the generator operating point to achieve reduced loads on the wind turbine. Results are demonstrated using a high fidelity simulator of a utility-scale wind turbine.

Autonomous Pointing Control of a Large Satellite Antenna Subject to Parametric Uncertainty

PubMed Central

Wu, Shunan; Liu, Yufei; Radice, Gianmarco; Tan, Shujun

2017-01-01

With the development of satellite mobile communications, large antennas are now widely used. The precise pointing of the antenna’s optical axis is essential for many space missions. This paper addresses the challenging problem of high-precision autonomous pointing control of a large satellite antenna. The pointing dynamics are firstly proposed. The proportional–derivative feedback and structural filter to perform pointing maneuvers and suppress antenna vibrations are then presented. An adaptive controller to estimate actual system frequencies in the presence of modal parameters uncertainty is proposed. In order to reduce periodic errors, the modified controllers, which include the proposed adaptive controller and an active disturbance rejection filter, are then developed. The system stability and robustness are analyzed and discussed in the frequency domain. Numerical results are finally provided, and the results have demonstrated that the proposed controllers have good autonomy and robustness. PMID:28287450

Overview of computational control research at UT Austin

NASA Technical Reports Server (NTRS)

Bong, Wie

1989-01-01

An overview of current research activities at UT Austin is presented to discuss certain technical issues in the following areas: (1) Computer-Aided Nonlinear Control Design: In this project, the describing function method is employed for the nonlinear control analysis and design of a flexible spacecraft equipped with pulse modulated reaction jets. INCA program has been enhanced to allow the numerical calculation of describing functions as well as the nonlinear limit cycle analysis capability in the frequency domain; (2) Robust Linear Quadratic Gaussian (LQG) Compensator Synthesis: Robust control design techniques and software tools are developed for flexible space structures with parameter uncertainty. In particular, an interactive, robust multivariable control design capability is being developed for INCA program; and (3) LQR-Based Autonomous Control System for the Space Station: In this project, real time implementation of LQR-based autonomous control system is investigated for the space station with time-varying inertias and with significant multibody dynamic interactions.

Generation and communication of dynamic maps using light projection

NASA Astrophysics Data System (ADS)

Busch, Steffen; Schlichting, Alexander; Brenner, Claus

2018-05-01

Many accidents are caused by miscommunication between traffic participants. Much research is being conducted in the area of car to car and car to infrastructure communication in order to eliminate this cause of accidents. How-ever, less attention is paid to the question how the behavior of a car can be communicated to pedestrians. Especially considering automated traffic, there is a lack of communication between cars and pedestrians. In this paper, we address the question how an autonomously driving car can inform pedestrians about its intentions. Especially in case of highly automated driving, making eye contact with a driver will give no clue about his or her intensions. We developed a prototype which continuously informs pedestrians about the intentions of the vehicle by projecting visual patterns onto the ground. Furthermore, the system communicates its interpretation of the observed situation to the pedestrians to warn them or to encourage them to perform a certain action. In order to communicate adaptively, the vehicle needs to develop an understanding of the dynamics of a city to know what to expect in certain situations and what speed is appropriate. To support this, we created a dynamic map, which estimates the number of pedestrians and cyclists in a certain area, which is then used to determine how `hazardous' the area is. This dynamic map is obtained from measurement data from many time instances, in contrast to the static car navigation maps, which are prevalent today. Apart from being used for communication purposes, the dynamic map can also influence the speed of a car, be it manually or autonomously driven. Adapting the speed in hazardous areas will avoid accidents where a car drives too fast, so that neither a human nor a computer-operated system would be able to stop in time.

Toward a Dynamically Reconfigurable Computing and Communication System for Small Spacecraft

NASA Technical Reports Server (NTRS)

Kifle, Muli; Andro, Monty; Tran, Quang K.; Fujikawa, Gene; Chu, Pong P.

2003-01-01

Future science missions will require the use of multiple spacecraft with multiple sensor nodes autonomously responding and adapting to a dynamically changing space environment. The acquisition of random scientific events will require rapidly changing network topologies, distributed processing power, and a dynamic resource management strategy. Optimum utilization and configuration of spacecraft communications and navigation resources will be critical in meeting the demand of these stringent mission requirements. There are two important trends to follow with respect to NASA's (National Aeronautics and Space Administration) future scientific missions: the use of multiple satellite systems and the development of an integrated space communications network. Reconfigurable computing and communication systems may enable versatile adaptation of a spacecraft system's resources by dynamic allocation of the processor hardware to perform new operations or to maintain functionality due to malfunctions or hardware faults. Advancements in FPGA (Field Programmable Gate Array) technology make it possible to incorporate major communication and network functionalities in FPGA chips and provide the basis for a dynamically reconfigurable communication system. Advantages of higher computation speeds and accuracy are envisioned with tremendous hardware flexibility to ensure maximum survivability of future science mission spacecraft. This paper discusses the requirements, enabling technologies, and challenges associated with dynamically reconfigurable space communications systems.

Distributed formation control of nonholonomic autonomous vehicle via RBF neural network

NASA Astrophysics Data System (ADS)

Yang, Shichun; Cao, Yaoguang; Peng, Zhaoxia; Wen, Guoguang; Guo, Konghui

2017-03-01

In this paper, RBF neural network consensus-based distributed control scheme is proposed for nonholonomic autonomous vehicles in a pre-defined formation along the specified reference trajectory. A variable transformation is first designed to convert the formation control problem into a state consensus problem. Then, the complete dynamics of the vehicles including inertia, Coriolis, friction model and unmodeled bounded disturbances are considered, which lead to the formation unstable when the distributed kinematic controllers are proposed based on the kinematics. RBF neural network torque controllers are derived to compensate for them. Some sufficient conditions are derived to accomplish the asymptotically stability of the systems based on algebraic graph theory, matrix theory, and Lyapunov theory. Finally, simulation examples illustrate the effectiveness of the proposed controllers.

Multiresolution motion planning for autonomous agents via wavelet-based cell decompositions.

PubMed

Cowlagi, Raghvendra V; Tsiotras, Panagiotis

2012-10-01

We present a path- and motion-planning scheme that is "multiresolution" both in the sense of representing the environment with high accuracy only locally and in the sense of addressing the vehicle kinematic and dynamic constraints only locally. The proposed scheme uses rectangular multiresolution cell decompositions, efficiently generated using the wavelet transform. The wavelet transform is widely used in signal and image processing, with emerging applications in autonomous sensing and perception systems. The proposed motion planner enables the simultaneous use of the wavelet transform in both the perception and in the motion-planning layers of vehicle autonomy, thus potentially reducing online computations. We rigorously prove the completeness of the proposed path-planning scheme, and we provide numerical simulation results to illustrate its efficacy.

Conditions for Fully Autonomous Anticipation

NASA Astrophysics Data System (ADS)

Collier, John

2006-06-01

Anticipation allows a system to adapt to conditions that have not yet come to be, either externally to the system or internally. Autonomous systems actively control the conditions of their own existence so as to increase their overall viability. This paper will first give minimal necessary and sufficient conditions for autonomous anticipation, followed by a taxonomy of autonomous anticipation. In more complex systems, there can be semi-autonomous subsystems that can anticipate and adapt on their own. Such subsystems can be integrated into a system's overall autonomy, typically with greater efficiency due to modularity and specialization of function. However, it is also possible that semi-autonomous subsystems can act against the viability of the overall system, and have their own functions that conflict with overall system functions.

Agent-based modeling in ecological economics.

PubMed

Heckbert, Scott; Baynes, Tim; Reeson, Andrew

2010-01-01

Interconnected social and environmental systems are the domain of ecological economics, and models can be used to explore feedbacks and adaptations inherent in these systems. Agent-based modeling (ABM) represents autonomous entities, each with dynamic behavior and heterogeneous characteristics. Agents interact with each other and their environment, resulting in emergent outcomes at the macroscale that can be used to quantitatively analyze complex systems. ABM is contributing to research questions in ecological economics in the areas of natural resource management and land-use change, urban systems modeling, market dynamics, changes in consumer attitudes, innovation, and diffusion of technology and management practices, commons dilemmas and self-governance, and psychological aspects to human decision making and behavior change. Frontiers for ABM research in ecological economics involve advancing the empirical calibration and validation of models through mixed methods, including surveys, interviews, participatory modeling, and, notably, experimental economics to test specific decision-making hypotheses. Linking ABM with other modeling techniques at the level of emergent properties will further advance efforts to understand dynamics of social-environmental systems.

Towards A Theory of Autonomous Reconstitution of Compromised Cyber-Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramuhalli, Pradeep; Halappanavar, Mahantesh; Coble, Jamie B.

The ability to maintain mission-critical operations in cyber-systems in the face of disruptions is critical. Faults in cyber systems can come from accidental sources (e.g., natural failure of a component) or deliberate sources (e.g., an intelligent adversary). Natural and intentional manipulation of data, computing, or coordination are the most impactful ways that an attacker can prevent an infrastructure from realizing its mission goals. Under these conditions, the ability to reconstitute critical infrastructure becomes important. Specifically, the question is: Given an intelligent adversary, how can cyber systems respond to keep critical infrastructure operational? In cyber systems, the distributed nature of themore » system poses serious difficulties in maintaining operations, in part due to the fact that a centralized command and control apparatus is unlikely to provide a robust framework for resilience. Resilience in cyber-systems, in general, has several components, and requires the ability to anticipate and withstand attacks or faults, as well as recover from faults and evolve the system to improve future resilience. The recovery effort (and any subsequent evolution) may require significant reconfiguration of the system (at all levels – hardware, software, services, permissions, etc.) if the system is to be made resilient to further attack or faults. This is especially important in the case of ongoing attacks, where reconfiguration decisions must be taken with care to avoid further compromising the system while maintaining continuity of operations. Collectively, we will label this recovery and evolution process as “reconstitution”. Currently, reconstitution is performed manually, generally after-the-fact, and usually consists of either standing up redundant systems, check-points (rolling back the configuration to a “clean” state), or re-creating the system using “gold-standard” copies. For enterprise systems, such reconstitution may be performed either directly on hardware, or using virtual machines. A significant challenge within this context is the ability to verify that the reconstitution is performed in a manner that renders the cyber-system resilient to ongoing and future attacks or faults. Fundamentally, the need is to determine optimal configuration of the cyber system when a fault is determined to be present. While existing theories for fault tolerance (for example, Byzantine fault tolerance) can guarantee resilience under certain conditions, in practice, these theories can break down in the face of an intelligent adversary. Further, it is difficult, in a dynamically evolving environment, to determine whether the necessary conditions for resilience have been met, resulting in difficulties in achieving resilient operation. In addition, existing theories do not sufficiently take into account the cost for attack and defense (the adversary is generally assumed to have infinite resources and time), hierarchy of importance (all network resources are assumed to be equally important), and the dynamic nature of some attacks (i.e., as the attack evolves, can resilience be maintained?). Alternative approaches to resilience based on a centralized command and control structure suffer from a single-point-failure. This paper presents preliminary research towards concepts for effective autonomous reconstitution of compromised cyber systems. We describe a mathematical framework as a first step towards a theoretical basis for autonomous reconstitution in dynamic cyber-system environments. We then propose formulating autonomous reconstitution as an optimization problem and describe some of the challenges associated with this formulation. This is followed by a brief discussion on potential solutions to these challenges.« less

The Joint Tactical Aerial Resupply Vehicle Impact on Sustainment Operations

DTIC Science & Technology

2017-06-09

Artificial Intelligence , Sustainment Operations, Rifle Company, Autonomous Aerial Resupply, Joint Tactical Autonomous Aerial Resupply System 16...Integrations and Development System AI Artificial Intelligence ARCIC Army Capabilities Integration Center ARDEC Armament Research, Development and...semi- autonomous systems, and fully autonomous systems. Autonomy of machines depends on sophisticated software, including Artificial Intelligence

Designing an architectural style for dynamic medical Cross-Organizational Workflow management system: an approach based on agents and web services.

PubMed

Bouzguenda, Lotfi; Turki, Manel

2014-04-01

This paper shows how the combined use of agent and web services technologies can help to design an architectural style for dynamic medical Cross-Organizational Workflow (COW) management system. Medical COW aims at supporting the collaboration between several autonomous and possibly heterogeneous medical processes, distributed over different organizations (Hospitals, Clinic or laboratories). Dynamic medical COW refers to occasional cooperation between these health organizations, free of structural constraints, where the medical partners involved and their number are not pre-defined. More precisely, this paper proposes a new architecture style based on agents and web services technologies to deal with two key coordination issues of dynamic COW: medical partners finding and negotiation between them. It also proposes how the proposed architecture for dynamic medical COW management system can connect to a multi-agent system coupling the Clinical Decision Support System (CDSS) with Computerized Prescriber Order Entry (CPOE). The idea is to assist the health professionals such as doctors, nurses and pharmacists with decision making tasks, as determining diagnosis or patient data analysis without stopping their clinical processes in order to act in a coherent way and to give care to the patient.

Distributed Energy Systems Integration and Demand Optimization for Autonomous Operations and Electric Grid Transactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghatikar, Girish; Mashayekh, Salman; Stadler, Michael

Distributed power systems in the U.S. and globally are evolving to provide reliable and clean energy to consumers. In California, existing regulations require significant increases in renewable generation, as well as identification of customer-side distributed energy resources (DER) controls, communication technologies, and standards for interconnection with the electric grid systems. As DER deployment expands, customer-side DER control and optimization will be critical for system flexibility and demand response (DR) participation, which improves the economic viability of DER systems. Current DER systems integration and communication challenges include leveraging the existing DER and DR technology and systems infrastructure, and enabling optimized cost,more » energy and carbon choices for customers to deploy interoperable grid transactions and renewable energy systems at scale. Our paper presents a cost-effective solution to these challenges by exploring communication technologies and information models for DER system integration and interoperability. This system uses open standards and optimization models for resource planning based on dynamic-pricing notifications and autonomous operations within various domains of the smart grid energy system. It identifies architectures and customer engagement strategies in dynamic DR pricing transactions to generate feedback information models for load flexibility, load profiles, and participation schedules. The models are tested at a real site in California—Fort Hunter Liggett (FHL). Furthermore, our results for FHL show that the model fits within the existing and new DR business models and networked systems for transactive energy concepts. Integrated energy systems, communication networks, and modeling tools that coordinate supply-side networks and DER will enable electric grid system operators to use DER for grid transactions in an integrated system.« less

Autonomic Function in Infancy.

ERIC Educational Resources Information Center

Fox, Nathan A.; Fitzgerald, Hiram E.

1990-01-01

Reviews research that uses autonomic responses of human infants as dependent measures. Focuses on the history of research on the autonomic nervous system, measurement issues, and autonomic correlates of infant behavior and systems. (RJC)

Methods of determining complete sensor requirements for autonomous mobility

NASA Technical Reports Server (NTRS)

Curtis, Steven A. (Inventor)

2012-01-01

A method of determining complete sensor requirements for autonomous mobility of an autonomous system includes computing a time variation of each behavior of a set of behaviors of the autonomous system, determining mobility sensitivity to each behavior of the autonomous system, and computing a change in mobility based upon the mobility sensitivity to each behavior and the time variation of each behavior. The method further includes determining the complete sensor requirements of the autonomous system through analysis of the relative magnitude of the change in mobility, the mobility sensitivity to each behavior, and the time variation of each behavior, wherein the relative magnitude of the change in mobility, the mobility sensitivity to each behavior, and the time variation of each behavior are characteristic of the stability of the autonomous system.

A SINS/SRS/GNS Autonomous Integrated Navigation System Based on Spectral Redshift Velocity Measurements.

PubMed

Wei, Wenhui; Gao, Zhaohui; Gao, Shesheng; Jia, Ke

2018-04-09

In order to meet the requirements of autonomy and reliability for the navigation system, combined with the method of measuring speed by using the spectral redshift information of the natural celestial bodies, a new scheme, consisting of Strapdown Inertial Navigation System (SINS)/Spectral Redshift (SRS)/Geomagnetic Navigation System (GNS), is designed for autonomous integrated navigation systems. The principle of this SINS/SRS/GNS autonomous integrated navigation system is explored, and the corresponding mathematical model is established. Furthermore, a robust adaptive central difference particle filtering algorithm is proposed for this autonomous integrated navigation system. The simulation experiments are conducted and the results show that the designed SINS/SRS/GNS autonomous integrated navigation system possesses good autonomy, strong robustness and high reliability, thus providing a new solution for autonomous navigation technology.

Autonomous undulatory serpentine locomotion utilizing body dynamics of a fluidic soft robot.

PubMed

Onal, Cagdas D; Rus, Daniela

2013-06-01

Soft robotics offers the unique promise of creating inherently safe and adaptive systems. These systems bring man-made machines closer to the natural capabilities of biological systems. An important requirement to enable self-contained soft mobile robots is an on-board power source. In this paper, we present an approach to create a bio-inspired soft robotic snake that can undulate in a similar way to its biological counterpart using pressure for actuation power, without human intervention. With this approach, we develop an autonomous soft snake robot with on-board actuation, power, computation and control capabilities. The robot consists of four bidirectional fluidic elastomer actuators in series to create a traveling curvature wave from head to tail along its body. Passive wheels between segments generate the necessary frictional anisotropy for forward locomotion. It takes 14 h to build the soft robotic snake, which can attain an average locomotion speed of 19 mm s(-1).

Design of a biochemical circuit motif for learning linear functions

PubMed Central

Lakin, Matthew R.; Minnich, Amanda; Lane, Terran; Stefanovic, Darko

2014-01-01

Learning and adaptive behaviour are fundamental biological processes. A key goal in the field of bioengineering is to develop biochemical circuit architectures with the ability to adapt to dynamic chemical environments. Here, we present a novel design for a biomolecular circuit capable of supervised learning of linear functions, using a model based on chemical reactions catalysed by DNAzymes. To achieve this, we propose a novel mechanism of maintaining and modifying internal state in biochemical systems, thereby advancing the state of the art in biomolecular circuit architecture. We use simulations to demonstrate that the circuit is capable of learning behaviour and assess its asymptotic learning performance, scalability and robustness to noise. Such circuits show great potential for building autonomous in vivo nanomedical devices. While such a biochemical system can tell us a great deal about the fundamentals of learning in living systems and may have broad applications in biomedicine (e.g. autonomous and adaptive drugs), it also offers some intriguing challenges and surprising behaviours from a machine learning perspective. PMID:25401175

Design of a biochemical circuit motif for learning linear functions.

PubMed

Lakin, Matthew R; Minnich, Amanda; Lane, Terran; Stefanovic, Darko

2014-12-06

Learning and adaptive behaviour are fundamental biological processes. A key goal in the field of bioengineering is to develop biochemical circuit architectures with the ability to adapt to dynamic chemical environments. Here, we present a novel design for a biomolecular circuit capable of supervised learning of linear functions, using a model based on chemical reactions catalysed by DNAzymes. To achieve this, we propose a novel mechanism of maintaining and modifying internal state in biochemical systems, thereby advancing the state of the art in biomolecular circuit architecture. We use simulations to demonstrate that the circuit is capable of learning behaviour and assess its asymptotic learning performance, scalability and robustness to noise. Such circuits show great potential for building autonomous in vivo nanomedical devices. While such a biochemical system can tell us a great deal about the fundamentals of learning in living systems and may have broad applications in biomedicine (e.g. autonomous and adaptive drugs), it also offers some intriguing challenges and surprising behaviours from a machine learning perspective.

Optimal control of coupled parabolic-hyperbolic non-autonomous PDEs: infinite-dimensional state-space approach

NASA Astrophysics Data System (ADS)

Aksikas, I.; Moghadam, A. Alizadeh; Forbes, J. F.

2018-04-01

This paper deals with the design of an optimal state-feedback linear-quadratic (LQ) controller for a system of coupled parabolic-hypebolic non-autonomous partial differential equations (PDEs). The infinite-dimensional state space representation and the corresponding operator Riccati differential equation are used to solve the control problem. Dynamical properties of the coupled system of interest are analysed to guarantee the existence and uniqueness of the solution of the LQ-optimal control problem and also to guarantee the exponential stability of the closed-loop system. Thanks to the eigenvalues and eigenfunctions of the parabolic operator and also the fact that the hyperbolic-associated operator Riccati differential equation can be converted to a scalar Riccati PDE, an algorithm to solve the LQ control problem has been presented. The results are applied to a non-isothermal packed-bed catalytic reactor. The LQ optimal controller designed in the early portion of the paper is implemented for the original non-linear model. Numerical simulations are performed to show the controller performances.

An Autonomous Glider Network for the Monterey Bay Predictive Skill Experiment / AOSN-II

DTIC Science & Technology

2006-12-13

distributed measurements (Figure 1) of temperature and salinity, vertically-averaged velocity, chlorophyll fluorescence , optical backscatter, and PAR. We... Clarence Rowley, and Jerrold Marsden N000140210826 Underwater Glider Dynamics and Control Leonard (PI) N00014-02-1-0861 Autonomous Ocean Sampling

An Architecture for Autonomic Web Service Process Planning

NASA Astrophysics Data System (ADS)

Moore, Colm; Xue Wang, Ming; Pahl, Claus

Web service composition is a technology that has received considerable attention in the last number of years. Languages and tools to aid in the process of creating composite Web services have been received specific attention. Web service composition is the process of linking single Web services together in order to accomplish more complex tasks. One area of Web service composition that has not received as much attention is the area of dynamic error handling and re-planning, enabling autonomic composition. Given a repository of service descriptions and a task to complete, it is possible for AI planners to automatically create a plan that will achieve this goal. If however a service in the plan is unavailable or erroneous the plan will fail. Motivated by this problem, this paper suggests autonomous re-planning as a means to overcome dynamic problems. Our solution involves automatically recovering from faults and creating a context-dependent alternate plan. We present an architecture that serves as a basis for the central activities autonomous composition, monitoring and fault handling.

Robust Planning for Autonomous Navigation of Mobile Robots in Unstructured, Dynamic Environments: An LDRD Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

EISLER, G. RICHARD

This report summarizes the analytical and experimental efforts for the Laboratory Directed Research and Development (LDRD) project entitled ''Robust Planning for Autonomous Navigation of Mobile Robots In Unstructured, Dynamic Environments (AutoNav)''. The project goal was to develop an algorithmic-driven, multi-spectral approach to point-to-point navigation characterized by: segmented on-board trajectory planning, self-contained operation without human support for mission duration, and the development of appropriate sensors and algorithms to navigate unattended. The project was partially successful in achieving gains in sensing, path planning, navigation, and guidance. One of three experimental platforms, the Minimalist Autonomous Testbed, used a repetitive sense-and-re-plan combination to demonstratemore » the majority of elements necessary for autonomous navigation. However, a critical goal for overall success in arbitrary terrain, that of developing a sensor that is able to distinguish true obstacles that need to be avoided as a function of vehicle scale, still needs substantial research to bring to fruition.« less

Assured Human-Autonomy Interaction through Machine Self-Confidence

NASA Astrophysics Data System (ADS)

Aitken, Matthew

Autonomous systems employ many layers of approximations in order to operate in increasingly uncertain and unstructured environments. The complexity of these systems makes it hard for a user to understand the systems capabilities, especially if the user is not an expert. However, if autonomous systems are to be used efficiently, their users must trust them appropriately. This purpose of this work is to implement and assess an 'assurance' that an autonomous system can provide to the user to elicit appropriate trust. Specifically, the autonomous system's perception of its own capabilities is reported to the user as the self-confidence assurance. The self-confidence assurance should allow the user to more quickly and accurately assess the autonomous system's capabilities, generating appropriate trust in the autonomous system. First, this research defines self-confidence and discusses what the self-confidence assurance is attempting to communicate to the user. Then it provides a framework for computing the autonomous system's self-confidence as a function of self-confidence factors which correspond to individual elements in the autonomous system's process. In order to explore this idea, self-confidence is implemented on an autonomous system that uses a mixed observability Markov decision process model to solve a pursuit-evasion problem on a road network. The implementation of a factor assessing the goodness of the autonomy's expected performance is focused on in particular. This work highlights some of the issues and considerations in the design of appropriate metrics for the self-confidence factors, and provides the basis for future research for computing self-confidence in autonomous systems.

Brain correlates of autonomic modulation: combining heart rate variability with fMRI.

PubMed

Napadow, Vitaly; Dhond, Rupali; Conti, Giulia; Makris, Nikos; Brown, Emery N; Barbieri, Riccardo

2008-08-01

The central autonomic network (CAN) has been described in animal models but has been difficult to elucidate in humans. Potential confounds include physiological noise artifacts affecting brainstem neuroimaging data, and difficulty in deriving non-invasive continuous assessments of autonomic modulation. We have developed and implemented a new method which relates cardiac-gated fMRI timeseries with continuous-time heart rate variability (HRV) to estimate central autonomic processing. As many autonomic structures of interest are in brain regions strongly affected by cardiogenic pulsatility, we chose to cardiac-gate our fMRI acquisition to increase sensitivity. Cardiac-gating introduces T1-variability, which was corrected by transforming fMRI data to a fixed TR using a previously published method [Guimaraes, A.R., Melcher, J.R., et al., 1998. Imaging subcortical auditory activity in humans. Hum. Brain Mapp. 6(1), 33-41]. The electrocardiogram was analyzed with a novel point process adaptive-filter algorithm for computation of the high-frequency (HF) index, reflecting the time-varying dynamics of efferent cardiovagal modulation. Central command of cardiovagal outflow was inferred by using the resample HF timeseries as a regressor to the fMRI data. A grip task was used to perturb the autonomic nervous system. Our combined HRV-fMRI approach demonstrated HF correlation with fMRI activity in the hypothalamus, cerebellum, parabrachial nucleus/locus ceruleus, periaqueductal gray, amygdala, hippocampus, thalamus, and dorsomedial/dorsolateral prefrontal, posterior insular, and middle temporal cortices. While some regions consistent with central cardiovagal control in animal models gave corroborative evidence for our methodology, other mostly higher cortical or limbic-related brain regions may be unique to humans. Our approach should be optimized and applied to study the human brain correlates of autonomic modulation for various stimuli in both physiological and pathological states.

Analysis and design of a capsule landing system and surface vehicle control system for Mars exploration

NASA Technical Reports Server (NTRS)

Gisser, D. G.; Frederick, D. K.; Lashmet, P. K.; Sandor, G. N.; Shen, C. N.; Yerazunis, S. Y.

1975-01-01

Problems related to an unmanned exploration of the planet Mars by means of an autonomous roving planetary vehicle are investigated. These problems include: design, construction and evaluation of the vehicle itself and its control and operating systems. More specifically, vehicle configuration, dynamics, control, propulsion, hazard detection systems, terrain sensing and modelling, obstacle detection concepts, path selection, decision-making systems, and chemical analyses of samples are studied. Emphasis is placed on development of a vehicle capable of gathering specimens and data for an Augmented Viking Mission or to provide the basis for a Sample Return Mission.

Adaptive integral feedback controller for pitch and yaw channels of an AUV with actuator saturations.

PubMed

Sarhadi, Pouria; Noei, Abolfazl Ranjbar; Khosravi, Alireza

2016-11-01

Input saturations and uncertain dynamics are among the practical challenges in control of autonomous vehicles. Adaptive control is known as a proper method to deal with the uncertain dynamics of these systems. Therefore, incorporating the ability to confront with input saturation in adaptive controllers can be valuable. In this paper, an adaptive autopilot is presented for the pitch and yaw channels of an autonomous underwater vehicle (AUV) in the presence of input saturations. This will be performed by combination of a model reference adaptive control (MRAC) with integral state feedback with a modern anti-windup (AW) compensator. MRAC with integral state feedback is commonly used in autonomous vehicles. However, some proper modifications need to be taken into account in order to cope with the saturation problem. To this end, a Riccati-based anti-windup (AW) compensator is employed. The presented technique is applied to the non-linear six degrees of freedom (DOF) model of an AUV and the obtained results are compared with that of its baseline method. Several simulation scenarios are executed in the pitch and yaw channels to evaluate the controller performance. Moreover, effectiveness of proposed adaptive controller is comprehensively investigated by implementing Monte Carlo simulations. The obtained results verify the performance of proposed method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

The Autonomous Sciencecraft and applications to future science missions

NASA Astrophysics Data System (ADS)

Chien, S.

2006-05-01

The Autonomous Sciencecraft Software has operated the Earth Observing One (EO-1) Mission for over 5000 science observations [Chien et al. 2005a]. This software enables onboard analysis of data to drive: 1. production of rapid alerts summary products, 2. data editing, and 3. to inform subsequent observations. This methodology has been applied to more effectively study Volcano, Flooding, and Cryosphere processes on Earth. In this talk we discuss how this software enables new paradigms for science missions and discuss the types of science phenomena that can now be more readily studied (e.g. dynamic investigations, large scale searches for specific events). We also describe a range of Earth, Solar, and Space science applications under concept study for onboard autonomy. Finally, we describe ongoing work to link EO-1 with other spacecraft and in-situ sensor networks to enable a sensorweb for monitoring dynamic science events [Chien et al. 2005b]. S. Chien, R. Sherwood, D. Tran, B. Cichy, G. Rabideau, R. Castano, A. Davies, D. Mandl, S. Frye, B. Trout, S. Shulman, D. Boyer, "Using Autonomy Flight Software to Improve Science Return on Earth Observing One, Journal of Aerospace Computing, Information, & Communication, April 2005, AIAA. S. Chien, B. Cichy, A. Davies, D. Tran, G. Rabideau, R. Castano, R. Sherwood, D. Mandl, S. Frye, S. Shulman, J. Jones, S. Grosvenor, "An Autonomous Earth Observing Sensorweb," IEEE Intelligent Systems, May-June 2005, pp. 16- 24.

Prediction of atrial fibrillation recurrence after cardioversion-interaction analysis of cardiac autonomic regulation.

PubMed

Seeck, A; Rademacher, W; Fischer, C; Haueisen, J; Surber, R; Voss, A

2013-03-01

Today atrial fibrillation (AF) is the most common cardiac arrhythmia in clinical practice accounting for approximately one third of hospitalizations and accompanied with a 5 fold increased risk for ischemic stroke and a 1.5 fold increased mortality risk. The role of the cardiac regulation system in AF recurrence after electrical cardioversion (CV) is still unclear. The aim of this study was to investigate the autonomic regulation by analyzing the interaction between heart rate and blood pressure using novel methods of nonlinear interaction dynamics, namely joint symbolic dynamics (JSD) and segmented Poincaré plot analysis (SPPA). For the first time, we applied SPPA to analyze the interaction between two time series. Introducing a parameter set of two indices, one derived from JSD and one from SPPA, the linear discriminant function analysis revealed an overall accuracy of 89% (sensitivity 91.7%, specificity 86.7%) for the classification between patients with stable sinus rhythm (group SR, n = 15) and with AF recurrence (group REZ, n = 12). This study proves that the assessment of the autonomic regulation by analyzing the coupling of heart rate and systolic blood pressure provides a potential tool for the prediction of AF recurrence after CV and could aid in the adjustment of therapeutic options for patients with AF. Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.

Systems, methods and apparatus for quiesence of autonomic systems with self action

NASA Technical Reports Server (NTRS)

Hinchey, Michael G. (Inventor); Sterritt, Roy (Inventor)

2011-01-01

Systems, methods and apparatus are provided in which an autonomic unit or element is quiesced. A quiesce component of an autonomic unit can cause the autonomic unit to self-destruct if a stay-alive reprieve signal is not received after a predetermined time.

New Meanings of Thin-Skinned: The Contrasting Attentional Profiles of Typical 12-Month-Olds Who Show High, and Low, Stress Reactivity

ERIC Educational Resources Information Center

Wass, Sam V.; de Barbaro, Kaya; Clackson, Kaili; Leong, Victoria

2018-01-01

Previous research is inconsistent as to whether a more labile (faster-changing) autonomic system confers performance advantages, or disadvantages, in infants and children. To examine this, we presented a stimulus battery consisting of mixed static and dynamic viewing materials to a cohort of 63 typical 12-month-old infants. While viewing the…

Biology-Inspired Autonomous Control

DTIC Science & Technology

2011-08-31

from load sensing in a turbulent flow field with high levels of plant uncertainty and optical feedback latency. The results of this paper suggest... Mimicry of biological systems, in the form of precise mathematical or physical dynamical modeling, is yielding impressive insight into the underlying...processing and plants , the aerospace industry has been slow to accept adaptive control. In the past decade however, newer methods for design of adaptive

Expert systems for automated maintenance of a Mars oxygen production system

NASA Astrophysics Data System (ADS)

Huang, Jen-Kuang; Ho, Ming-Tsang; Ash, Robert L.

1992-08-01

Application of expert system concepts to a breadboard Mars oxygen processor unit have been studied and tested. The research was directed toward developing the methodology required to enable autonomous operation and control of these simple chemical processors at Mars. Failure detection and isolation was the key area of concern, and schemes using forward chaining, backward chaining, knowledge-based expert systems, and rule-based expert systems were examined. Tests and simulations were conducted that investigated self-health checkout, emergency shutdown, and fault detection, in addition to normal control activities. A dynamic system model was developed using the Bond-Graph technique. The dynamic model agreed well with tests involving sudden reductions in throughput. However, nonlinear effects were observed during tests that incorporated step function increases in flow variables. Computer simulations and experiments have demonstrated the feasibility of expert systems utilizing rule-based diagnosis and decision-making algorithms.

Flocking algorithm for autonomous flying robots.

PubMed

Virágh, Csaba; Vásárhelyi, Gábor; Tarcai, Norbert; Szörényi, Tamás; Somorjai, Gergő; Nepusz, Tamás; Vicsek, Tamás

2014-06-01

Animal swarms displaying a variety of typical flocking patterns would not exist without the underlying safe, optimal and stable dynamics of the individuals. The emergence of these universal patterns can be efficiently reconstructed with agent-based models. If we want to reproduce these patterns with artificial systems, such as autonomous aerial robots, agent-based models can also be used in their control algorithms. However, finding the proper algorithms and thus understanding the essential characteristics of the emergent collective behaviour requires thorough and realistic modeling of the robot and also the environment. In this paper, we first present an abstract mathematical model of an autonomous flying robot. The model takes into account several realistic features, such as time delay and locality of communication, inaccuracy of the on-board sensors and inertial effects. We present two decentralized control algorithms. One is based on a simple self-propelled flocking model of animal collective motion, the other is a collective target tracking algorithm. Both algorithms contain a viscous friction-like term, which aligns the velocities of neighbouring agents parallel to each other. We show that this term can be essential for reducing the inherent instabilities of such a noisy and delayed realistic system. We discuss simulation results on the stability of the control algorithms, and perform real experiments to show the applicability of the algorithms on a group of autonomous quadcopters. In our case, bio-inspiration works in two ways. On the one hand, the whole idea of trying to build and control a swarm of robots comes from the observation that birds tend to flock to optimize their behaviour as a group. On the other hand, by using a realistic simulation framework and studying the group behaviour of autonomous robots we can learn about the major factors influencing the flight of bird flocks.

Autonomic Computing for Spacecraft Ground Systems

NASA Technical Reports Server (NTRS)

Li, Zhenping; Savkli, Cetin; Jones, Lori

2007-01-01

Autonomic computing for spacecraft ground systems increases the system reliability and reduces the cost of spacecraft operations and software maintenance. In this paper, we present an autonomic computing solution for spacecraft ground systems at NASA Goddard Space Flight Center (GSFC), which consists of an open standard for a message oriented architecture referred to as the GMSEC architecture (Goddard Mission Services Evolution Center), and an autonomic computing tool, the Criteria Action Table (CAT). This solution has been used in many upgraded ground systems for NASA 's missions, and provides a framework for developing solutions with higher autonomic maturity.

From Here to Autonomicity: Self-Managing Agents and the Biological Metaphors that Inspire Them

NASA Technical Reports Server (NTRS)

Sterritt, Roy; Hinchey, Mike

2005-01-01

We seek inspiration for self-managing systems from (obviously, pre-existing) biological mechanisms. Autonomic Computing (AC), a self-managing systems initiative based on the biological metaphor of the autonomic nervous system, is increasingly gaining momentum as the way forward for integrating and designing reliable systems, while agent technologies have been identified as a key enabler for engineering autonomicity in systems. This paper looks at other biological metaphors such as reflex and healing, heart- beat monitors, pulse monitors and apoptosis for assisting in the realization of autonomicity.

Sensing, Control, and System Integration for Autonomous Vehicles: A Series of Challenges

NASA Astrophysics Data System (ADS)

Özgüner, Ümit; Redmill, Keith

One of the important examples of mechatronic systems can be found in autonomous ground vehicles. Autonomous ground vehicles provide a series of challenges in sensing, control and system integration. In this paper we consider off-road autonomous vehicles, automated highway systems and urban autonomous driving and indicate the unifying aspects. We specifically consider our own experience during the last twelve years in various demonstrations and challenges in attempting to identify unifying themes. Such unifying themes can be observed in basic hierarchies, hybrid system control approaches and sensor fusion techniques.

Autonomous docking ground demonstration (category 3)

NASA Technical Reports Server (NTRS)

Lamkin, Steve L.; Eick, Richard E.; Baxter, James M.; Boyd, M. G.; Clark, Fred D.; Lee, Thomas Q.; Othon, L. T.; Prather, Joseph L.; Spehar, Peter T.; Teders, Rebecca J.

1991-01-01

The NASA Johnson Space Center (JSC) is involved in the development of an autonomous docking ground demonstration. The demonstration combines the technologies, expertise and facilities of the JSC Tracking and Communications Division (EE), Structures and Mechanics Division (ES), and the Navigation, Guidance and Control Division (EG) and their supporting contractors. The autonomous docking ground demonstration is an evaluation of the capabilities of the laser sensor system to support the docking phase (12ft to contact) when operated in conjunction with the Guidance, Navigation and Control Software. The docking mechanism being used was developed for the Apollo Soyuz Test Program. This demonstration will be conducted using the Six-Degrees of Freedom (6-DOF) Dynamic Test System (DTS). The DTS environment simulates the Space Station Freedom as the stationary or target vehicle and the Orbiter as the active or chase vehicle. For this demonstration the laser sensor will be mounted on the target vehicle and the retroreflectors on the chase vehicle. This arrangement was used to prevent potential damage to the laser. The sensor system. GN&C and 6-DOF DTS will be operated closed-loop. Initial condition to simulate vehicle misalignments, translational and rotational, will be introduced within the constraints of the systems involved. Detailed description of each of the demonstration components (e.g., Sensor System, GN&C, 6-DOF DTS and supporting computer configuration) including their capabilities and limitations will be discussed. A demonstration architecture drawing and photographs of the test configuration will be presented.

Autonomous docking ground demonstration (category 3)

NASA Astrophysics Data System (ADS)

Lamkin, Steve L.; Eick, Richard E.; Baxter, James M.; Boyd, M. G.; Clark, Fred D.; Lee, Thomas Q.; Othon, L. T.; Prather, Joseph L.; Spehar, Peter T.; Teders, Rebecca J.

The NASA Johnson Space Center (JSC) is involved in the development of an autonomous docking ground demonstration. The demonstration combines the technologies, expertise and facilities of the JSC Tracking and Communications Division (EE), Structures and Mechanics Division (ES), and the Navigation, Guidance and Control Division (EG) and their supporting contractors. The autonomous docking ground demonstration is an evaluation of the capabilities of the laser sensor system to support the docking phase (12ft to contact) when operated in conjunction with the Guidance, Navigation and Control Software. The docking mechanism being used was developed for the Apollo Soyuz Test Program. This demonstration will be conducted using the Six-Degrees of Freedom (6-DOF) Dynamic Test System (DTS). The DTS environment simulates the Space Station Freedom as the stationary or target vehicle and the Orbiter as the active or chase vehicle. For this demonstration the laser sensor will be mounted on the target vehicle and the retroreflectors on the chase vehicle. This arrangement was used to prevent potential damage to the laser. The sensor system. GN&C and 6-DOF DTS will be operated closed-loop. Initial condition to simulate vehicle misalignments, translational and rotational, will be introduced within the constraints of the systems involved. Detailed description of each of the demonstration components (e.g., Sensor System, GN&C, 6-DOF DTS and supporting computer configuration) including their capabilities and limitations will be discussed. A demonstration architecture drawing and photographs of the test configuration will be presented.

Decentralized Estimation and Vision-based Guidance of Fast Autonomous Systems with Guaranteed Performance in Uncertain Environments

DTIC Science & Technology

2013-04-22

Following for Unmanned Aerial Vehicles Using L1 Adaptive Augmentation of Commercial Autopilots, Journal of Guidance, Control, and Dynamics, (3 2010): 0...Naira Hovakimyan. L1 Adaptive Controller for MIMO system with Unmatched Uncertainties using Modi?ed Piecewise Constant Adaptation Law, IEEE 51st...adaptive input nominal input with  Nominal input L1 ‐based control generator  This L1 adaptive control architecture uses data from the reference model

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

NASA Technical Reports Server (NTRS)

Joshi, Suresh; Gonzalez, Oscar R.

2014-01-01

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.

Navigation of autonomous vehicles for oil spill cleaning in dynamic and uncertain environments

NASA Astrophysics Data System (ADS)

Jin, Xin; Ray, Asok

2014-04-01

In the context of oil spill cleaning by autonomous vehicles in dynamic and uncertain environments, this paper presents a multi-resolution algorithm that seamlessly integrates the concepts of local navigation and global navigation based on the sensory information; the objective here is to enable adaptive decision making and online replanning of vehicle paths. The proposed algorithm provides a complete coverage of the search area for clean-up of the oil spills and does not suffer from the problem of having local minima, which is commonly encountered in potential-field-based methods. The efficacy of the algorithm is tested on a high-fidelity player/stage simulator for oil spill cleaning in a harbour, where the underlying oil weathering process is modelled as 2D random-walk particle tracking. A preliminary version of this paper was presented by X. Jin and A. Ray as 'Coverage Control of Autonomous Vehicles for Oil Spill Cleaning in Dynamic and Uncertain Environments', Proceedings of the American Control Conference, Washington, DC, June 2013, pp. 2600-2605.

Optimized Autonomous Space In-situ Sensor-Web for volcano monitoring

USGS Publications Warehouse

Song, W.-Z.; Shirazi, B.; Kedar, S.; Chien, S.; Webb, F.; Tran, D.; Davis, A.; Pieri, D.; LaHusen, R.; Pallister, J.; Dzurisin, D.; Moran, S.; Lisowski, M.

2008-01-01

In response to NASA's announced requirement for Earth hazard monitoring sensor-web technology, a multidisciplinary team involving sensor-network experts (Washington State University), space scientists (JPL), and Earth scientists (USGS Cascade Volcano Observatory (CVO)), is developing a prototype dynamic and scaleable hazard monitoring sensor-web and applying it to volcano monitoring. The combined Optimized Autonomous Space -In-situ Sensor-web (OASIS) will have two-way communication capability between ground and space assets, use both space and ground data for optimal allocation of limited power and bandwidth resources on the ground, and use smart management of competing demands for limited space assets. It will also enable scalability and seamless infusion of future space and in-situ assets into the sensor-web. The prototype will be focused on volcano hazard monitoring at Mount St. Helens, which has been active since October 2004. The system is designed to be flexible and easily configurable for many other applications as well. The primary goals of the project are: 1) integrating complementary space (i.e., Earth Observing One (EO-1) satellite) and in-situ (ground-based) elements into an interactive, autonomous sensor-web; 2) advancing sensor-web power and communication resource management technology; and 3) enabling scalability for seamless infusion of future space and in-situ assets into the sensor-web. To meet these goals, we are developing: 1) a test-bed in-situ array with smart sensor nodes capable of making autonomous data acquisition decisions; 2) efficient self-organization algorithm of sensor-web topology to support efficient data communication and command control; 3) smart bandwidth allocation algorithms in which sensor nodes autonomously determine packet priorities based on mission needs and local bandwidth information in real-time; and 4) remote network management and reprogramming tools. The space and in-situ control components of the system will be integrated such that each element is capable of autonomously tasking the other. Sensor-web data acquisition and dissemination will be accomplished through the use of the Open Geospatial Consortium Sensorweb Enablement protocols. The three-year project will demonstrate end-to-end system performance with the in-situ test-bed at Mount St. Helens and NASA's EO-1 platform. ??2008 IEEE.

On the Selection of Models for Runtime Prediction of System Resources

NASA Astrophysics Data System (ADS)

Casolari, Sara; Colajanni, Michele

Applications and services delivered through large Internet Data Centers are now feasible thanks to network and server improvement, but also to virtualization, dynamic allocation of resources and dynamic migrations. The large number of servers and resources involved in these systems requires autonomic management strategies because no amount of human administrators would be capable of cloning and migrating virtual machines in time, as well as re-distributing or re-mapping the underlying hardware. At the basis of most autonomic management decisions, there is the need of evaluating own global behavior and change it when the evaluation indicates that they are not accomplishing what they were intended to do or some relevant anomalies are occurring. Decisions algorithms have to satisfy different time scales constraints. In this chapter we are interested to short-term contexts where runtime prediction models work on the basis of time series coming from samples of monitored system resources, such as disk, CPU and network utilization. In similar environments, we have to address two main issues. First, original time series are affected by limited predictability because measurements are characterized by noises due to system instability, variable offered load, heavy-tailed distributions, hardware and software interactions. Moreover, there is no existing criteria that can help us to choose a suitable prediction model and related parameters with the purpose of guaranteeing an adequate prediction quality. In this chapter, we evaluate the impact that different choices on prediction models have on different time series, and we suggest how to treat input data and whether it is convenient to choose the parameters of a prediction model in a static or dynamic way. Our conclusions are supported by a large set of analyses on realistic and synthetic data traces.

Large-Scale Test of Dynamic Correlation Processors: Implications for Correlation-Based Seismic Pipelines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dodge, D. A.; Harris, D. B.

Correlation detectors are of considerable interest to the seismic monitoring communities because they offer reduced detection thresholds and combine detection, location and identification functions into a single operation. They appear to be ideal for applications requiring screening of frequent repeating events. However, questions remain about how broadly empirical correlation methods are applicable. We describe the effectiveness of banks of correlation detectors in a system that combines traditional power detectors with correlation detectors in terms of efficiency, which we define to be the fraction of events detected by the correlators. This paper elaborates and extends the concept of a dynamic correlationmore » detection framework – a system which autonomously creates correlation detectors from event waveforms detected by power detectors; and reports observed performance on a network of arrays in terms of efficiency. We performed a large scale test of dynamic correlation processors on an 11 terabyte global dataset using 25 arrays in the single frequency band 1-3 Hz. The system found over 3.2 million unique signals and produced 459,747 screened detections. A very satisfying result is that, on average, efficiency grows with time and, after nearly 16 years of operation, exceeds 47% for events observed over all distance ranges and approaches 70% for near regional and 90% for local events. This observation suggests that future pipeline architectures should make extensive use of correlation detectors, principally for decluttering observations of local and near-regional events. Our results also suggest that future operations based on correlation detection will require commodity large-scale computing infrastructure, since the numbers of correlators in an autonomous system can grow into the hundreds of thousands.« less

Large-Scale Test of Dynamic Correlation Processors: Implications for Correlation-Based Seismic Pipelines

DOE PAGES

Dodge, D. A.; Harris, D. B.

2016-03-15

Correlation detectors are of considerable interest to the seismic monitoring communities because they offer reduced detection thresholds and combine detection, location and identification functions into a single operation. They appear to be ideal for applications requiring screening of frequent repeating events. However, questions remain about how broadly empirical correlation methods are applicable. We describe the effectiveness of banks of correlation detectors in a system that combines traditional power detectors with correlation detectors in terms of efficiency, which we define to be the fraction of events detected by the correlators. This paper elaborates and extends the concept of a dynamic correlationmore » detection framework – a system which autonomously creates correlation detectors from event waveforms detected by power detectors; and reports observed performance on a network of arrays in terms of efficiency. We performed a large scale test of dynamic correlation processors on an 11 terabyte global dataset using 25 arrays in the single frequency band 1-3 Hz. The system found over 3.2 million unique signals and produced 459,747 screened detections. A very satisfying result is that, on average, efficiency grows with time and, after nearly 16 years of operation, exceeds 47% for events observed over all distance ranges and approaches 70% for near regional and 90% for local events. This observation suggests that future pipeline architectures should make extensive use of correlation detectors, principally for decluttering observations of local and near-regional events. Our results also suggest that future operations based on correlation detection will require commodity large-scale computing infrastructure, since the numbers of correlators in an autonomous system can grow into the hundreds of thousands.« less

Autonomous Guidance Strategy for Spacecraft Formations and Reconfiguration Maneuvers

NASA Astrophysics Data System (ADS)

Wahl, Theodore P.

A guidance strategy for autonomous spacecraft formation reconfiguration maneuvers is presented. The guidance strategy is presented as an algorithm that solves the linked assignment and delivery problems. The assignment problem is the task of assigning the member spacecraft of the formation to their new positions in the desired formation geometry. The guidance algorithm uses an auction process (also called an "auction algorithm''), presented in the dissertation, to solve the assignment problem. The auction uses the estimated maneuver and time of flight costs between the spacecraft and targets to create assignments which minimize a specific "expense'' function for the formation. The delivery problem is the task of delivering the spacecraft to their assigned positions, and it is addressed through one of two guidance schemes described in this work. The first is a delivery scheme based on artificial potential function (APF) guidance. APF guidance uses the relative distances between the spacecraft, targets, and any obstacles to design maneuvers based on gradients of potential fields. The second delivery scheme is based on model predictive control (MPC); this method uses a model of the system dynamics to plan a series of maneuvers designed to minimize a unique cost function. The guidance algorithm uses an analytic linearized approximation of the relative orbital dynamics, the Yamanaka-Ankersen state transition matrix, in the auction process and in both delivery methods. The proposed guidance strategy is successful, in simulations, in autonomously assigning the members of the formation to new positions and in delivering the spacecraft to these new positions safely using both delivery methods. This guidance algorithm can serve as the basis for future autonomous guidance strategies for spacecraft formation missions.

Autonomous Power System intelligent diagnosis and control

NASA Technical Reports Server (NTRS)

Ringer, Mark J.; Quinn, Todd M.; Merolla, Anthony

1991-01-01

The Autonomous Power System (APS) project at NASA Lewis Research Center is designed to demonstrate the abilities of integrated intelligent diagnosis, control, and scheduling techniques to space power distribution hardware. Knowledge-based software provides a robust method of control for highly complex space-based power systems that conventional methods do not allow. The project consists of three elements: the Autonomous Power Expert System (APEX) for fault diagnosis and control, the Autonomous Intelligent Power Scheduler (AIPS) to determine system configuration, and power hardware (Brassboard) to simulate a space based power system. The operation of the Autonomous Power System as a whole is described and the responsibilities of the three elements - APEX, AIPS, and Brassboard - are characterized. A discussion of the methodologies used in each element is provided. Future plans are discussed for the growth of the Autonomous Power System.

Autonomous power system intelligent diagnosis and control

NASA Technical Reports Server (NTRS)

Ringer, Mark J.; Quinn, Todd M.; Merolla, Anthony

1991-01-01

The Autonomous Power System (APS) project at NASA Lewis Research Center is designed to demonstrate the abilities of integrated intelligent diagnosis, control, and scheduling techniques to space power distribution hardware. Knowledge-based software provides a robust method of control for highly complex space-based power systems that conventional methods do not allow. The project consists of three elements: the Autonomous Power Expert System (APEX) for fault diagnosis and control, the Autonomous Intelligent Power Scheduler (AIPS) to determine system configuration, and power hardware (Brassboard) to simulate a space based power system. The operation of the Autonomous Power System as a whole is described and the responsibilities of the three elements - APEX, AIPS, and Brassboard - are characterized. A discussion of the methodologies used in each element is provided. Future plans are discussed for the growth of the Autonomous Power System.

A SINS/SRS/GNS Autonomous Integrated Navigation System Based on Spectral Redshift Velocity Measurements

PubMed Central

Wei, Wenhui; Gao, Zhaohui; Gao, Shesheng; Jia, Ke

2018-01-01

In order to meet the requirements of autonomy and reliability for the navigation system, combined with the method of measuring speed by using the spectral redshift information of the natural celestial bodies, a new scheme, consisting of Strapdown Inertial Navigation System (SINS)/Spectral Redshift (SRS)/Geomagnetic Navigation System (GNS), is designed for autonomous integrated navigation systems. The principle of this SINS/SRS/GNS autonomous integrated navigation system is explored, and the corresponding mathematical model is established. Furthermore, a robust adaptive central difference particle filtering algorithm is proposed for this autonomous integrated navigation system. The simulation experiments are conducted and the results show that the designed SINS/SRS/GNS autonomous integrated navigation system possesses good autonomy, strong robustness and high reliability, thus providing a new solution for autonomous navigation technology. PMID:29642549

State Tracking and Fault Diagnosis for Dynamic Systems Using Labeled Uncertainty Graph.

PubMed

Zhou, Gan; Feng, Wenquan; Zhao, Qi; Zhao, Hongbo

2015-11-05

Cyber-physical systems such as autonomous spacecraft, power plants and automotive systems become more vulnerable to unanticipated failures as their complexity increases. Accurate tracking of system dynamics and fault diagnosis are essential. This paper presents an efficient state estimation method for dynamic systems modeled as concurrent probabilistic automata. First, the Labeled Uncertainty Graph (LUG) method in the planning domain is introduced to describe the state tracking and fault diagnosis processes. Because the system model is probabilistic, the Monte Carlo technique is employed to sample the probability distribution of belief states. In addition, to address the sample impoverishment problem, an innovative look-ahead technique is proposed to recursively generate most likely belief states without exhaustively checking all possible successor modes. The overall algorithms incorporate two major steps: a roll-forward process that estimates system state and identifies faults, and a roll-backward process that analyzes possible system trajectories once the faults have been detected. We demonstrate the effectiveness of this approach by applying it to a real world domain: the power supply control unit of a spacecraft.

Genetic autonomic disorders.

PubMed

Axelrod, Felicia B

2013-03-01

Genetic disorders affecting the autonomic nervous system can result in abnormal development of the nervous system or they can be caused by neurotransmitter imbalance, an ion-channel disturbance or by storage of deleterious material. The symptoms indicating autonomic dysfunction, however, will depend upon whether the genetic lesion has disrupted peripheral or central autonomic centers or both. Because the autonomic nervous system is pervasive and affects every organ system in the body, autonomic dysfunction will result in impaired homeostasis and symptoms will vary. The possibility of genetic confirmation by molecular testing for specific diagnosis is increasing but treatments tend to remain only supportive and directed toward particular symptoms. Copyright © 2013 Elsevier Inc. All rights reserved.

Dynamical inversion of the energy landscape promotes non-equilibrium self-assembly of binary mixtures

DOE PAGES

Pestana, Luis Ruiz; Minnetian, Natalie; Lammers, Laura Nielsen; ...

2018-01-02

When driven out of equilibrium, many diverse systems can form complex spatial and dynamical patterns, even in the absence of attractive interactions. Using kinetic Monte Carlo simulations, we investigate the phase behavior of a binary system of particles of dissimilar size confined between semiflexible planar surfaces, in which the nanoconfinement introduces a non-local coupling between particles, which we model as an activation energy barrier to diffusion that decreases with the local fraction of the larger particle. The system autonomously reaches a cyclical non-equilibrium state characterized by the formation and dissolution of metastable micelle-like clusters with the small particles in themore » core and the large ones in the surrounding corona. The power spectrum of the fluctuations in the aggregation number exhibits 1/f noise reminiscent of self-organized critical systems. Finally, we suggest that the dynamical metastability of the micellar structures arises from an inversion of the energy landscape, in which the relaxation dynamics of one of the species induces a metastable phase for the other species.« less

Dynamical inversion of the energy landscape promotes non-equilibrium self-assembly of binary mixtures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pestana, Luis Ruiz; Minnetian, Natalie; Lammers, Laura Nielsen

When driven out of equilibrium, many diverse systems can form complex spatial and dynamical patterns, even in the absence of attractive interactions. Using kinetic Monte Carlo simulations, we investigate the phase behavior of a binary system of particles of dissimilar size confined between semiflexible planar surfaces, in which the nanoconfinement introduces a non-local coupling between particles, which we model as an activation energy barrier to diffusion that decreases with the local fraction of the larger particle. The system autonomously reaches a cyclical non-equilibrium state characterized by the formation and dissolution of metastable micelle-like clusters with the small particles in themore » core and the large ones in the surrounding corona. The power spectrum of the fluctuations in the aggregation number exhibits 1/f noise reminiscent of self-organized critical systems. Finally, we suggest that the dynamical metastability of the micellar structures arises from an inversion of the energy landscape, in which the relaxation dynamics of one of the species induces a metastable phase for the other species.« less

IPA (v1): a framework for agent-based modelling of soil water movement

NASA Astrophysics Data System (ADS)

Mewes, Benjamin; Schumann, Andreas H.

2018-06-01

In the last decade, agent-based modelling (ABM) became a popular modelling technique in social sciences, medicine, biology, and ecology. ABM was designed to simulate systems that are highly dynamic and sensitive to small variations in their composition and their state. As hydrological systems, and natural systems in general, often show dynamic and non-linear behaviour, ABM can be an appropriate way to model these systems. Nevertheless, only a few studies have utilized the ABM method for process-based modelling in hydrology. The percolation of water through the unsaturated soil is highly responsive to the current state of the soil system; small variations in composition lead to major changes in the transport system. Hence, we present a new approach for modelling the movement of water through a soil column: autonomous water agents that transport water through the soil while interacting with their environment as well as with other agents under physical laws.

Modular Autonomous Systems Technology Framework: A Distributed Solution for System Monitoring and Control

NASA Technical Reports Server (NTRS)

Badger, Julia M.; Claunch, Charles; Mathis, Frank

2017-01-01

The Modular Autonomous Systems Technology (MAST) framework is a tool for building distributed, hierarchical autonomous systems. Originally intended for the autonomous monitoring and control of spacecraft, this framework concept provides support for variable autonomy, assume-guarantee contracts, and efficient communication between subsystems and a centralized systems manager. MAST was developed at NASA's Johnson Space Center (JSC) and has been applied to an integrated spacecraft example scenario.

Autonomous and Autonomic Swarms

NASA Technical Reports Server (NTRS)

Hinchey, Michael G.; Rash, James L.; Truszkowski, Walter F.; Rouff, Christopher A.; Sterritt, Roy

2005-01-01

A watershed in systems engineering is represented by the advent of swarm-based systems that accomplish missions through cooperative action by a (large) group of autonomous individuals each having simple capabilities and no global knowledge of the group s objective. Such systems, with individuals capable of surviving in hostile environments, pose unprecedented challenges to system developers. Design and testing and verification at much higher levels will be required, together with the corresponding tools, to bring such systems to fruition. Concepts for possible future NASA space exploration missions include autonomous, autonomic swarms. Engineering swarm-based missions begins with understanding autonomy and autonomicity and how to design, test, and verify systems that have those properties and, simultaneously, the capability to accomplish prescribed mission goals. Formal methods-based technologies, both projected and in development, are described in terms of their potential utility to swarm-based system developers.

Dynamical behavior of a stochastic SVIR epidemic model with vaccination

NASA Astrophysics Data System (ADS)

Zhang, Xinhong; Jiang, Daqing; Hayat, Tasawar; Ahmad, Bashir

2017-10-01

In this paper, we investigate the dynamical behavior of SVIR models in random environments. Firstly, we show that if R0s < 1, the disease of stochastic autonomous SVIR model will die out exponentially; if R˜0s > 1, the disease will be prevail. Moreover, this system admits a unique stationary distribution and it is ergodic when R˜0s > 1. Results show that environmental white noise is helpful for disease control. Secondly, we give sufficient conditions for the existence of nontrivial periodic solutions to stochastic SVIR model with periodic parameters. Finally, numerical simulations validate the analytical results.

Cardiac Autonomic Function during Submaximal Treadmill Exercise in Adults with Down Syndrome

ERIC Educational Resources Information Center

Mendonca, Goncalo V.; Pereira, Fernando D.; Fernhall, Bo

2011-01-01

This study determined whether the cardiac autonomic function of adults with Down syndrome (DS) differs from that of nondisabled persons during submaximal dynamic exercise. Thirteen participants with DS and 12 nondisabled individuals performed maximal and submaximal treadmill tests with metabolic and heart rate (HR) measurements. Spectral analysis…

Integrated Dynamic Process Planning and Scheduling in Flexible Manufacturing Systems via Autonomous Agents

NASA Astrophysics Data System (ADS)

Nejad, Hossein Tehrani Nik; Sugimura, Nobuhiro; Iwamura, Koji; Tanimizu, Yoshitaka

Process planning and scheduling are important manufacturing planning activities which deal with resource utilization and time span of manufacturing operations. The process plans and the schedules generated in the planning phase shall be modified in the execution phase due to the disturbances in the manufacturing systems. This paper deals with a multi-agent architecture of an integrated and dynamic system for process planning and scheduling for multi jobs. A negotiation protocol is discussed, in this paper, to generate the process plans and the schedules of the manufacturing resources and the individual jobs, dynamically and incrementally, based on the alternative manufacturing processes. The alternative manufacturing processes are presented by the process plan networks discussed in the previous paper, and the suitable process plans and schedules are searched and generated to cope with both the dynamic status and the disturbances of the manufacturing systems. We initiatively combine the heuristic search algorithms of the process plan networks with the negotiation protocols, in order to generate suitable process plans and schedules in the dynamic manufacturing environment. A simulation software has been developed to carry out case studies, aimed at verifying the performance of the proposed multi-agent architecture.

Quasi-periodic dynamics in system with multilevel pulse modulated control

NASA Astrophysics Data System (ADS)

Gol'tsov, Yu A.; Kizhuk, A. S.; Rubanov, V. G.

2018-03-01

In this paper, the authors describe the transitions from the regular periodic mode to quasiperiodicity that can be observed in a multilevel pulse-width modulated control system for a high-power heating unit. The behavior of such system can be described by a set of two coupled non-autonomous differential equations with discontinuous right-hand sides. The authors reduce the investigation of this system to the studying of a two-dimensional piecewise-smooth map. The authors demonstrate how a closed invariant curve associated with quasiperiodic dynamics can arise from a stable periodic motion through a border-collision bifurcation. The paper also considers a variety of interesting nonlinear phenomena, including phase-locking modes, the coexistence of several stable closed invariant curves, embedded one into the other and with their basins of attraction separated by intervening repelling closed curves.

Servo-controlled hind-limb electrical stimulation for short-term arterial pressure control.

PubMed

Kawada, Toru; Shimizu, Shuji; Yamamoto, Hiromi; Shishido, Toshiaki; Kamiya, Atsunori; Miyamoto, Tadayoshi; Sunagawa, Kenji; Sugimachi, Masaru

2009-05-01

Autonomic neural intervention is a promising tool for modulating the circulatory system thereby treating some cardiovascular diseases. In 8 pentobarbital-anesthetized cats, it was examined whether the arterial pressure (AP) could be controlled by acupuncture-like hind-limb electrical stimulation (HES). With a 0.5-ms pulse width, HES monotonically reduced AP as the stimulus current increased from 1 to 5 mA, suggesting that the stimulus current could be a primary control variable. In contrast, the depressor effect of HES showed a nadir approximately 10 Hz in the frequency range between 1 and 100 Hz. Dynamic characteristics of the AP response to HES approximated a second-order low-pass filter with dead time (gain: -10.2 +/- 1.6 mmHg/mA, natural frequency: 0.040 +/- 0.004 Hz, damping ratio 1.80 +/- 0.24, dead time: 1.38 +/- 0.13 s, mean +/- SE). Based on these dynamic characteristics, a servo-controlled HES system was developed. When a target AP value was set at 20 mmHg below the baseline AP, the time required for the AP response to reach 90% of the target level was 38 +/- 10 s. The steady-state error between the measured and target AP values was 1.3 +/- 0.1 mmHg. Autonomic neural intervention by acupuncture-like HES might provide an additional modality to quantitatively control the circulatory system.

Biomanufacturing and self-propulsion dynamics of nanoscale bacteria-enabled autonomous delivery systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Traore, Mahama A.; Behkam, Bahareh, E-mail: behkam@vt.edu; School of Biomedical Engineering and Sciences, Virginia Tech, Blacksburg, Virginia 24061

Flagellated bacteria have superb self-propulsion capabilities and are able to effectively move through highly viscous fluid and semi-solid (porous) environments. This innate aptitude has been harvested for whole-cell actuation of bio-hybrid microrobotic systems with applications in directed transport and microassembly. In this work, we present the biomanufacturing of Nanoscale Bacteria-Enabled Autonomous Delivery Systems (NanoBEADS) by controlled self-assembly and investigate the role of nanoparticle load on the dynamics of their self-propulsion in aqueous environments. Each NanoBEADS agent is comprised of spherical polystyrene nanoparticles assembled onto the body of a flagellated Escherichia coli bacterium. We demonstrate that the NanoBEADS assembly configuration ismore » strongly dependent upon the nanoparticles to bacteria ratio. Furthermore, we characterized the stochastic motion of the NanoBEADS as a function of the quantity and size of the nanoparticle load and computationally analyzed the effect of the nanoparticle load on the experienced drag force. We report that the average NanoBEADS swimming speed is reduced to 65% of the free-swimming bacteria speed (31 μm/s) at the highest possible load. NanoBEADS can be utilized as single agents or in a collaborative swarm in order to carry out specific tasks in a wide range of applications ranging from drug delivery to whole cell biosensing.« less

Autonomic Nervous System Disorders

MedlinePlus

Your autonomic nervous system is the part of your nervous system that controls involuntary actions, such as the beating of your heart ... breathing and swallowing Erectile dysfunction in men Autonomic nervous system disorders can occur alone or as the result ...

Evolving self-assembly in autonomous homogeneous robots: experiments with two physical robots.

PubMed

Ampatzis, Christos; Tuci, Elio; Trianni, Vito; Christensen, Anders Lyhne; Dorigo, Marco

2009-01-01

This research work illustrates an approach to the design of controllers for self-assembling robots in which the self-assembly is initiated and regulated by perceptual cues that are brought forth by the physical robots through their dynamical interactions. More specifically, we present a homogeneous control system that can achieve assembly between two modules (two fully autonomous robots) of a mobile self-reconfigurable system without a priori introduced behavioral or morphological heterogeneities. The controllers are dynamic neural networks evolved in simulation that directly control all the actuators of the two robots. The neurocontrollers cause the dynamic specialization of the robots by allocating roles between them based solely on their interaction. We show that the best evolved controller proves to be successful when tested on a real hardware platform, the swarm-bot. The performance achieved is similar to the one achieved by existing modular or behavior-based approaches, also due to the effect of an emergent recovery mechanism that was neither explicitly rewarded by the fitness function, nor observed during the evolutionary simulation. Our results suggest that direct access to the orientations or intentions of the other agents is not a necessary condition for robot coordination: Our robots coordinate without direct or explicit communication, contrary to what is assumed by most research works in collective robotics. This work also contributes to strengthening the evidence that evolutionary robotics is a design methodology that can tackle real-world tasks demanding fine sensory-motor coordination.

Preserved cardiac autonomic dynamics during sleep in subjects with spinal cord injuries.

PubMed

Tobaldini, Eleonora; Proserpio, Paola; Sambusida, Katrina; Lanza, Andrea; Redaelli, Tiziana; Frigerio, Pamela; Fratticci, Lara; Rosa, Silvia; Casali, Karina R; Somers, Virend K; Nobili, Lino; Montano, Nicola

2015-06-01

Spinal cord injuries (SCI) are associated with altered cardiovascular autonomic control (CAC). Sleep is characterized by modifications of autonomic control across sleep stages; however, no data are available in SCI subjects on CAC during sleep. We aim to assess cardiac autonomic modulation during sleep in subjects with SCI. 27 participants with a neurological and radiological diagnosis of cervical (Cerv, n = 12, ie, tetraplegic) and thoracic SCI (Thor, n = 15, ie, paraplegic) and healthy subjects (Controls) were enrolled. Overnight polysomnographic (PSG) recordings were obtained in all participants. Electrocardiography and respiration were extracted from PSG, divided into sleep stages [wakefulness (W), non-REM sleep (NREM) and REM] for assessment of CAC, using symbolic analysis (SA) and corrected conditional entropy (CCE). SA identified indices of sympathetic and parasympathetic modulation and CCE evaluated the degree of complexity of the heart period time series. SA revealed a reduction of sympathetic and predominant parasympathetic control during NREM compared to W and REM in SCI patients, independent of the level of the lesion, similar to the Controls. In all three groups, complexity of autonomic regulation was higher in NREM compared to W and REM. In subjects with SCI, cardiac autonomic control changed across sleep stages, with a reduction of sympathetic and an increase of parasympathetic modulation during NREM compared to W and REM, and a parallel increase of complexity during NREM, which was similar to the Controls. Cardiac autonomic dynamics during sleep are maintained in SCI, independent of the level of the lesion. Copyright © 2014 Elsevier B.V. All rights reserved.

Synchronization of Human Autonomic Nervous System Rhythms with Geomagnetic Activity in Human Subjects

PubMed Central

McCraty, Rollin; Atkinson, Mike; Stolc, Viktor; Alabdulgader, Abdullah A.; Vainoras, Alfonsas

2017-01-01

A coupling between geomagnetic activity and the human nervous system’s function was identified by virtue of continuous monitoring of heart rate variability (HRV) and the time-varying geomagnetic field over a 31-day period in a group of 10 individuals who went about their normal day-to-day lives. A time series correlation analysis identified a response of the group’s autonomic nervous systems to various dynamic changes in the solar, cosmic ray, and ambient magnetic field. Correlation coefficients and p values were calculated between the HRV variables and environmental measures during three distinct time periods of environmental activity. There were significant correlations between the group’s HRV and solar wind speed, Kp, Ap, solar radio flux, cosmic ray counts, Schumann resonance power, and the total variations in the magnetic field. In addition, the time series data were time synchronized and normalized, after which all circadian rhythms were removed. It was found that the participants’ HRV rhythms synchronized across the 31-day period at a period of approximately 2.5 days, even though all participants were in separate locations. Overall, this suggests that daily autonomic nervous system activity not only responds to changes in solar and geomagnetic activity, but is synchronized with the time-varying magnetic fields associated with geomagnetic field-line resonances and Schumann resonances. PMID:28703754

Autonomous Operations System: Development and Application

NASA Technical Reports Server (NTRS)

Toro Medina, Jaime A.; Wilkins, Kim N.; Walker, Mark; Stahl, Gerald M.

2016-01-01

Autonomous control systems provides the ability of self-governance beyond the conventional control system. As the complexity of mechanical and electrical systems increases, there develops a natural drive for developing robust control systems to manage complicated operations. By closing the bridge between conventional automated systems to knowledge based self-awareness systems, nominal control of operations can evolve into relying on safe critical mitigation processes to support any off-nominal behavior. Current research and development efforts lead by the Autonomous Propellant Loading (APL) group at NASA Kennedy Space Center aims to improve cryogenic propellant transfer operations by developing an automated control and health monitoring system. As an integrated systems, the center aims to produce an Autonomous Operations System (AOS) capable of integrating health management operations with automated control to produce a fully autonomous system.

The Visual Representation and Acquisition of Driving Knowledge for Autonomous Vehicle

NASA Astrophysics Data System (ADS)

Zhang, Zhaoxia; Jiang, Qing; Li, Ping; Song, LiangTu; Wang, Rujing; Yu, Biao; Mei, Tao

2017-09-01

In this paper, the driving knowledge base of autonomous vehicle is designed. Based on the driving knowledge modeling system, the driving knowledge of autonomous vehicle is visually acquired, managed, stored, and maintenanced, which has vital significance for creating the development platform of intelligent decision-making systems of automatic driving expert systems for autonomous vehicle.

Project WISH: The Emerald City

NASA Technical Reports Server (NTRS)

1990-01-01

When Project WISH (Wandering Interplanetary Space Harbor) was initiated as a multi-year project, several design requirements were specified. The space station must have a lifetime of at least 50 years, be autonomous and independent of Earth resources, be capable of traveling throughout the solar system within a maximum flight time of three years, and have a population of 500 to 1000 people. The purpose of the station is to provide a permanent home for space colonists and to serve as a service station for space missions. The orbital mechanics, propulsion system, vehicle dynamics and control, life support system, communication system, power system, and thermal system are discussed.

Optimal path planning for video-guided smart munitions via multitarget tracking

NASA Astrophysics Data System (ADS)

Borkowski, Jeffrey M.; Vasquez, Juan R.

2006-05-01

An advent in the development of smart munitions entails autonomously modifying target selection during flight in order to maximize the value of the target being destroyed. A unique guidance law can be constructed that exploits both attribute and kinematic data obtained from an onboard video sensor. An optimal path planning algorithm has been developed with the goals of obstacle avoidance and maximizing the value of the target impacted by the munition. Target identification and classification provides a basis for target value which is used in conjunction with multi-target tracks to determine an optimal waypoint for the munition. A dynamically feasible trajectory is computed to provide constraints on the waypoint selection. Results demonstrate the ability of the autonomous system to avoid moving obstacles and revise target selection in flight.

Examining accident reports involving autonomous vehicles in California

PubMed Central

Nader, Nazanin; Eurich, Sky O.; Tripp, Michelle; Varadaraju, Naresh

2017-01-01

Autonomous Vehicle technology is quickly expanding its market and has found in Silicon Valley, California, a strong foothold for preliminary testing on public roads. In an effort to promote safety and transparency to consumers, the California Department of Motor Vehicles has mandated that reports of accidents involving autonomous vehicles be drafted and made available to the public. The present work shows an in-depth analysis of the accident reports filed by different manufacturers that are testing autonomous vehicles in California (testing data from September 2014 to March 2017). The data provides important information on autonomous vehicles accidents’ dynamics, related to the most frequent types of collisions and impacts, accident frequencies, and other contributing factors. The study also explores important implications related to future testing and validation of semi-autonomous vehicles, tracing the investigation back to current literature as well as to the current regulatory panorama. PMID:28931022

Examining accident reports involving autonomous vehicles in California.

PubMed

Favarò, Francesca M; Nader, Nazanin; Eurich, Sky O; Tripp, Michelle; Varadaraju, Naresh

2017-01-01

Autonomous Vehicle technology is quickly expanding its market and has found in Silicon Valley, California, a strong foothold for preliminary testing on public roads. In an effort to promote safety and transparency to consumers, the California Department of Motor Vehicles has mandated that reports of accidents involving autonomous vehicles be drafted and made available to the public. The present work shows an in-depth analysis of the accident reports filed by different manufacturers that are testing autonomous vehicles in California (testing data from September 2014 to March 2017). The data provides important information on autonomous vehicles accidents' dynamics, related to the most frequent types of collisions and impacts, accident frequencies, and other contributing factors. The study also explores important implications related to future testing and validation of semi-autonomous vehicles, tracing the investigation back to current literature as well as to the current regulatory panorama.

A fuzzy logic controller for an autonomous mobile robot

NASA Technical Reports Server (NTRS)

Yen, John; Pfluger, Nathan

1993-01-01

The ability of a mobile robot system to plan and move intelligently in a dynamic system is needed if robots are to be useful in areas other than controlled environments. An example of a use for this system is to control an autonomous mobile robot in a space station, or other isolated area where it is hard or impossible for human life to exist for long periods of time (e.g., Mars). The system would allow the robot to be programmed to carry out the duties normally accomplished by a human being. Some of the duties that could be accomplished include operating instruments, transporting objects, and maintenance of the environment. The main focus of our early work has been on developing a fuzzy controller that takes a path and adapts it to a given environment. The robot only uses information gathered from the sensors, but retains the ability to avoid dynamically placed obstacles near and along the path. Our fuzzy logic controller is based on the following algorithm: (1) determine the desired direction of travel; (2) determine the allowed direction of travel; and (3) combine the desired and allowed directions in order to determine a direciton that is both desired and allowed. The desired direction of travel is determined by projecting ahead to a point along the path that is closer to the goal. This gives a local direction of travel for the robot and helps to avoid obstacles.

Dynamic Curvature Steering Control for Autonomous Vehicle: Performance Analysis

NASA Astrophysics Data System (ADS)

Aizzat Zakaria, Muhammad; Zamzuri, Hairi; Amri Mazlan, Saiful

2016-02-01

This paper discusses the design of dynamic curvature steering control for autonomous vehicle. The lateral control and longitudinal control are discussed in this paper. The controller is designed based on the dynamic curvature calculation to estimate the path condition and modify the vehicle speed and steering wheel angle accordingly. In this paper, the simulation results are presented to show the capability of the controller to track the reference path. The controller is able to predict the path and modify the vehicle speed to suit the path condition. The effectiveness of the controller is shown in this paper whereby identical performance is achieved with the benchmark but with extra curvature adaptation capabilites.

Memory consolidation from seconds to weeks: a three-stage neural network model with autonomous reinstatement dynamics

PubMed Central

Fiebig, Florian; Lansner, Anders

2014-01-01

Declarative long-term memories are not created in an instant. Gradual stabilization and temporally shifting dependence of acquired declarative memories in different brain regions—called systems consolidation—can be tracked in time by lesion experiments. The observation of temporally graded retrograde amnesia (RA) following hippocampal lesions points to a gradual transfer of memory from hippocampus to neocortical long-term memory. Spontaneous reactivations of hippocampal memories, as observed in place cell reactivations during slow-wave-sleep, are supposed to drive neocortical reinstatements and facilitate this process. We propose a functional neural network implementation of these ideas and furthermore suggest an extended three-state framework that includes the prefrontal cortex (PFC). It bridges the temporal chasm between working memory percepts on the scale of seconds and consolidated long-term memory on the scale of weeks or months. We show that our three-stage model can autonomously produce the necessary stochastic reactivation dynamics for successful episodic memory consolidation. The resulting learning system is shown to exhibit classical memory effects seen in experimental studies, such as retrograde and anterograde amnesia (AA) after simulated hippocampal lesioning; furthermore the model reproduces peculiar biological findings on memory modulation, such as retrograde facilitation of memory after suppressed acquisition of new long-term memories—similar to the effects of benzodiazepines on memory. PMID:25071536

Agent Based Intelligence in a Tetrahedral Rover

NASA Technical Reports Server (NTRS)

Phelps, Peter; Truszkowski, Walt

2007-01-01

A tetrahedron is a 4-node 6-strut pyramid structure which is being used by the NASA - Goddard Space Flight Center as the basic building block for a new approach to robotic motion. The struts are extendable; it is by the sequence of activities: strut-extension, changing the center of gravity and falling that the tetrahedron "moves". Currently, strut-extension is handled by human remote control. There is an effort underway to make the movement of the tetrahedron autonomous, driven by an attempt to achieve a goal. The approach being taken is to associate an intelligent agent with each node. Thus, the autonomous tetrahedron is realized as a constrained multi-agent system, where the constraints arise from the fact that between any two agents there is an extendible strut. The hypothesis of this work is that, by proper composition of such automated tetrahedra, robotic structures of various levels of complexity can be developed which will support more complex dynamic motions. This is the basis of the new approach to robotic motion which is under investigation. A Java-based simulator for the single tetrahedron, realized as a constrained multi-agent system, has been developed and evaluated. This paper reports on this project and presents a discussion of the structure and dynamics of the simulator.

An apparatus to estimate the hydrodynamic coefficients of autonomous underwater vehicles using water tunnel testing.

PubMed

Nouri, N M; Mostafapour, K; Bahadori, R

2016-06-01

Hydrodynamic coefficients or hydrodynamic derivatives of autonomous underwater vehicles (AUVs) play an important role in their development and maneuverability. The most popular way of estimating their coefficients is to implement captive model tests such as straight line tests and planar motion mechanism (PMM) tests in the towing tanks. This paper aims to develop an apparatus based on planar experiments of water tunnel in order to estimate hydrodynamic derivatives due to AUVs' acceleration and velocity. The capability of implementing straight line tests and PMM ones using mechanical oscillators located in the downstream flow of the model is considered in the design procedure of the system. The hydrodynamic derivatives that resulted from the acceleration and velocity of the AUV model were estimated using the apparatus that we developed. Static and dynamics test results were compared for the similar derivatives. The findings showed that the system provided the basis for conducting static tests, i.e., straight-line and dynamic tests that included pure pitch and pure heave. By conducting such tests in a water tunnel, we were able to eliminate errors related to the time limitation of the tests and the effects of surface waves in the towing tank on AUVs with applications in the deep sea.

Knowledge-based and integrated monitoring and diagnosis in autonomous power systems

NASA Technical Reports Server (NTRS)

Momoh, J. A.; Zhang, Z. Z.

1990-01-01

A new technique of knowledge-based and integrated monitoring and diagnosis (KBIMD) to deal with abnormalities and incipient or potential failures in autonomous power systems is presented. The KBIMD conception is discussed as a new function of autonomous power system automation. Available diagnostic modelling, system structure, principles and strategies are suggested. In order to verify the feasibility of the KBIMD, a preliminary prototype expert system is designed to simulate the KBIMD function in a main electric network of the autonomous power system.

Man-Robot Symbiosis: A Framework For Cooperative Intelligence And Control

NASA Astrophysics Data System (ADS)

Parker, Lynne E.; Pin, Francois G.

1988-10-01

The man-robot symbiosis concept has the fundamental objective of bridging the gap between fully human-controlled and fully autonomous systems to achieve true man-robot cooperative control and intelligence. Such a system would allow improved speed, accuracy, and efficiency of task execution, while retaining the man in the loop for innovative reasoning and decision-making. The symbiont would have capabilities for supervised and unsupervised learning, allowing an increase of expertise in a wide task domain. This paper describes a robotic system architecture facilitating the symbiotic integration of teleoperative and automated modes of task execution. The architecture reflects a unique blend of many disciplines of artificial intelligence into a working system, including job or mission planning, dynamic task allocation, man-robot communication, automated monitoring, and machine learning. These disciplines are embodied in five major components of the symbiotic framework: the Job Planner, the Dynamic Task Allocator, the Presenter/Interpreter, the Automated Monitor, and the Learning System.

Nature's Autonomous Oscillators

NASA Technical Reports Server (NTRS)

Mayr, H. G.; Yee, J.-H.; Mayr, M.; Schnetzler, R.

2012-01-01

Nonlinearity is required to produce autonomous oscillations without external time dependent source, and an example is the pendulum clock. The escapement mechanism of the clock imparts an impulse for each swing direction, which keeps the pendulum oscillating at the resonance frequency. Among nature's observed autonomous oscillators, examples are the quasi-biennial oscillation and bimonthly oscillation of the Earth atmosphere, and the 22-year solar oscillation. The oscillations have been simulated in numerical models without external time dependent source, and in Section 2 we summarize the results. Specifically, we shall discuss the nonlinearities that are involved in generating the oscillations, and the processes that produce the periodicities. In biology, insects have flight muscles, which function autonomously with wing frequencies that far exceed the animals' neural capacity; Stretch-activation of muscle contraction is the mechanism that produces the high frequency oscillation of insect flight, discussed in Section 3. The same mechanism is also invoked to explain the functioning of the cardiac muscle. In Section 4, we present a tutorial review of the cardio-vascular system, heart anatomy, and muscle cell physiology, leading up to Starling's Law of the Heart, which supports our notion that the human heart is also a nonlinear oscillator. In Section 5, we offer a broad perspective of the tenuous links between the fluid dynamical oscillators and the human heart physiology.

Monitoring Floods with NASA's ST6 Autonomous Sciencecraft Experiment: Implications on Planetary Exploration

NASA Technical Reports Server (NTRS)

Ip, Felipe; Dohm, J. M.; Baker, V. R.; Castano, B.; Chien, S.; Cichy, B.; Davies, A. G.; Doggett, T.; Greeley, R.; Sherwood, R.

2005-01-01

NASA's New Millennium Program (NMP) Autonomous Sciencecraft Experiment (ASE) [1-3] has been successfully demonstrated in Earth-orbit. NASA has identified the development of an autonomously operating spacecraft as a necessity for an expanded program of missions exploring the Solar System. The versatile ASE spacecraft command and control, image formation, and science processing software was uploaded to the Earth Observer 1 (EO-1) spacecraft in early 2004 and has been undergoing onboard testing since May 2004 for the near real-time detection of surface modification related to transient geological and hydrological processes such as volcanism [4], ice formation and retreat [5], and flooding [6]. Space autonomy technology developed as part of ASE creates the new capability to autonomously detect, assess, react to, and monitor dynamic events such as flooding. Part of the challenge has been the difficulty to observe flooding in real time at sufficient temporal resolutions; more importantly, it is the large spatial extent of most drainage networks coupled with the size of the data sets necessary to be downlinked from satellites that make it difficult to monitor flooding from space. Below is a description of the algorithms (referred to as ASE Flood water Classifiers) used in tandem with the Hyperion spectrometer instrument on EO-1 to identify flooding and some of the test results.

Adaptive Control for Autonomous Navigation of Mobile Robots Considering Time Delay and Uncertainty

NASA Astrophysics Data System (ADS)

Armah, Stephen Kofi

Autonomous control of mobile robots has attracted considerable attention of researchers in the areas of robotics and autonomous systems during the past decades. One of the goals in the field of mobile robotics is development of platforms that robustly operate in given, partially unknown, or unpredictable environments and offer desired services to humans. Autonomous mobile robots need to be equipped with effective, robust and/or adaptive, navigation control systems. In spite of enormous reported work on autonomous navigation control systems for mobile robots, achieving the goal above is still an open problem. Robustness and reliability of the controlled system can always be improved. The fundamental issues affecting the stability of the control systems include the undesired nonlinear effects introduced by actuator saturation, time delay in the controlled system, and uncertainty in the model. This research work develops robustly stabilizing control systems by investigating and addressing such nonlinear effects through analytical, simulations, and experiments. The control systems are designed to meet specified transient and steady-state specifications. The systems used for this research are ground (Dr Robot X80SV) and aerial (Parrot AR.Drone 2.0) mobile robots. Firstly, an effective autonomous navigation control system is developed for X80SV using logic control by combining 'go-to-goal', 'avoid-obstacle', and 'follow-wall' controllers. A MATLAB robot simulator is developed to implement this control algorithm and experiments are conducted in a typical office environment. The next stage of the research develops an autonomous position (x, y, and z) and attitude (roll, pitch, and yaw) controllers for a quadrotor, and PD-feedback control is used to achieve stabilization. The quadrotor's nonlinear dynamics and kinematics are implemented using MATLAB S-function to generate the state output. Secondly, the white-box and black-box approaches are used to obtain a linearized second-order altitude models for the quadrotor, AR.Drone 2.0. Proportional (P), pole placement or proportional plus velocity (PV), linear quadratic regulator (LQR), and model reference adaptive control (MRAC) controllers are designed and validated through simulations using MATLAB/Simulink. Control input saturation and time delay in the controlled systems are also studied. MATLAB graphical user interface (GUI) and Simulink programs are developed to implement the controllers on the drone. Thirdly, the time delay in the drone's control system is estimated using analytical and experimental methods. In the experimental approach, the transient properties of the experimental altitude responses are compared to those of simulated responses. The analytical approach makes use of the Lambert W function to obtain analytical solutions of scalar first-order delay differential equations (DDEs). A time-delayed P-feedback control system (retarded type) is used in estimating the time delay. Then an improved system performance is obtained by incorporating the estimated time delay in the design of the PV control system (neutral type) and PV-MRAC control system. Furthermore, the stability of a parametric perturbed linear time-invariant (LTI) retarded-type system is studied. This is done by analytically calculating the stability radius of the system. Simulation of the control system is conducted to confirm the stability. This robust control design and uncertainty analysis are conducted for first-order and second-order quadrotor models. Lastly, the robustly designed PV and PV-MRAC control systems are used to autonomously track multiple waypoints. Also, the robustness of the PV-MRAC controller is tested against a baseline PV controller using the payload capability of the drone. It is shown that the PV-MRAC offers several benefits over the fixed-gain approach of the PV controller. The adaptive control is found to offer enhanced robustness to the payload fluctuations.

Structured Kernel Subspace Learning for Autonomous Robot Navigation.

PubMed

Kim, Eunwoo; Choi, Sungjoon; Oh, Songhwai

2018-02-14

This paper considers two important problems for autonomous robot navigation in a dynamic environment, where the goal is to predict pedestrian motion and control a robot with the prediction for safe navigation. While there are several methods for predicting the motion of a pedestrian and controlling a robot to avoid incoming pedestrians, it is still difficult to safely navigate in a dynamic environment due to challenges, such as the varying quality and complexity of training data with unwanted noises. This paper addresses these challenges simultaneously by proposing a robust kernel subspace learning algorithm based on the recent advances in nuclear-norm and l 1 -norm minimization. We model the motion of a pedestrian and the robot controller using Gaussian processes. The proposed method efficiently approximates a kernel matrix used in Gaussian process regression by learning low-rank structured matrix (with symmetric positive semi-definiteness) to find an orthogonal basis, which eliminates the effects of erroneous and inconsistent data. Based on structured kernel subspace learning, we propose a robust motion model and motion controller for safe navigation in dynamic environments. We evaluate the proposed robust kernel learning in various tasks, including regression, motion prediction, and motion control problems, and demonstrate that the proposed learning-based systems are robust against outliers and outperform existing regression and navigation methods.

Autonomous control systems - Architecture and fundamental issues

NASA Technical Reports Server (NTRS)

Antsaklis, P. J.; Passino, K. M.; Wang, S. J.

1988-01-01

A hierarchical functional autonomous controller architecture is introduced. In particular, the architecture for the control of future space vehicles is described in detail; it is designed to ensure the autonomous operation of the control system and it allows interaction with the pilot and crew/ground station, and the systems on board the autonomous vehicle. The fundamental issues in autonomous control system modeling and analysis are discussed. It is proposed to utilize a hybrid approach to modeling and analysis of autonomous systems. This will incorporate conventional control methods based on differential equations and techniques for the analysis of systems described with a symbolic formalism. In this way, the theory of conventional control can be fully utilized. It is stressed that autonomy is the design requirement and intelligent control methods appear at present, to offer some of the necessary tools to achieve autonomy. A conventional approach may evolve and replace some or all of the `intelligent' functions. It is shown that in addition to conventional controllers, the autonomous control system incorporates planning, learning, and FDI (fault detection and identification).

New meanings of thin-skinned: The contrasting attentional profiles of typical 12-month-olds who show high, and low, stress reactivity.

PubMed

Wass, Sam V; de Barbaro, Kaya; Clackson, Kaili; Leong, Victoria

2018-05-01

Previous research is inconsistent as to whether a more labile (faster-changing) autonomic system confers performance advantages, or disadvantages, in infants and children. To examine this, we presented a stimulus battery consisting of mixed static and dynamic viewing materials to a cohort of 63 typical 12-month-old infants. While viewing the battery, infants' spontaneous visual attention (looks to and away from the screen) was measured. Concurrently, arousal was recorded via heart rate (HR), electrodermal activity, head velocity, and peripheral movement levels. In addition, stress reactivity was assessed using a mild behavioral stressor (watching a video of another infant crying). We found that infants who were generally more attentive showed smaller HR increases to the stressor. However, they also showed greater phasic autonomic changes to attractive, attention-getting stimulus events, a faster rate of change of both look duration and of arousal, and more general oscillatory activity in arousal. Finally, 4 sessions of attention training were applied to a subset of the infants (24 trained, 24 active controls), which had the effect of increasing visual sustained attention. No changes in HR responses to stressor were observed as a result of training, but concomitant increases in arousal lability were observed. Our results point to 2 contrasting autonomic profiles: infants with high autonomic reactivity to stressors show short attention durations, whereas infants with lower autonomic reactivity show longer attention durations and greater arousal lability. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Autonomous Flight Safety System September 27, 2005, Aircraft Test

NASA Technical Reports Server (NTRS)

Simpson, James C.

2005-01-01

This report describes the first aircraft test of the Autonomous Flight Safety System (AFSS). The test was conducted on September 27, 2005, near Kennedy Space Center (KSC) using a privately-owned single-engine plane and evaluated the performance of several basic flight safety rules using real-time data onboard a moving aerial vehicle. This test follows the first road test of AFSS conducted in February 2005 at KSC. AFSS is a joint KSC and Wallops Flight Facility (WEF) project that is in its third phase of development. AFSS is an independent subsystem intended for use with Expendable Launch Vehicles that uses tracking data from redundant onboard sensors to autonomously make flight termination decisions using software-based rules implemented on redundant flight processors. The goals of this project are to increase capabilities by allowing launches from locations that do not have or cannot afford extensive ground-based range safety assets, to decrease range costs, and to decrease reaction time for special situations. The mission rules are configured for each operation by the responsible Range Safety authorities and can be loosely categorized in four major categories: Parameter Threshold Violations, Physical Boundary Violations present position and instantaneous impact point (TIP), Gate Rules static and dynamic, and a Green-Time Rule. Examples of each of these rules were evaluated during this aircraft test.

Agent Technology, Complex Adaptive Systems, and Autonomic Systems: Their Relationships

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Rash, James; Rouff, Chistopher; Hincheny, Mike

2004-01-01

To reduce the cost of future spaceflight missions and to perform new science, NASA has been investigating autonomous ground and space flight systems. These goals of cost reduction have been further complicated by nanosatellites for future science data-gathering which will have large communications delays and at times be out of contact with ground control for extended periods of time. This paper describes two prototype agent-based systems, the Lights-out Ground Operations System (LOGOS) and the Agent Concept Testbed (ACT), and their autonomic properties that were developed at NASA Goddard Space Flight Center (GSFC) to demonstrate autonomous operations of future space flight missions. The paper discusses the architecture of the two agent-based systems, operational scenarios of both, and the two systems autonomic properties.

Autonomous Systems, Robotics, and Computing Systems Capability Roadmap: NRC Dialogue

NASA Technical Reports Server (NTRS)

Zornetzer, Steve; Gage, Douglas

2005-01-01

Contents include the following: Introduction. Process, Mission Drivers, Deliverables, and Interfaces. Autonomy. Crew-Centered and Remote Operations. Integrated Systems Health Management. Autonomous Vehicle Control. Autonomous Process Control. Robotics. Robotics for Solar System Exploration. Robotics for Lunar and Planetary Habitation. Robotics for In-Space Operations. Computing Systems. Conclusion.

Sustainable and Autonomic Space Exploration Missions

NASA Technical Reports Server (NTRS)

Hinchey, Michael G.; Sterritt, Roy; Rouff, Christopher; Rash, James L.; Truszkowski, Walter

2006-01-01

Visions for future space exploration have long term science missions in sight, resulting in the need for sustainable missions. Survivability is a critical property of sustainable systems and may be addressed through autonomicity, an emerging paradigm for self-management of future computer-based systems based on inspiration from the human autonomic nervous system. This paper examines some of the ongoing research efforts to realize these survivable systems visions, with specific emphasis on developments in Autonomic Policies.

Linear and nonlinear dynamics of heart rate variability in the process of exposure to 3600 m in 10 min.

PubMed

Zhang, Da; She, Jin; Yang, Jun; Yu, Mengsun

2015-06-01

Acute hypoxia activates several autonomic mechanisms, mainly in cardiovascular system and respiratory system. The influence of acute hypoxia on linear and nonlinear heart rate variability (HRV) has been studied, but the parameters in the process of hypoxia are still unclear. Although the changes of HRV in frequency domain are related to autonomic responses, how nonlinear dynamics change with the decrease of ambient atmospheric pressure is unknown either. Eight healthy male subjects were exposed to simulated altitude from sea level to 3600 m in 10 min. HRV parameters in frequency domain were analyzed by wavelet packet transform (Daubechies 4, 4 level) followed by Hilbert transform to assess the spectral power of modified low frequency (0.0625-0.1875 Hz, LFmod), modified high frequency (0.1875-0.4375 Hz, HFmod), and the LFmod/HFmod ratio in every 1 min. Nonlinear parameters were also quantified by sample entropy (SampEn) and short term fractal correlation exponent (α1) in the process. Hypoxia was associated with the depression of both LFmod and HFmod component. They were significantly lower than that at sea level at 3600 m and 2880 m respectively (both p < 0.05). The LFmod/HFmod ratio was acutely increased at 3600 m (p < 0.05). SampEn was significantly declined at 2880 m (p < 0.05). Although the value of α1 was close to 1, it changed not significantly in the whole process. These results indicated hypoxia gradually attenuated both spectral HRV parameters and SampEn. The balance of sympathovagal shifted towards sympathetic dominance at a certain altitude. Monitoring linear and nonlinear HRV parameters continuously in the process of hypoxia would be an effective way to evaluate the different regulatory mechanisms of autonomic nervous system.

The development of an autonomous gust insensitive unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Pisano, William James

The study of a small Unmanned Aerial Vehicle (UAV) that is designed towards eventual operation in harsh storm-like conditions is presented. Investigation of the aircraft equations of motion shows that the selection of certain aerodynamic derivatives has a significant effect on the gust response of a small unmanned aircraft. Analytical comparison of this newly formulated Autonomous Gust Insensitive Aircraft (AGIA) to a conventionally designed aircraft shows a significant reduction in undesirable roll motion caused by gusts. A simulation is presented showing that the AGIA is capable of operating in more extreme environments than a conventional aircraft, and puts less strain on the control system components in both extreme and calm environments. The role that aircraft size plays in gust response is also studied. Pilot instinct dictates that smaller aircraft are more difficult to fly in windy environments than larger ones. This phenomenon is investigated using an analytic approach, providing insight into why smaller aircraft are indeed more difficult to fly in more challenging environments. As an aircraft gets smaller, its natural aerodynamic modes and response get faster. In an ideal system, this does not limit small aircraft to poor performance (in fact it will be shown that idealized small aircraft theoretically perform better than their larger counterparts). A more realistic system is presented that includes not only aerodynamics, but also realistic sensor and actuator dynamics. It is shown that these additional dynamics become a limiting factor in control system performance, and thus limit the closed-loop flight performance of small aircraft in turbulent environments. It is shown that the AGIA design approach plays a more significant role the as an aircraft gets smaller. To provide experimental validation of the gust insensitive theory presented herein, a representative small conventional aircraft was built alongside a similar aircraft that incorporated the AGIA design characteristics. These two aircraft were flown simultaneously and autonomously using the autopilot developed by the Author. Data from this experiment strongly supports the hypothesis that the AGIA is less sensitive to gusts than its conventional counterpart, and that flight of the AGIA puts less strain on the control system components in flight.

Optimized autonomous space in-situ sensor web for volcano monitoring

USGS Publications Warehouse

Song, W.-Z.; Shirazi, B.; Huang, R.; Xu, M.; Peterson, N.; LaHusen, R.; Pallister, J.; Dzurisin, D.; Moran, S.; Lisowski, M.; Kedar, S.; Chien, S.; Webb, F.; Kiely, A.; Doubleday, J.; Davies, A.; Pieri, D.

2010-01-01

In response to NASA's announced requirement for Earth hazard monitoring sensor-web technology, a multidisciplinary team involving sensor-network experts (Washington State University), space scientists (JPL), and Earth scientists (USGS Cascade Volcano Observatory (CVO)), have developed a prototype of dynamic and scalable hazard monitoring sensor-web and applied it to volcano monitoring. The combined Optimized Autonomous Space In-situ Sensor-web (OASIS) has two-way communication capability between ground and space assets, uses both space and ground data for optimal allocation of limited bandwidth resources on the ground, and uses smart management of competing demands for limited space assets. It also enables scalability and seamless infusion of future space and in-situ assets into the sensor-web. The space and in-situ control components of the system are integrated such that each element is capable of autonomously tasking the other. The ground in-situ was deployed into the craters and around the flanks of Mount St. Helens in July 2009, and linked to the command and control of the Earth Observing One (EO-1) satellite. ?? 2010 IEEE.

A Neural Dynamic Architecture for Reaching and Grasping Integrates Perception and Movement Generation and Enables On-Line Updating.

PubMed

Knips, Guido; Zibner, Stephan K U; Reimann, Hendrik; Schöner, Gregor

2017-01-01

Reaching for objects and grasping them is a fundamental skill for any autonomous robot that interacts with its environment. Although this skill seems trivial to adults, who effortlessly pick up even objects they have never seen before, it is hard for other animals, for human infants, and for most autonomous robots. Any time during movement preparation and execution, human reaching movement are updated if the visual scene changes (with a delay of about 100 ms). The capability for online updating highlights how tightly perception, movement planning, and movement generation are integrated in humans. Here, we report on an effort to reproduce this tight integration in a neural dynamic process model of reaching and grasping that covers the complete path from visual perception to movement generation within a unified modeling framework, Dynamic Field Theory. All requisite processes are realized as time-continuous dynamical systems that model the evolution in time of neural population activation. Population level neural processes bring about the attentional selection of objects, the estimation of object shape and pose, and the mapping of pose parameters to suitable movement parameters. Once a target object has been selected, its pose parameters couple into the neural dynamics of movement generation so that changes of pose are propagated through the architecture to update the performed movement online. Implementing the neural architecture on an anthropomorphic robot arm equipped with a Kinect sensor, we evaluate the model by grasping wooden objects. Their size, shape, and pose are estimated from a neural model of scene perception that is based on feature fields. The sequential organization of a reach and grasp act emerges from a sequence of dynamic instabilities within a neural dynamics of behavioral organization, that effectively switches the neural controllers from one phase of the action to the next. Trajectory formation itself is driven by a dynamical systems version of the potential field approach. We highlight the emergent capacity for online updating by showing that a shift or rotation of the object during the reaching phase leads to the online adaptation of the movement plan and successful completion of the grasp.

A Neural Dynamic Architecture for Reaching and Grasping Integrates Perception and Movement Generation and Enables On-Line Updating

PubMed Central

Knips, Guido; Zibner, Stephan K. U.; Reimann, Hendrik; Schöner, Gregor

2017-01-01

Reaching for objects and grasping them is a fundamental skill for any autonomous robot that interacts with its environment. Although this skill seems trivial to adults, who effortlessly pick up even objects they have never seen before, it is hard for other animals, for human infants, and for most autonomous robots. Any time during movement preparation and execution, human reaching movement are updated if the visual scene changes (with a delay of about 100 ms). The capability for online updating highlights how tightly perception, movement planning, and movement generation are integrated in humans. Here, we report on an effort to reproduce this tight integration in a neural dynamic process model of reaching and grasping that covers the complete path from visual perception to movement generation within a unified modeling framework, Dynamic Field Theory. All requisite processes are realized as time-continuous dynamical systems that model the evolution in time of neural population activation. Population level neural processes bring about the attentional selection of objects, the estimation of object shape and pose, and the mapping of pose parameters to suitable movement parameters. Once a target object has been selected, its pose parameters couple into the neural dynamics of movement generation so that changes of pose are propagated through the architecture to update the performed movement online. Implementing the neural architecture on an anthropomorphic robot arm equipped with a Kinect sensor, we evaluate the model by grasping wooden objects. Their size, shape, and pose are estimated from a neural model of scene perception that is based on feature fields. The sequential organization of a reach and grasp act emerges from a sequence of dynamic instabilities within a neural dynamics of behavioral organization, that effectively switches the neural controllers from one phase of the action to the next. Trajectory formation itself is driven by a dynamical systems version of the potential field approach. We highlight the emergent capacity for online updating by showing that a shift or rotation of the object during the reaching phase leads to the online adaptation of the movement plan and successful completion of the grasp. PMID:28303100

Robust input design for nonlinear dynamic modeling of AUV.

PubMed

Nouri, Nowrouz Mohammad; Valadi, Mehrdad

2017-09-01

Input design has a dominant role in developing the dynamic model of autonomous underwater vehicles (AUVs) through system identification. Optimal input design is the process of generating informative inputs that can be used to generate the good quality dynamic model of AUVs. In a problem with optimal input design, the desired input signal depends on the unknown system which is intended to be identified. In this paper, the input design approach which is robust to uncertainties in model parameters is used. The Bayesian robust design strategy is applied to design input signals for dynamic modeling of AUVs. The employed approach can design multiple inputs and apply constraints on an AUV system's inputs and outputs. Particle swarm optimization (PSO) is employed to solve the constraint robust optimization problem. The presented algorithm is used for designing the input signals for an AUV, and the estimate obtained by robust input design is compared with that of the optimal input design. According to the results, proposed input design can satisfy both robustness of constraints and optimality. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

The role of self-determined motivation in job search: A dynamic approach.

PubMed

da Motta Veiga, Serge P; Gabriel, Allison S

2016-03-01

Job search is a dynamic self-regulated process during which job seekers need to stay motivated to secure a job. However, past research has taken a relatively static approach to examining motivation during the job search, in addition to ignoring how the quality of one's motivation--ranging from autonomous to controlled--can influence job search processes. Adopting a within-person perspective, the current study extends self-determination theory (SDT) to the job search context to investigate (a) when autonomous and controlled motivations are more or less prevalent and (b) whether they influence job search effort through metacognitive strategies in differing ways depending upon the amount of time elapsed in the search. In a weekly study of new labor market entrants (Level-2 n = 149; Level-1 n = 691), results indicated that autonomous motivation decreased until the midpoint of the job search and then plateaued, whereas controlled motivation remained stable. Results also showed that autonomous motivation had a consistent, positive relation with metacognitive strategies, whereas the relation between controlled motivation and such strategies was negative early in the job search, but became positive as the job search progressed. Finally, the effects of motivation on job search effort occurred via metacognitive strategies differentially depending upon the time elapsed in the search. Combined, we provide a first glimpse into the dynamics of self-determined motivation on job search processes. (c) 2016 APA, all rights reserved).

Cybersecurity for aerospace autonomous systems

NASA Astrophysics Data System (ADS)

Straub, Jeremy

2015-05-01

High profile breaches have occurred across numerous information systems. One area where attacks are particularly problematic is autonomous control systems. This paper considers the aerospace information system, focusing on elements that interact with autonomous control systems (e.g., onboard UAVs). It discusses the trust placed in the autonomous systems and supporting systems (e.g., navigational aids) and how this trust can be validated. Approaches to remotely detect the UAV compromise, without relying on the onboard software (on a potentially compromised system) as part of the process are discussed. How different levels of autonomy (task-based, goal-based, mission-based) impact this remote characterization is considered.

Insights into the background of autonomic medicine.

PubMed

Laranjo, Sérgio; Geraldes, Vera; Oliveira, Mário; Rocha, Isabel

2017-10-01

Knowledge of the physiology underlying the autonomic nervous system is pivotal for understanding autonomic dysfunction in clinical practice. Autonomic dysfunction may result from primary modifications of the autonomic nervous system or be secondary to a wide range of diseases that cause severe morbidity and mortality. Together with a detailed history and physical examination, laboratory assessment of autonomic function is essential for the analysis of various clinical conditions and the establishment of effective, personalized and precise therapeutic schemes. This review summarizes the main aspects of autonomic medicine that constitute the background of cardiovascular autonomic dysfunction. Copyright © 2017 Sociedade Portuguesa de Cardiologia. Publicado por Elsevier España, S.L.U. All rights reserved.

Algebraic-geometry approach to integrability of birational plane mappings. Integrable birational quadratic reversible mappings. I

NASA Astrophysics Data System (ADS)

Rerikh, K. V.

1998-02-01

Using classic results of algebraic geometry for birational plane mappings in plane CP 2 we present a general approach to algebraic integrability of autonomous dynamical systems in C 2 with discrete time and systems of two autonomous functional equations for meromorphic functions in one complex variable defined by birational maps in C 2. General theorems defining the invariant curves, the dynamics of a birational mapping and a general theorem about necessary and sufficient conditions for integrability of birational plane mappings are proved on the basis of a new idea — a decomposition of the orbit set of indeterminacy points of direct maps relative to the action of the inverse mappings. A general method of generating integrable mappings and their rational integrals (invariants) I is proposed. Numerical characteristics Nk of intersections of the orbits Φn- kOi of fundamental or indeterminacy points Oi ɛ O ∩ S, of mapping Φn, where O = { O i} is the set of indeterminacy points of Φn and S is a similar set for invariant I, with the corresponding set O' ∩ S, where O' = { O' i} is the set of indeterminacy points of inverse mapping Φn-1, are introduced. Using the method proposed we obtain all nine integrable multiparameter quadratic birational reversible mappings with the zero fixed point and linear projective symmetry S = CΛC-1, Λ = diag(±1), with rational invariants generated by invariant straight lines and conics. The relations of numbers Nk with such numerical characteristics of discrete dynamical systems as the Arnold complexity and their integrability are established for the integrable mappings obtained. The Arnold complexities of integrable mappings obtained are determined. The main results are presented in Theorems 2-5, in Tables 1 and 2, and in Appendix A.

Towards autonomous fuzzy control

NASA Technical Reports Server (NTRS)

Shenoi, Sujeet; Ramer, Arthur

1993-01-01

The efficient implementation of on-line adaptation in real time is an important research problem in fuzzy control. The goal is to develop autonomous self-organizing controllers employing system-independent control meta-knowledge which enables them to adjust their control policies depending on the systems they control and the environments in which they operate. An autonomous fuzzy controller would continuously observe system behavior while implementing its control actions and would use the outcomes of these actions to refine its control policy. It could be designed to lie dormant when its control actions give rise to adequate performance characteristics but could rapidly and autonomously initiate real-time adaptation whenever its performance degrades. Such an autonomous fuzzy controller would have immense practical value. It could accommodate individual variations in system characteristics and also compensate for degradations in system characteristics caused by wear and tear. It could also potentially deal with black-box systems and control scenarios. On-going research in autonomous fuzzy control is reported. The ultimate research objective is to develop robust and relatively inexpensive autonomous fuzzy control hardware suitable for use in real time environments.

Impact adding bifurcation in an autonomous hybrid dynamical model of church bell

NASA Astrophysics Data System (ADS)

Brzeski, P.; Chong, A. S. E.; Wiercigroch, M.; Perlikowski, P.

2018-05-01

In this paper we present the bifurcation analysis of the yoke-bell-clapper system which corresponds to the biggest bell "Serce Lodzi" mounted in the Cathedral Basilica of St Stanislaus Kostka, Lodz, Poland. The mathematical model of the system considered in this work has been derived and verified based on measurements of dynamics of the real bell. We perform numerical analysis both by direct numerical integration and path-following method using toolbox ABESPOL (Chong, 2016). By introducing the active yoke the position of the bell-clapper system with respect to the yoke axis of rotation can be easily changed and it can be used to probe the system dynamics. We found a wide variety of periodic and non-periodic solutions, and examined the ranges of coexistence of solutions and transitions between them via different types of bifurcations. Finally, a new type of bifurcation induced by a grazing event - an "impact adding bifurcation" has been proposed. When it occurs, the number of impacts between the bell and the clapper is increasing while the period of the system's motion stays the same.

Dynamic sensitivity analysis of biological systems

PubMed Central

Wu, Wu Hsiung; Wang, Feng Sheng; Chang, Maw Shang

2008-01-01

Background A mathematical model to understand, predict, control, or even design a real biological system is a central theme in systems biology. A dynamic biological system is always modeled as a nonlinear ordinary differential equation (ODE) system. How to simulate the dynamic behavior and dynamic parameter sensitivities of systems described by ODEs efficiently and accurately is a critical job. In many practical applications, e.g., the fed-batch fermentation systems, the system admissible input (corresponding to independent variables of the system) can be time-dependent. The main difficulty for investigating the dynamic log gains of these systems is the infinite dimension due to the time-dependent input. The classical dynamic sensitivity analysis does not take into account this case for the dynamic log gains. Results We present an algorithm with an adaptive step size control that can be used for computing the solution and dynamic sensitivities of an autonomous ODE system simultaneously. Although our algorithm is one of the decouple direct methods in computing dynamic sensitivities of an ODE system, the step size determined by model equations can be used on the computations of the time profile and dynamic sensitivities with moderate accuracy even when sensitivity equations are more stiff than model equations. To show this algorithm can perform the dynamic sensitivity analysis on very stiff ODE systems with moderate accuracy, it is implemented and applied to two sets of chemical reactions: pyrolysis of ethane and oxidation of formaldehyde. The accuracy of this algorithm is demonstrated by comparing the dynamic parameter sensitivities obtained from this new algorithm and from the direct method with Rosenbrock stiff integrator based on the indirect method. The same dynamic sensitivity analysis was performed on an ethanol fed-batch fermentation system with a time-varying feed rate to evaluate the applicability of the algorithm to realistic models with time-dependent admissible input. Conclusion By combining the accuracy we show with the efficiency of being a decouple direct method, our algorithm is an excellent method for computing dynamic parameter sensitivities in stiff problems. We extend the scope of classical dynamic sensitivity analysis to the investigation of dynamic log gains of models with time-dependent admissible input. PMID:19091016

Clustering in Cell Cycle Dynamics with General Response/Signaling Feedback

PubMed Central

Young, Todd R.; Fernandez, Bastien; Buckalew, Richard; Moses, Gregory; Boczko, Erik M.

2011-01-01

Motivated by experimental and theoretical work on autonomous oscillations in yeast, we analyze ordinary differential equations models of large populations of cells with cell-cycle dependent feedback. We assume a particular type of feedback that we call Responsive/Signaling (RS), but do not specify a functional form of the feedback. We study the dynamics and emergent behaviour of solutions, particularly temporal clustering and stability of clustered solutions. We establish the existence of certain periodic clustered solutions as well as “uniform” solutions and add to the evidence that cell-cycle dependent feedback robustly leads to cell-cycle clustering. We highlight the fundamental differences in dynamics between systems with negative and positive feedback. For positive feedback systems the most important mechanism seems to be the stability of individual isolated clusters. On the other hand we find that in negative feedback systems, clusters must interact with each other to reinforce coherence. We conclude from various details of the mathematical analysis that negative feedback is most consistent with observations in yeast experiments. PMID:22001733

System Engineering and Integration of Controls for Advanced Life Support

NASA Technical Reports Server (NTRS)

Overland, David; Hoo, Karlene; Ciskowski, Marvin

2006-01-01

The Advanced Integration Matrix (AIM) project at the Johnson Space Center (JSC) was chartered to study and solve systems-level integration issues for exploration missions. One of the first issues identified was an inability to conduct trade studies on control system architectures due to the absence of mature evaluation criteria. Such architectures are necessary to enable integration of regenerative life support systems. A team was formed to address issues concerning software and hardware architectures and system controls.. The team has investigated what is required to integrate controls for the types of non-linear dynamic systems encountered in advanced life support. To this end, a water processing bioreactor testbed is being developed which will enable prototyping and testing of integration strategies and technologies. Although systems such as the water bioreactors exhibit the complexities of interactions between control schemes most vividly, it is apparent that this behavior and its attendant risks will manifest itself among any set of interdependent autonomous control systems. A methodology for developing integration requirements for interdependent and autonomous systems is a goal of this team and this testbed. This paper is a high-level summary of the current status of the investigation, the issues encountered, some tentative conclusions, and the direction expected for further research.

Control Design and Performance Analysis for Autonomous Formation Flight Experimentss

NASA Astrophysics Data System (ADS)

Rice, Caleb Michael

Autonomous Formation Flight is a key approach for reducing greenhouse gas emissions and managing traffic in future high density airspace. Unmanned Aerial Vehicles (UAV's) have made it possible for the physical demonstration and validation of autonomous formation flight concepts inexpensively and eliminates the flight risk to human pilots. This thesis discusses the design, implementation, and flight testing of three different formation flight control methods, Proportional Integral and Derivative (PID); Fuzzy Logic (FL); and NonLinear Dynamic Inversion (NLDI), and their respective performance behavior. Experimental results show achievable autonomous formation flight and performance quality with a pair of low-cost unmanned research fixed wing aircraft and also with a solo vertical takeoff and landing (VTOL) quadrotor.

Quantifying Effects of Pharmacological Blockers of Cardiac Autonomous Control Using Variability Parameters.

PubMed

Miyabara, Renata; Berg, Karsten; Kraemer, Jan F; Baltatu, Ovidiu C; Wessel, Niels; Campos, Luciana A

2017-01-01

Objective: The aim of this study was to identify the most sensitive heart rate and blood pressure variability (HRV and BPV) parameters from a given set of well-known methods for the quantification of cardiovascular autonomic function after several autonomic blockades. Methods: Cardiovascular sympathetic and parasympathetic functions were studied in freely moving rats following peripheral muscarinic (methylatropine), β1-adrenergic (metoprolol), muscarinic + β1-adrenergic, α1-adrenergic (prazosin), and ganglionic (hexamethonium) blockades. Time domain, frequency domain and symbolic dynamics measures for each of HRV and BPV were classified through paired Wilcoxon test for all autonomic drugs separately. In order to select those variables that have a high relevance to, and stable influence on our target measurements (HRV, BPV) we used Fisher's Method to combine the p -value of multiple tests. Results: This analysis led to the following best set of cardiovascular variability parameters: The mean normal beat-to-beat-interval/value (HRV/BPV: meanNN), the coefficient of variation (cvNN = standard deviation over meanNN) and the root mean square differences of successive (RMSSD) of the time domain analysis. In frequency domain analysis the very-low-frequency (VLF) component was selected. From symbolic dynamics Shannon entropy of the word distribution (FWSHANNON) as well as POLVAR3, the non-linear parameter to detect intermittently decreased variability, showed the best ability to discriminate between the different autonomic blockades. Conclusion: Throughout a complex comparative analysis of HRV and BPV measures altered by a set of autonomic drugs, we identified the most sensitive set of informative cardiovascular variability indexes able to pick up the modifications imposed by the autonomic challenges. These indexes may help to increase our understanding of cardiovascular sympathetic and parasympathetic functions in translational studies of experimental diseases.

A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning.

PubMed

Kappel, David; Legenstein, Robert; Habenschuss, Stefan; Hsieh, Michael; Maass, Wolfgang

2018-01-01

Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is at least as large as the component that depends on the history of pre- and postsynaptic neural activity. These data are inconsistent with common models for network plasticity and raise the following questions: how can neural circuits maintain a stable computational function in spite of these continuously ongoing processes, and what could be functional uses of these ongoing processes? Here, we present a rigorous theoretical framework for these seemingly stochastic spine dynamics and rewiring processes in the context of reward-based learning tasks. We show that spontaneous synapse-autonomous processes, in combination with reward signals such as dopamine, can explain the capability of networks of neurons in the brain to configure themselves for specific computational tasks, and to compensate automatically for later changes in the network or task. Furthermore, we show theoretically and through computer simulations that stable computational performance is compatible with continuously ongoing synapse-autonomous changes. After reaching good computational performance it causes primarily a slow drift of network architecture and dynamics in task-irrelevant dimensions, as observed for neural activity in motor cortex and other areas. On the more abstract level of reinforcement learning the resulting model gives rise to an understanding of reward-driven network plasticity as continuous sampling of network configurations.

A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning

PubMed Central

Habenschuss, Stefan; Hsieh, Michael

2018-01-01

Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is at least as large as the component that depends on the history of pre- and postsynaptic neural activity. These data are inconsistent with common models for network plasticity and raise the following questions: how can neural circuits maintain a stable computational function in spite of these continuously ongoing processes, and what could be functional uses of these ongoing processes? Here, we present a rigorous theoretical framework for these seemingly stochastic spine dynamics and rewiring processes in the context of reward-based learning tasks. We show that spontaneous synapse-autonomous processes, in combination with reward signals such as dopamine, can explain the capability of networks of neurons in the brain to configure themselves for specific computational tasks, and to compensate automatically for later changes in the network or task. Furthermore, we show theoretically and through computer simulations that stable computational performance is compatible with continuously ongoing synapse-autonomous changes. After reaching good computational performance it causes primarily a slow drift of network architecture and dynamics in task-irrelevant dimensions, as observed for neural activity in motor cortex and other areas. On the more abstract level of reinforcement learning the resulting model gives rise to an understanding of reward-driven network plasticity as continuous sampling of network configurations. PMID:29696150

Information for Successful Interaction with Autonomous Systems

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Johnson, Kathy A.

2003-01-01

Interaction in heterogeneous mission operations teams is not well matched to classical models of coordination with autonomous systems. We describe methods of loose coordination and information management in mission operations. We describe an information agent and information management tool suite for managing information from many sources, including autonomous agents. We present an integrated model of levels of complexity of agent and human behavior, which shows types of information processing and points of potential error in agent activities. We discuss the types of information needed for diagnosing problems and planning interactions with an autonomous system. We discuss types of coordination for which designs are needed for autonomous system functions.

A Low Cost Approach to Simultaneous Orbit, Attitude, and Rate Estimation Using an Extended Kalman Filter

NASA Technical Reports Server (NTRS)

Deutschmann, Julie; Harman, Rick; Bar-Itzhack, Itzhack

1998-01-01

An innovative approach to autonomous attitude and trajectory estimation is available using only magnetic field data and rate data. The estimation is performed simultaneously using an Extended Kalman Filter, a well known algorithm used extensively in onboard applications. The magnetic field is measured on a satellite by a magnetometer, an inexpensive and reliable sensor flown on virtually all satellites in low earth orbit. Rate data is provided by a gyro, which can be costly. This system has been developed and successfully tested in a post-processing mode using magnetometer and gyro data from 4 satellites supported by the Flight Dynamics Division at Goddard. In order for this system to be truly low cost, an alternative source for rate data must be utilized. An independent system which estimate spacecraft rate has been successfully developed and tested using only magnetometer data or a combination of magnetometer data and sun sensor data, which is less costly than a gyro. This system also uses an Extended Kalman Filter. Merging the two systems will provide an extremely low cost, autonomous approach to attitude and trajectory estimation. In this work we provide the theoretical background of the combined system. The measurement matrix is developed by combining the measurement matrix of the orbit and attitude estimation EKF with the measurement matrix of the rate estimation EKF, which is composed of a pseudo-measurement which makes the effective measurement a function of the angular velocity. Associated with this is the development of the noise covariance matrix associated with the original measurement combined with the new pseudo-measurement. In addition, the combination of the dynamics from the two systems is presented along with preliminary test results.

A low cost approach to simultaneous orbit, attitude, and rate estimation using an extended Kalman filter

NASA Technical Reports Server (NTRS)

Deutschmann, Julie; Harman, Rick; Bar-Itzhack, Itzhack

1998-01-01

An innovative approach to autonomous attitude and trajectory estimation is available using only magnetic field data and rate data. The estimation is performed simultaneously using an Extended Kalman Filter (EKF), a well known algorithm used extensively in onboard applications. The magnetic field is measured on a satellite by a magnetometer, an inexpensive and reliable sensor flown on virtually all satellites in low earth orbit. Rate data is provided by a gyro, which can be costly. This system has been developed and successfully tested in a post-processing mode using magnetometer and gyro data from 4 satellites supported by the Flight Dynamics Division at Goddard. In order for this system to be truly low cost, an alternative source for rate data must be utilized. An independent system which estimates spacecraft rate has been successfully developed and tested using only magnetometer data or a combination of magnetometer data and sun sensor data, which is less costly than a gyro. This system also uses an EKF. Merging the two systems will provide an extremely low cost, autonomous approach to attitude and trajectory estimation. In this work we provide the theoretical background of the combined system. The measurement matrix is developed by combining the measurement matrix of the orbit and attitude estimation EKF with the measurement matrix of the rate estimation EKF, which is composed of a pseudo-measurement which makes the effective measurement a function of the angular velocity. Associated with this is the development of the noise covariance matrix associated with the original measurement combined with the new pseudo-measurement. In addition, the combination of the dynamics from the two systems is presented along with preliminary test results.

Mathematics of Web science: structure, dynamics and incentives.

PubMed

Chayes, Jennifer

2013-03-28

Dr Chayes' talk described how, to a discrete mathematician, 'all the world's a graph, and all the people and domains merely vertices'. A graph is represented as a set of vertices V and a set of edges E, so that, for instance, in the World Wide Web, V is the set of pages and E the directed hyperlinks; in a social network, V is the people and E the set of relationships; and in the autonomous system Internet, V is the set of autonomous systems (such as AOL, Yahoo! and MSN) and E the set of connections. This means that mathematics can be used to study the Web (and other large graphs in the online world) in the following way: first, we can model online networks as large finite graphs; second, we can sample pieces of these graphs; third, we can understand and then control processes on these graphs; and fourth, we can develop algorithms for these graphs and apply them to improve the online experience.

Adjustably Autonomous Multi-agent Plan Execution with an Internal Spacecraft Free-Flying Robot Prototype

NASA Technical Reports Server (NTRS)

Dorais, Gregory A.; Nicewarner, Keith

2006-01-01

We present an multi-agent model-based autonomy architecture with monitoring, planning, diagnosis, and execution elements. We discuss an internal spacecraft free-flying robot prototype controlled by an implementation of this architecture and a ground test facility used for development. In addition, we discuss a simplified environment control life support system for the spacecraft domain also controlled by an implementation of this architecture. We discuss adjustable autonomy and how it applies to this architecture. We describe an interface that provides the user situation awareness of both autonomous systems and enables the user to dynamically edit the plans prior to and during execution as well as control these agents at various levels of autonomy. This interface also permits the agents to query the user or request the user to perform tasks to help achieve the commanded goals. We conclude by describing a scenario where these two agents and a human interact to cooperatively detect, diagnose and recover from a simulated spacecraft fault.

Artificial Neural Network Based Mission Planning Mechanism for Spacecraft

NASA Astrophysics Data System (ADS)

Li, Zhaoyu; Xu, Rui; Cui, Pingyuan; Zhu, Shengying

2018-04-01

The ability to plan and react fast in dynamic space environments is central to intelligent behavior of spacecraft. For space and robotic applications, many planners have been used. But it is difficult to encode the domain knowledge and directly use existing techniques such as heuristic to improve the performance of the application systems. Therefore, regarding planning as an advanced control problem, this paper first proposes an autonomous mission planning and action selection mechanism through a multiple layer perceptron neural network approach to select actions in planning process and improve efficiency. To prove the availability and effectiveness, we use autonomous mission planning problems of the spacecraft, which is a sophisticated system with complex subsystems and constraints as an example. Simulation results have shown that artificial neural networks (ANNs) are usable for planning problems. Compared with the existing planning method in EUROPA, the mechanism using ANNs is more efficient and can guarantee stable performance. Therefore, the mechanism proposed in this paper is more suitable for planning problems of spacecraft that require real time and stability.

Autonomous Research Vessels for Adaptive Upper-Ocean Process Studies

DTIC Science & Technology

2014-09-30

system with the goal  of extending  its mission robustness,  adaptabilit and science capabilities beyond that  of the   Arduino -­‐ based ones... measure the interplay between these finescale dynamics and turbulence, which ultimately drives  the  irreversible  heat/freshwater  transports...profiling in Greenland  Fjords. acquiring CTD cast (and ADCP profiles) within m of a Greenland iceberg.APPROACH: Our first ARV (ARV Rob) was based on

The TRIDEC System-of-Systems; Choreography of large-scale concurrent tasks in Natural Crisis Management

NASA Astrophysics Data System (ADS)

Häner, R.; Wächter, J.

2012-04-01

The project Collaborative, Complex, and Critical Decision-Support in Evolving Crises (TRIDEC), co-funded by the European Commission in its Seventh Framework Programme aims at establishing a network of dedicated, autonomous legacy systems for large-scale concurrent management of natural crises utilising heterogeneous information resources. TRIDEC's architecture reflects the System-of- Systems (SoS) approach which is based on task-oriented systems, cooperatively interacting as a collective in a common environment. The design of the TRIDEC-SoS follows the principles of service-oriented and event-driven architectures (SOA & EDA) exceedingly focusing on a loose coupling of the systems. The SoS approach in combination with SOA and EDA has the distinction of being able to provide novel and coherent behaviours and features resulting from a process of dynamic self-organisation. Self-organisation is a process without the need for a central or external coordinator controlling it through orchestration. It is the result of enacted concurrent tasks in a collaborative environment of geographically distributed systems. Although the individual systems act completely autonomously, their interactions expose emergent structures of evolving nature. Particularly, the fact is important that SoS are inherently able to evolve on all facets of intelligent information management. This includes adaptive properties, e.g. seamless integration of new resource types or the adoption of new fields in natural crisis management. In the case of TRIDEC with various heterogeneous participants involved, concurrent information processing is of fundamental importance because of the achievable improvements regarding cooperative decision making. Collaboration within TRIDEC will be implemented with choreographies and conversations. Choreographies specify the expected behaviour between two or more participants; conversations describe the message exchange between all participants emphasising their logical relation. The TRIDEC choreography will be based on the definition of Behavioural Interfaces and Service Level Agreements, which describe the interactions of all participants involved in the collaborative process by binding the tasks of dedicated systems to high-level business processes. All methods of a Behavioural Interfaces can be assigned dynamically to the activities of a business process. This allows it to utilise a system during the run-time of a business process and thus, for example enabling task balancing or the delegation of responsibilities. Since the individual parts of a SoS are normally managed independently and operate autonomously because of their geographical distribution it is of vital importance to ensure the reliability (robustness and correctness) of their interactions which will be achieved by applying the Design by Contract (DbC) approach to the TRIDEC architecture. Key challenge for TRIDEC is establishing a reliable adaptive system which exposes an emergent behaviour, for example intelligent monitoring strategies or dynamic system adaptions even in case of partly system failures. It is essential for TRIDEC that for example redundant parts of the system can take over tasks from defect components in a process of re-organising its network.

Bifurcation analysis of an automatic dynamic balancing mechanism for eccentric rotors

NASA Astrophysics Data System (ADS)

Green, K.; Champneys, A. R.; Lieven, N. J.

2006-04-01

We present a nonlinear bifurcation analysis of the dynamics of an automatic dynamic balancing mechanism for rotating machines. The principle of operation is to deploy two or more masses that are free to travel around a race at a fixed distance from the hub and, subsequently, balance any eccentricity in the rotor. Mathematically, we start from a Lagrangian description of the system. It is then shown how under isotropic conditions a change of coordinates into a rotating frame turns the problem into a regular autonomous dynamical system, amenable to a full nonlinear bifurcation analysis. Using numerical continuation techniques, curves are traced of steady states, limit cycles and their bifurcations as parameters are varied. These results are augmented by simulations of the system trajectories in phase space. Taking the case of a balancer with two free masses, broad trends are revealed on the existence of a stable, dynamically balanced steady-state solution for specific rotation speeds and eccentricities. However, the analysis also reveals other potentially attracting states—non-trivial steady states, limit cycles, and chaotic motion—which are not in balance. The transient effects which lead to these competing states, which in some cases coexist, are investigated.

Effects of automation and task load on task switching during human supervision of multiple semi-autonomous robots in a dynamic environment.

PubMed

Squire, P N; Parasuraman, R

2010-08-01

The present study assessed the impact of task load and level of automation (LOA) on task switching in participants supervising a team of four or eight semi-autonomous robots in a simulated 'capture the flag' game. Participants were faster to perform the same task than when they chose to switch between different task actions. They also took longer to switch between different tasks when supervising the robots at a high compared to a low LOA. Task load, as manipulated by the number of robots to be supervised, did not influence switch costs. The results suggest that the design of future unmanned vehicle (UV) systems should take into account not simply how many UVs an operator can supervise, but also the impact of LOA and task operations on task switching during supervision of multiple UVs. The findings of this study are relevant for the ergonomics practice of UV systems. This research extends the cognitive theory of task switching to inform the design of UV systems and results show that switching between UVs is an important factor to consider.

Autonomous oscillation in supramolecular assemblies: Role of free energy landscape and fluctuations

NASA Astrophysics Data System (ADS)

Sereda, Yuriy V.; Ortoleva, Peter J.

2015-11-01

Molecular dynamics studies demonstrated that a supramolecular assembly can express autonomous structural oscillations about equilibrium. It is demonstrated here that for nanosystems such oscillations can result from the interplay of free energy landscape and structural fluctuations. Furthermore, these oscillations have intermittent character, reflecting the conflict between a tendency to oscillate due to features in the free energy landscape, and the Second Law's repression of perpetual oscillation in an isothermal, equilibrium system. The demonstration system is a T = 1 icosahedral structure constituted of 12 protein pentamers in contact with a bath at fixed temperature. The oscillations are explained in terms of a Langevin model accounting for interactions among neighboring pentamers. The model is based on a postulated free energy landscape in the 24-dimensional space of variables describing the centrifugal and rotational motion of each pentamer. The model includes features such as basins of attraction and low free energy corridors. When the system is driven slightly out of equilibrium, the oscillations are transformed into a limit cycle, as expressed in terms of power spectrum narrowing.

Engineering Review of ANCAUS/AVATAR: An Enabling Technology for the Autonomous Land Systems Program?

DTIC Science & Technology

2003-12-01

technology for future Autonomous Land System (ALS) autonomous vehicles . Since 1989, forward thinking engineering has characterized the history of ANC/EUS and...technology for future autonomous vehicles and that; (2) ALS should adopt commercial/open source technology to support a new ALS architecture and (3) ALS

Autonomous Agents: The Origins and Co-Evolution of Reproducing Molecular Systems

NASA Technical Reports Server (NTRS)

Kauffman, Stuart

1999-01-01

The central aim of this award concerned an investigation into, and adequate formulation of, the concept of an "autonomous agent." If we consider a bacterium swimming upstream in a glucose gradient, we are willing to say of the bacterium that it is going to get food. That is, we are willing, and do, describe the bacterium as acting on its own behalf in an environment. All free living cells are, in this sense, autonomous agents. But the bacterium is "just" a set of molecules. We define an autonomous agent as a physical system able to act on its own behalf in an environment, then ask, "What must a physical system be to be an autonomous agent?" The tentative definition for a molecular autonomous agent is that it must be self-reproducing and carry out at least one thermodynamic work cycle. The work carried out in this grant involved, among other features, the development of a detailed model of a molecular autonomous agent, and study of the kinetics of this system. In particular, a molecular autonomous agent must, by the above tentative definition, not only reproduce, but must carry out at least one work cycle. I took, as a simple example of a self-reproducing molecular system, the single-stranded DNA hexamer 3'CCGCGG5' which can line up and ligate its two complementary trimers, 5'CCG3' and 5'CGG3'. But the two ligated trimers constitute the same molecular sequence in the 3' to 5' direction as the initial hexamer, hence this system is autocatalytic. On the other hand the above system is not yet an autonomous agent. At the minimum, autonomous agents, as I have defined them, are a new class of chemical reaction network. At a maximum, they may constitute a proper definition of life itself.

Teaching Cardiac Autonomic Function Dynamics Employing the Valsalva (Valsalva-Weber) Maneuver

ERIC Educational Resources Information Center

Junqueira, Luiz Fernando, Jr.

2008-01-01

In this report, a brief history of the Valsalva (Valsalva-Weber) maneuver is outlined, followed by an explanation on the use of this approach for the evaluation of cardiac autonomic function based on underlying heart rate changes. The most important methodological and interpretative aspects of the Valsalva-Weber maneuver are critically updated,…

Developing operation algorithms for vision subsystems in autonomous mobile robots

NASA Astrophysics Data System (ADS)

Shikhman, M. V.; Shidlovskiy, S. V.

2018-05-01

The paper analyzes algorithms for selecting keypoints on the image for the subsequent automatic detection of people and obstacles. The algorithm is based on the histogram of oriented gradients and the support vector method. The combination of these methods allows successful selection of dynamic and static objects. The algorithm can be applied in various autonomous mobile robots.

A Universal Definition of Life: Autonomy and Open-Ended Evolution

NASA Astrophysics Data System (ADS)

Ruiz-Mirazo, Kepa; Peretó, Juli; Moreno, Alvaro

2004-06-01

Life is a complex phenomenon that not only requires individual self-producing and self-sustaining systems but also a historical-collective organization of those individual systems, which brings about characteristic evolutionary dynamics. On these lines, we propose to define universally living beings as autonomous systems with open-ended evolution capacities, and we claim that all such systems must have a semi-permeable active boundary (membrane), an energy transduction apparatus (set of energy currencies) and, at least, two types of functionally interdependent macromolecular components (catalysts and records). The latter is required to articulate a `phenotype-genotype' decoupling that leads to a scenario where the global network of autonomous systems allows for an open-ended increase in the complexity of the individual agents. Thus, the basic-individual organization of biological systems depends critically on being instructed by patterns (informational records) whose generation and reliable transmission cannot be explained but take into account the complete historical network of relationships among those systems. We conclude that a proper definition of life should consider both levels, individual and collective: living systems cannot be fully constituted without being part of the evolutionary process of a whole ecosystem. Finally, we also discuss a few practical implications of the definition for different programs of research.

Instantons re-examined: dynamical tunneling and resonant tunneling.

PubMed

Le Deunff, Jérémy; Mouchet, Amaury

2010-04-01

Starting from trace formulas for the tunneling splittings (or decay rates) analytically continued in the complex time domain, we obtain explicit semiclassical expansions in terms of complex trajectories that are selected with appropriate complex-time paths. We show how this instantonlike approach, which takes advantage of an incomplete Wick rotation, accurately reproduces tunneling effects not only in the usual double-well potential but also in situations where a pure Wick rotation is insufficient, for instance dynamical tunneling or resonant tunneling. Even though only one-dimensional autonomous Hamiltonian systems are quantitatively studied, we discuss the relevance of our method for multidimensional and/or chaotic tunneling.

A Power Regulation and Droop Mode Control Method for a Stand-Alone Load Fed from a PV-Current Source Inverter

NASA Astrophysics Data System (ADS)

Khayamy, Mehdy; Ojo, Olorunfemi

2015-04-01

A current source inverter fed from photovoltaic cells is proposed to power an autonomous load when operating under either power regulation or voltage and frequency drooping modes. Input-output linearization technique is applied to the overall nonlinear system to achieve a globally stable system under feasible operating conditions. After obtaining the steady-state model that demarcates the modes of operation, computer Simulation results for variations in irradiance and the load power of the controlled system are generated in which an acceptable dynamic response of the power generator system under the two modes of operation is observed.

Crash response data system for the controlled impact demonstration (CID) of a full scale transport aircraft

NASA Astrophysics Data System (ADS)

Calloway, Raymond S.; Knight, Vernie H., Jr.

NASA Langley's Crash Response Data System (CRDS) which is designed to acquire aircraft structural and anthropomorphic dummy responses during the full-scale transport CID test is described. Included in the discussion are the system design approach, details on key instrumentation subsystems and operations, overall instrumentation crash performance, and data recovery results. Two autonomous high-environment digital flight instrumentation systems, DAS 1 and DAS 2, were employed to obtain research data from various strain gage, accelerometer, and tensiometric sensors installed in the B-720 test aircraft. The CRDS successfully acquired 343 out of 352 measurements of dynamic crash data.

Dynamic characteristics of a 20 kHz resonant power system - Fault identification and fault recovery

NASA Technical Reports Server (NTRS)

Wasynczuk, O.

1988-01-01

A detailed simulation of a dc inductor resonant driver and receiver is used to demonstrate the transient characteristics of a 20 kHz resonant power system during fault and overload conditions. The simulated system consists of a dc inductor resonant inverter (driver), a 50-meter transmission cable, and a dc inductor resonant receiver load. Of particular interest are the driver and receiver performance during fault and overload conditions and on the recovery characteristics following removal of the fault. The information gained from these studies sets the stage for further work in fault identification and autonomous power system control.

Autonomous dynamic obstacle avoidance for bacteria-powered microrobots (BPMs) with modified vector field histogram

PubMed Central

Kim, Hoyeon; Cheang, U. Kei

2017-01-01

In order to broaden the use of microrobots in practical fields, autonomous control algorithms such as obstacle avoidance must be further developed. However, most previous studies of microrobots used manual motion control to navigate past tight spaces and obstacles while very few studies demonstrated the use of autonomous motion. In this paper, we demonstrated a dynamic obstacle avoidance algorithm for bacteria-powered microrobots (BPMs) using electric field in fluidic environments. A BPM consists of an artificial body, which is made of SU-8, and a high dense layer of harnessed bacteria. BPMs can be controlled using externally applied electric fields due to the electrokinetic property of bacteria. For developing dynamic obstacle avoidance for BPMs, a kinematic model of BPMs was utilized to prevent collision and a finite element model was used to characteristic the deformation of an electric field near the obstacle walls. In order to avoid fast moving obstacles, we modified our previously static obstacle avoidance approach using a modified vector field histogram (VFH) method. To validate the advanced algorithm in experiments, magnetically controlled moving obstacles were used to intercept the BPMs as the BPMs move from the initial position to final position. The algorithm was able to successfully guide the BPMs to reach their respective goal positions while avoiding the dynamic obstacles. PMID:29020016

Autonomous dynamic obstacle avoidance for bacteria-powered microrobots (BPMs) with modified vector field histogram.

PubMed

Kim, Hoyeon; Cheang, U Kei; Kim, Min Jun

2017-01-01

In order to broaden the use of microrobots in practical fields, autonomous control algorithms such as obstacle avoidance must be further developed. However, most previous studies of microrobots used manual motion control to navigate past tight spaces and obstacles while very few studies demonstrated the use of autonomous motion. In this paper, we demonstrated a dynamic obstacle avoidance algorithm for bacteria-powered microrobots (BPMs) using electric field in fluidic environments. A BPM consists of an artificial body, which is made of SU-8, and a high dense layer of harnessed bacteria. BPMs can be controlled using externally applied electric fields due to the electrokinetic property of bacteria. For developing dynamic obstacle avoidance for BPMs, a kinematic model of BPMs was utilized to prevent collision and a finite element model was used to characteristic the deformation of an electric field near the obstacle walls. In order to avoid fast moving obstacles, we modified our previously static obstacle avoidance approach using a modified vector field histogram (VFH) method. To validate the advanced algorithm in experiments, magnetically controlled moving obstacles were used to intercept the BPMs as the BPMs move from the initial position to final position. The algorithm was able to successfully guide the BPMs to reach their respective goal positions while avoiding the dynamic obstacles.

Swarm autonomic agents with self-destruct capability

NASA Technical Reports Server (NTRS)

Hinchey, Michael G. (Inventor); Sterritt, Roy (Inventor)

2009-01-01

Systems, methods and apparatus are provided through which in some embodiments an autonomic entity manages a system by generating one or more stay alive signals based on the functioning status and operating state of the system. In some embodiments, an evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy. The evolvable neural interface receives and generates heartbeat monitor signals and pulse monitor signals that are used to generate a stay alive signal that is used to manage the operations of the synthetic neural system. In another embodiment an asynchronous Alice signal (Autonomic license) requiring valid credentials of an anonymous autonomous agent is initiated. An unsatisfactory Alice exchange may lead to self-destruction of the anonymous autonomous agent for self-protection.

Swarm autonomic agents with self-destruct capability

NASA Technical Reports Server (NTRS)

Hinchey, Michael G. (Inventor); Sterritt, Roy (Inventor)

2011-01-01

Systems, methods and apparatus are provided through which in some embodiments an autonomic entity manages a system by generating one or more stay alive signals based on the functioning status and operating state of the system. In some embodiments, an evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy. The evolvable neural interface receives and generates heartbeat monitor signals and pulse monitor signals that are used to generate a stay alive signal that is used to manage the operations of the synthetic neural system. In another embodiment an asynchronous Alice signal (Autonomic license) requiring valid credentials of an anonymous autonomous agent is initiated. An unsatisfactory Alice exchange may lead to self-destruction of the anonymous autonomous agent for self-protection.

Graphical coding data and operational guidance for implementation or modification of a LabVIEW®-based pHstat system for the cultivation of microalgae.

PubMed

Golda, Rachel L; Golda, Mark D; Peterson, Tawnya D; Needoba, Joseph A

2017-06-01

The influence of pH on phytoplankton physiology is an important facet of the body of research on ocean acidification. We provide data developed during the design and implementation of a novel pHstat system capable of maintaining both static and dynamic pH environments in a laboratory setting. These data both help improve functionality of the system, and provide specific coding blocks for controlling the pHstat using a LabVIEW® virtual instrument (VI). The data in this paper support the research article "Development of an economical, autonomous pHstat system for culturing phytoplankton under steady state or dynamic conditions" (Golda et al. [2]). These data will be of interest to researchers studying the effects of changing pH on phytoplankton in a laboratory context, and to those desiring to build their own pHstat system(s). These data can also be used to facilitate modification of the pHstat system to control salinity, temperature, or other environmental factors.

Analysis, synchronisation and circuit design of a new highly nonlinear chaotic system

NASA Astrophysics Data System (ADS)

Mobayen, Saleh; Kingni, Sifeu Takougang; Pham, Viet-Thanh; Nazarimehr, Fahimeh; Jafari, Sajad

2018-02-01

This paper investigates a three-dimensional autonomous chaotic flow without linear terms. Dynamical behaviour of the proposed system is investigated through eigenvalue structures, phase portraits, bifurcation diagram, Lyapunov exponents and basin of attraction. For a suitable choice of the parameters, the proposed system can exhibit anti-monotonicity, periodic oscillations and double-scroll chaotic attractor. Basin of attraction of the proposed system shows that the chaotic attractor is self-excited. Furthermore, feasibility of double-scroll chaotic attractor in the real word is investigated by using the OrCAD-PSpice software via an electronic implementation of the proposed system. A good qualitative agreement is illustrated between the numerical simulations and the OrCAD-PSpice results. Finally, a finite-time control method based on dynamic sliding surface for the synchronisation of master and slave chaotic systems in the presence of external disturbances is performed. Using the suggested control technique, the superior master-slave synchronisation is attained. Illustrative simulation results on the studied chaotic system are presented to indicate the effectiveness of the suggested scheme.

Mission Level Autonomy for USSV

NASA Technical Reports Server (NTRS)

Huntsberger, Terry; Stirb, Robert C.; Brizzolara, Robert

2011-01-01

On-water demonstration of a wide range of mission-proven, advanced technologies at TRL 5+ that provide a total integrated, modular approach to effectively address the majority of the key needs for full mission-level autonomous, cross-platform control of USV s. Wide baseline stereo system mounted on the ONR USSV was shown to be an effective sensing modality for tracking of dynamic contacts as a first step to automated retrieval operations. CASPER onboard planner/replanner successfully demonstrated realtime, on-water resource-based analysis for mission-level goal achievement and on-the-fly opportunistic replanning. Full mixed mode autonomy was demonstrated on-water with a seamless transition between operator over-ride and return to current mission plan. Autonomous cooperative operations for fixed asset protection and High Value Unit escort using 2 USVs (AMN1 & 14m RHIB) were demonstrated during Trident Warrior 2010 in JUN 2010

Systems, methods and apparatus for quiesence of autonomic safety devices with self action

NASA Technical Reports Server (NTRS)

Hinchey, Michael G. (Inventor); Sterritt, Roy (Inventor)

2011-01-01

Systems, methods and apparatus are provided through which in some embodiments an autonomic environmental safety device may be quiesced. In at least one embodiment, a method for managing an autonomic safety device, such as a smoke detector, based on functioning state and operating status of the autonomic safety device includes processing received signals from the autonomic safety device to obtain an analysis of the condition of the autonomic safety device, generating one or more stay-awake signals based on the functioning status and the operating state of the autonomic safety device, transmitting the stay-awake signal, transmitting self health/urgency data, and transmitting environment health/urgency data. A quiesce component of an autonomic safety device can render the autonomic safety device inactive for a specific amount of time or until a challenging situation has passed.

Hair-based sensors for micro-autonomous systems

NASA Astrophysics Data System (ADS)

Sadeghi, Mahdi M.; Peterson, Rebecca L.; Najafi, Khalil

2012-06-01

We seek to harness microelectromechanical systems (MEMS) technologies to build biomimetic devices for low-power, high-performance, robust sensors and actuators on micro-autonomous robot platforms. Hair is used abundantly in nature for a variety of functions including balance and inertial sensing, flow sensing and aerodynamic (air foil) control, tactile and touch sensing, insulation and temperature control, particle filtering, and gas/chemical sensing. Biological hairs, which are typically characterized by large surface/volume ratios and mechanical amplification of movement, can be distributed in large numbers over large areas providing unprecedented sensitivity, redundancy, and stability (robustness). Local neural transduction allows for space- and power-efficient signal processing. Moreover by varying the hair structure and transduction mechanism, the basic hair form can be used for a wide diversity of functions. In this paper, by exploiting a novel wafer-level, bubble-free liquid encapsulation technology, we make arrays of micro-hydraulic cells capable of electrostatic actuation and hydraulic amplification, which enables high force/high deflection actuation and extremely sensitive detection (sensing) at low power. By attachment of cilia (hair) to the micro-hydraulic cell, air flow sensors with excellent sensitivity (< few cm/s) and dynamic range (> 10 m/s) have been built. A second-generation design has significantly reduced the sensor response time while maintaining sensitivity of about 2 cm/s and dynamic range of more than 15 m/s. These sensors can be used for dynamic flight control of flying robots or for situational awareness in surveillance applications. The core biomimetic technologies developed are applicable to a broad range of sensors and actuators.

A Self-Tuning Kalman Filter for Autonomous Spacecraft Navigation

NASA Technical Reports Server (NTRS)

Truong, Son H.

1998-01-01

Most navigation systems currently operated by NASA are ground-based, and require extensive support to produce accurate results. Recently developed systems that use Kalman Filter and Global Positioning System (GPS) data for orbit determination greatly reduce dependency on ground support, and have potential to provide significant economies for NASA spacecraft navigation. Current techniques of Kalman filtering, however, still rely on manual tuning from analysts, and cannot help in optimizing autonomy without compromising accuracy and performance. This paper presents an approach to produce a high accuracy autonomous navigation system fully integrated with the flight system. The resulting system performs real-time state estimation by using an Extended Kalman Filter (EKF) implemented with high-fidelity state dynamics model, as does the GPS Enhanced Orbit Determination Experiment (GEODE) system developed by the NASA Goddard Space Flight Center. Augmented to the EKF is a sophisticated neural-fuzzy system, which combines the explicit knowledge representation of fuzzy logic with the learning power of neural networks. The fuzzy-neural system performs most of the self-tuning capability and helps the navigation system recover from estimation errors. The core requirement is a method of state estimation that handles uncertainties robustly, capable of identifying estimation problems, flexible enough to make decisions and adjustments to recover from these problems, and compact enough to run on flight hardware. The resulting system can be extended to support geosynchronous spacecraft and high-eccentricity orbits. Mathematical methodology, systems and operations concepts, and implementation of a system prototype are presented in this paper. Results from the use of the prototype to evaluate optimal control algorithms implemented are discussed. Test data and major control issues (e.g., how to define specific roles for fuzzy logic to support the self-learning capability) are also discussed. In addition, architecture of a complete end-to-end candidate flight system that provides navigation with highly autonomous control using data from GPS is presented.

Infrared Free Space Communication - The Autonomous Testing of Free Space Infrared Communication

NASA Technical Reports Server (NTRS)

Heldman, Christopher

2017-01-01

Fiber optics has been a winning player in the game of high-speed communication and data transfer in cable connections. Yet, in free space RF has been the repeated choice of communication medium of the space industry. Investigating the benefits of free space optical communication over radio frequency is worthwhile. An increase in science data rate return capabilities could occur if optical communication is implemented. Optical communication systems also provide efficiencies in power, mass, and volume over RF systems1. Optical communication systems have been demonstrated from a satellite in orbit with the moon to earth, and resulted in the highest data rates ever seen through space (622Mbps)2. Because of these benefits, optical communication is far superior to RF. The HiDRA (High Data Rate Architecture) project is researching Passive Misalignment Mitigation of Dynamic Free Apace Optical Communication Links. The goal of this effort is to enable gigabit per second transmission of data in short range dynamic links (less than 100 meters). In practice this would enhance data rates between sites on the International Space Station with minimal size, weight, and power requirements. This paper will focus on an autonomous code and a hardware setup that will be used to fulfill the next step in the research being conducted. The free space optical communications pointing downfalls will be investigated. This was achieved by creating 5 python programs and a top-level code to automate this test.

Amplifying human ability through autonomics and machine learning in IMPACT

NASA Astrophysics Data System (ADS)

Dzieciuch, Iryna; Reeder, John; Gutzwiller, Robert; Gustafson, Eric; Coronado, Braulio; Martinez, Luis; Croft, Bryan; Lange, Douglas S.

2017-05-01

Amplifying human ability for controlling complex environments featuring autonomous units can be aided by learned models of human and system performance. In developing a command and control system that allows a small number of people to control a large number of autonomous teams, we employ an autonomics framework to manage the networks that represent mission plans and the networks that are composed of human controllers and their autonomous assistants. Machine learning allows us to build models of human and system performance useful for monitoring plans and managing human attention and task loads. Machine learning also aids in the development of tactics that human supervisors can successfully monitor through the command and control system.

Detection of bifurcations in noisy coupled systems from multiple time series

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williamson, Mark S., E-mail: m.s.williamson@exeter.ac.uk; Lenton, Timothy M.

We generalize a method of detecting an approaching bifurcation in a time series of a noisy system from the special case of one dynamical variable to multiple dynamical variables. For a system described by a stochastic differential equation consisting of an autonomous deterministic part with one dynamical variable and an additive white noise term, small perturbations away from the system's fixed point will decay slower the closer the system is to a bifurcation. This phenomenon is known as critical slowing down and all such systems exhibit this decay-type behaviour. However, when the deterministic part has multiple coupled dynamical variables, themore » possible dynamics can be much richer, exhibiting oscillatory and chaotic behaviour. In our generalization to the multi-variable case, we find additional indicators to decay rate, such as frequency of oscillation. In the case of approaching a homoclinic bifurcation, there is no change in decay rate but there is a decrease in frequency of oscillations. The expanded method therefore adds extra tools to help detect and classify approaching bifurcations given multiple time series, where the underlying dynamics are not fully known. Our generalisation also allows bifurcation detection to be applied spatially if one treats each spatial location as a new dynamical variable. One may then determine the unstable spatial mode(s). This is also something that has not been possible with the single variable method. The method is applicable to any set of time series regardless of its origin, but may be particularly useful when anticipating abrupt changes in the multi-dimensional climate system.« less

Detection of bifurcations in noisy coupled systems from multiple time series

NASA Astrophysics Data System (ADS)

Williamson, Mark S.; Lenton, Timothy M.

2015-03-01

We generalize a method of detecting an approaching bifurcation in a time series of a noisy system from the special case of one dynamical variable to multiple dynamical variables. For a system described by a stochastic differential equation consisting of an autonomous deterministic part with one dynamical variable and an additive white noise term, small perturbations away from the system's fixed point will decay slower the closer the system is to a bifurcation. This phenomenon is known as critical slowing down and all such systems exhibit this decay-type behaviour. However, when the deterministic part has multiple coupled dynamical variables, the possible dynamics can be much richer, exhibiting oscillatory and chaotic behaviour. In our generalization to the multi-variable case, we find additional indicators to decay rate, such as frequency of oscillation. In the case of approaching a homoclinic bifurcation, there is no change in decay rate but there is a decrease in frequency of oscillations. The expanded method therefore adds extra tools to help detect and classify approaching bifurcations given multiple time series, where the underlying dynamics are not fully known. Our generalisation also allows bifurcation detection to be applied spatially if one treats each spatial location as a new dynamical variable. One may then determine the unstable spatial mode(s). This is also something that has not been possible with the single variable method. The method is applicable to any set of time series regardless of its origin, but may be particularly useful when anticipating abrupt changes in the multi-dimensional climate system.

[Systems analysis of colour music corrective effect].

PubMed

Gumeniuk, V A; Batova, N Ia; Mel'nikova, T S; Glazachev, O S; Golubeva, N K; Klimina, N V; Hubner, P

1998-01-01

In the context of P. K. Anokhin's theory of functional systems, the corrective effects of various combinations of medical therapeutical resonance music (MTRM) and dynamic colour exposure were analyzed. As compared to rehabilitative music programmes, MRTM was shown to have a more pronounced relaxing effect as manifested both in the optimization of emotion and in the activity of autonomic regulation of cardiovascular functions. On combined MRTM and dynamic colour flow exposures, the relaxing effect is most marked. In the examinees, the personality and situation anxieties diminish, mood improves, cardiovascular parameters become normal, the rate of metabolic processes and muscular rigidity reduce, the spectral power of alpha-rhythm increases, these occurring predominantly in the anterior region of the brain. The findings suggest the high efficiency of the chosen way of normalizing the functional status of man.

Adaptive sliding control of non-autonomous active suspension systems with time-varying loadings

NASA Astrophysics Data System (ADS)

Chen, Po-Chang; Huang, An-Chyau

2005-04-01

An adaptive sliding controller is proposed in this paper for controlling a non-autonomous quarter-car suspension system with time-varying loadings. The bound of the car-body loading is assumed to be available. Then, the reference coordinate is placed at the static position under the nominal loading so that the system dynamic equation is derived. Due to spring nonlinearities, the system property becomes asymmetric after coordinate transformation. Besides, in practical cases, system parameters are not easy to be obtained precisely for controller design. Therefore, in this paper, system uncertainties are lumped into two unknown time-varying functions. Since the variation bound of one of the unknown functions is not available, conventional adaptive schemes and robust designs are not applicable. To deal with this problem, the function approximation technique is employed to represent the unknown function as a finite combination of basis functions. The Lyapunov direct method can thus be used to find adaptive laws for updating coefficients in the approximating series and to prove stability of the closed-loop system. Since the position and velocity measurements of the unsprung mass are lumped into the unknown function, there is no need to install sensors on the axle and wheel assembly in the actual implementation. Simulation results are presented to show the performance of the proposed strategy.

A wearable, low-power, health-monitoring instrumentation based on a Programmable System-on-Chip.

PubMed

Massot, Bertrand; Gehin, Claudine; Nocua, Ronald; Dittmar, Andre; McAdams, Eric

2009-01-01

Improvement in quality and efficiency of health and medicine, at home and in hospital, has become of paramount importance. The solution of this problem would require the continuous monitoring of several key patient parameters, including the assessment of autonomic nervous system (ANS) activity using non-invasive sensors, providing information for emotional, sensorial, cognitive and physiological analysis of the patient. Recent advances in embedded systems, microelectronics, sensors and wireless networking enable the design of wearable systems capable of such advanced health monitoring. The subject of this article is an ambulatory system comprising a small wrist device connected to several sensors for the detection of the autonomic nervous system activity. It affords monitoring of skin resistance, skin temperature and heart activity. It is also capable of recording the data on a removable media or sending it to computer via a wireless communication. The wrist device is based on a Programmable System-on-Chip (PSoC) from Cypress: PSoCs are mixed-signal arrays, with dynamic, configurable digital and analogical blocks and an 8-bit Microcontroller unit (MCU) core on a single chip. In this paper we present first of all the hardware and software architecture of the device, and then results obtained from initial experiments.

An autonomous recovery mechanism against optical distribution network failures in EPON

NASA Astrophysics Data System (ADS)

Liem, Andrew Tanny; Hwang, I.-Shyan; Nikoukar, AliAkbar

2014-10-01

Ethernet Passive Optical Network (EPON) is chosen for servicing diverse applications with higher bandwidth and Quality-of-Service (QoS), starting from Fiber-To-The-Home (FTTH), FTTB (business/building) and FTTO (office). Typically, a single OLT can provide services to both residential and business customers on the same Optical Line Terminal (OLT) port; thus, any failures in the system will cause a great loss for both network operators and customers. Network operators are looking for low-cost and high service availability mechanisms that focus on the failures that occur within the drop fiber section because the majority of faults are in this particular section. Therefore, in this paper, we propose an autonomous recovery mechanism that provides protection and recovery against Drop Distribution Fiber (DDF) link faults or transceiver failure at the ONU(s) in EPON systems. In the proposed mechanism, the ONU can automatically detect any signal anomalies in the physical layer or transceiver failure, switching the working line to the protection line and sending the critical event alarm to OLT via its neighbor. Each ONU has a protection line, which is connected to the nearest neighbor ONU, and therefore, when failure occurs, the ONU can still transmit and receive data via the neighbor ONU. Lastly, the Fault Dynamic Bandwidth Allocation for recovery mechanism is presented. Simulation results show that our proposed autonomous recovery mechanism is able to maintain the overall QoS performance in terms of mean packet delay, system throughput, packet loss and EF jitter.

Autonomic, locomotor and cardiac abnormalities in a mouse model of muscular dystrophy: targeting the renin-angiotensin system.

PubMed

Sabharwal, Rasna; Chapleau, Mark W

2014-04-01

New Findings What is the topic of this review? This symposium report summarizes autonomic, cardiac and skeletal muscle abnormalities in sarcoglycan-δ-deficient mice (Sgcd-/-), a mouse model of limb girdle muscular dystrophy, with emphasis on the roles of autonomic dysregulation and activation of the renin-angiotensin system at a young age. What advances does it highlight? The contributions of the autonomic nervous system and the renin-angiotensin system to the pathogenesis of muscular dystrophy are highlighted. Results demonstrate that autonomic dysregulation precedes and predicts later development of cardiac dysfunction in Sgcd-/- mice and that treatment of young Sgcd-/- mice with the angiotensin type 1 receptor antagonist losartan or with angiotensin-(1-7) abrogates the autonomic dysregulation, attenuates skeletal muscle pathology and increases spontaneous locomotor activity. Muscular dystrophies are a heterogeneous group of genetic muscle diseases characterized by muscle weakness and atrophy. Mutations in sarcoglycans and other subunits of the dystrophin-glycoprotein complex cause muscular dystrophy and dilated cardiomyopathy in animals and humans. Aberrant autonomic signalling is recognized in a variety of neuromuscular disorders. We hypothesized that activation of the renin-angiotensin system contributes to skeletal muscle and autonomic dysfunction in mice deficient in the sarcoglycan-δ (Sgcd) gene at a young age and that this early autonomic dysfunction contributes to the later development of left ventricular (LV) dysfunction and increased mortality. We demonstrated that young Sgcd-/- mice exhibit histopathological features of skeletal muscle dystrophy, decreased locomotor activity and severe autonomic dysregulation, but normal LV function. Autonomic regulation continued to deteriorate in Sgcd-/- mice with age and was accompanied by LV dysfunction and dilated cardiomyopathy at older ages. Autonomic dysregulation at a young age predicted later development of LV dysfunction and higher mortality in Sgcd-/- mice. Treatment of Sgcd-/- mice with the angiotensin type 1 receptor blocker losartan for 8-9 weeks, beginning at 3 weeks of age, decreased fibrosis and oxidative stress in skeletal muscle, increased locomotor activity and prevented autonomic dysfunction. Chronic infusion of the counter-regulatory peptide angiotensin-(1-7) resulted in similar protection. We conclude that activation of the renin-angiotensin system, at a young age, contributes to skeletal muscle and autonomic dysfunction in muscular dystrophy. We speculate that the latter is mediated via abnormal sensory nerve and/or cytokine signalling from dystrophic skeletal muscle to the brain and contributes to age-related LV dysfunction, dilated cardiomyopathy, arrhythmias and premature death. Therefore, correcting the early autonomic dysregulation and renin-angiotensin system activation may provide a novel therapeutic approach in muscular dystrophy.

System Engineering of Autonomous Space Vehicles

NASA Technical Reports Server (NTRS)

Watson, Michael D.; Johnson, Stephen B.; Trevino, Luis

2014-01-01

Human exploration of the solar system requires fully autonomous systems when travelling more than 5 light minutes from Earth. This autonomy is necessary to manage a large, complex spacecraft with limited crew members and skills available. The communication latency requires the vehicle to deal with events with only limited crew interaction in most cases. The engineering of these systems requires an extensive knowledge of the spacecraft systems, information theory, and autonomous algorithm characteristics. The characteristics of the spacecraft systems must be matched with the autonomous algorithm characteristics to reliably monitor and control the system. This presents a large system engineering problem. Recent work on product-focused, elegant system engineering will be applied to this application, looking at the full autonomy stack, the matching of autonomous systems to spacecraft systems, and the integration of different types of algorithms. Each of these areas will be outlined and a general approach defined for system engineering to provide the optimal solution to the given application context.

The prognostic value of heart rate variability in the elderly, changing the perspective: from sympathovagal balance to chaos theory.

PubMed

Nicolini, Paola; Ciulla, Michele M; De Asmundis, Carlo; Magrini, Fabio; Brugada, Pedro

2012-05-01

Heart rate variability (HRV) is the temporal beat-to-beat variation in successive RR intervals on an electrocardiographic (ECG) recording and it reflects the regulation of the heart rate (HR) by the autonomic nervous system (ANS). HRV analysis is a noninvasive tool for the assessment of autonomic function that gained momentum in the late 1980s when its clinical relevance as a predictor of mortality was established by a milestone study by Kleiger et al. in patients with postacute myocardial infarction. In the last few decades, the increasing availability of commercial ECG devices offering HRV analysis has made HRV a favorite marker for risk stratification in the setting of cardiovascular disease. The rapid aging of the world population and the growing popularity of HRV have also fueled interest for the prognostic value of HRV in the elderly, outside a specific cardiological context. However, the discussion of HRV measures in the elderly is still very much centered on the rather reductionistic model of sympathovagal balance, with the orthosympathetic and parasympathetic limbs of the ANS exercising opposing effects on the heart via autonomic tone. The expanding application of nonlinear dynamics to medicine has brought to the forefront the notion of system complexity, embedded in the mathematical concepts of chaos theory and fractals, and provides an opportunity to suggest a broader interpretation for the prognostic significance of HRV, especially in the elderly. Although the use of novel indices of HRV may be hampered by practical issues, a more holistic approach to HRV may still be safeguarded if traditional time- and frequency-domain measures are viewed in terms of autonomic modulation. This review focuses on HRV in geriatric populations. It considers studies on the prognostic value of HRV in elderly subjects, discussing the potential confounding effect of erratic rhythm, and concentrates on the conceptual distinction between autonomic tone and autonomic modulation. It also briefly addresses the question of the practicality of ECG recordings and identifies a promising area for future research in the effects of common noncardioactive drugs on HRV. ©2012, The Authors. Journal compilation ©2012 Wiley Periodicals, Inc.

Autonomic Evaluation of Patients With Gastroparesis and Neurostimulation: Comparisons of Direct/Systemic and Indirect/Cardiac Measures

PubMed Central

Stocker, Abigail; Abell, Thomas L.; Rashed, Hani; Kedar, Archana; Boatright, Ben; Chen, Jiande

2016-01-01

Background Disorders of nausea, vomiting, abdominal pain, and related problems often are manifestations of gastrointestinal, neuromuscular, and/or autonomic dysfunction. Many of these patients respond to neurostimulation, either gastric electrical stimulation or electroacupuncture. Both of these therapeutic techniques appear to influence the autonomic nervous system which can be evaluated directly by traditional testing and indirectly by heart rate variability. Methods We studied patients undergoing gastric neuromodulation by both systemic autonomic testing (39 patients, six males and 33 females, mean age 38 years) and systemic autonomic testing and heart rate variability (35 patients, seven males and 28 females, mean age 37 years) testing before and after gastric neuromodulation. We also performed a pilot study using both systemic autonomic testing and heart rate variability in a small number of patients (five patients, all females, mean age 48.6 years) with diabetic gastroparesis at baseline to compare the two techniques at baseline. Systemic autonomic testing and heart rate variability were performed with standardized techniques and gastric electrical stimulation was performed as previously described with electrodes implanted serosally in the myenteric plexus. Results Both systemic autonomic testing and heart rate variability measures were often abnormal at baseline and showed changes after gastric neuromodulation therapy in two groups of symptomatic patients. Pilot data on a small group of similar patients with systemic automatic nervous measures and heart rate variability showed good concordance between the two techniques. Conclusions Both traditional direct autonomic measures and indirect measures such as heart rate variability were evaluated, including a pilot study of both methods in the same patient group. Both appear to be useful in evaluation of patients at baseline and after stimulation therapies; however, a future full head-to-head comparison is warranted. PMID:27785318

Intelligent autonomy for unmanned naval systems

NASA Astrophysics Data System (ADS)

Steinberg, Marc

2006-05-01

This paper provides an overview of the development and demonstration of intelligent autonomy technologies for control of heterogeneous unmanned naval air and sea vehicles and describes some of the current limitations of such technologies. The focus is on modular technologies that support highly automated retasking and fully autonomous dynamic replanning for up to ten heterogeneous unmanned systems based on high-level mission objectives, priorities, constraints, and Rules-of-Engagement. A key aspect of the demonstrations is incorporating frequent naval operator evaluations in order to gain better understanding of the integrated man/machine system and its tactical utility. These evaluations help ensure that the automation can provide information to the user in a meaningful way and that the user has a sufficient level of control and situation awareness to task the system as needed to complete complex mission tasks. Another important aspect of the program is examination of the interactions of higher-level autonomy algorithms with other relevant components that would be needed within the decision-making and control loops. Examples of these are vision and other sensor processing algorithms, sensor fusion, obstacle avoidance, and other lower level vehicle autonomous navigation, guidance, and control functions. Initial experiments have been completed using medium and high-fidelity vehicle simulations in a virtual warfare environment and inexpensive surrogate vehicles in flight and in-water demonstrations. Simulation experiments included integration of multi-vehicle task allocation, dynamic replanning under constraints, lower level autonomous vehicle control, automatic assessment of the impact of contingencies on plans, management of situation awareness data, operator alert management, and a mixed-initiative operator interface. In-water demonstrations of a maritime situation awareness capability were completed in both a river and a harbor environment using unmanned surface vehicles and a buoy as surrogate platforms. In addition, a multiple heterogeneous vehicle demonstration was performed using five different types of small unmanned air and ground vehicles. This provided some initial experimentation with specifying tasking for high-level mission objectives and then mapping those objectives onto heterogeneous unmanned vehicles that each have different lower-level autonomy software. Finally, this paper will discuss lessons learned.

Research on support effectiveness modeling and simulating of aviation materiel autonomic logistics system

NASA Astrophysics Data System (ADS)

Zhou, Yan; Zhou, Yang; Yuan, Kai; Jia, Zhiyu; Li, Shuo

2018-05-01

Aiming at the demonstration of autonomic logistics system to be used at the new generation of aviation materiel in our country, the modeling and simulating method of aviation materiel support effectiveness considering autonomic logistics are studied. Firstly, this paper introduced the idea of JSF autonomic logistics and analyzed the influence of autonomic logistics on support effectiveness from aspects of reliability, false alarm rate, troubleshooting time, and support delay time and maintenance level. On this basis, the paper studies the modeling and simulating methods of support effectiveness considering autonomic logistics, and puts forward the maintenance support simulation process considering autonomic logistics. Finally, taking the typical aviation materiel as an example, this paper analyzes and verifies the above-mentioned support effectiveness modeling and simulating method of aviation materiel considering autonomic logistics.

Autonomous Agents on Expedition: Humans and Progenitor Ants and Planetary Exploration

NASA Astrophysics Data System (ADS)

Rilee, M. L.; Clark, P. E.; Curtis, S. A.; Truszkowski, W. F.

2002-01-01

The Autonomous Nano-Technology Swarm (ANTS) is an advanced mission architecture based on a social insect analog of many specialized spacecraft working together to achieve mission goals. The principal mission concept driving the ANTS architecture is a Main Belt Asteroid Survey in the 2020s that will involve a thousand or more nano-technology enabled, artificially intelligent, autonomous pico-spacecraft (< 1 kg). The objective of this survey is to construct a compendium of composition, shape, and other physical parameter observations of a significant fraction of asteroid belt objects. Such an atlas will be of primary scientific importance for the understanding of Solar System origins and evolution and will lay the foundation for future exploration and capitalization of space. As the capabilities enabling ANTS are developed over the next two decades, these capabilities will need to be proven. Natural milestones for this process include the deployment of progenitors to ANTS on human expeditions to space and remote missions with interfaces for human interaction and control. These progenitors can show up in a variety of forms ranging from spacecraft subsystems and advanced handheld sensors, through complete prototypical ANTS spacecraft. A critical capability to be demonstrated is reliable, long-term autonomous operations across the ANTS architecture. High level, mission-oriented behaviors are to be managed by a control / communications layer of the swarm, whereas common low level functions required of all spacecraft, e.g. attitude control and guidance and navigation, are handled autonomically on each spacecraft. At the higher levels of mission planning and social interaction deliberative techniques are to be used. For the asteroid survey, ANTS acts as a large community of cooperative agents while for precursor missions there arises the intriguing possibility of Progenitor ANTS and humans acting together as agents. For optimal efficiency and responsiveness for individual spacecraft at the lowest levels of control we have been studying control methods based on nonlinear dynamical systems. We describe the critically important autonomous control architecture of the ANTS mission concept and a sequence of partial implementations that feature increasingly autonomous behaviors. The scientific and engineering roles that these Progenitor ANTS could play in human missions or remote missions with near real time human interactions, particularly to the Moon and Mars, will be discussed.

Robot navigation research using the HERMIES mobile robot

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barnett, D.L.

1989-01-01

In recent years robot navigation has attracted much attention from researchers around the world. Not only are theoretical studies being simulated on sophisticated computers, but many mobile robots are now used as test vehicles for these theoretical studies. Various algorithms have been perfected for navigation in a known static environment; but navigation in an unknown and dynamic environment poses a much more challenging problem for researchers. Many different methodologies have been developed for autonomous robot navigation, but each methodology is usually restricted to a particular type of environment. One important research focus of the Center for Engineering Systems Advanced researchmore » (CESAR) at Oak Ridge National Laboratory, is autonomous navigation in unknown and dynamic environments using the series of HERMIES mobile robots. The research uses an expert system for high-level planning interfaced with C-coded routines for implementing the plans, and for quick processing of data requested by the expert system. In using this approach, the navigation is not restricted to one methodology since the expert system can activate a rule module for the methodology best suited for the current situation. Rule modules can be added the rule base as they are developed and tested. Modules are being developed or enhanced for navigating from a map, searching for a target, exploring, artificial potential-field navigation, navigation using edge-detection, etc. This paper will report on the various rule modules and methods of navigation in use, or under development at CESAR, using the HERMIES-IIB robot as a testbed. 13 refs., 5 figs., 1 tab.« less

The nature of the autonomic dysfunction in multiple system atrophy

NASA Technical Reports Server (NTRS)

Parikh, Samir M.; Diedrich, Andre; Biaggioni, Italo; Robertson, David

2002-01-01

The concept that multiple system atrophy (MSA, Shy-Drager syndrome) is a disorder of the autonomic nervous system is several decades old. While there has been renewed interest in the movement disorder associated with MSA, two recent consensus statements confirm the centrality of the autonomic disorder to the diagnosis. Here, we reexamine the autonomic pathophysiology in MSA. Whereas MSA is often thought of as "autonomic failure", new evidence indicates substantial persistence of functioning sympathetic and parasympathetic nerves even in clinically advanced disease. These findings help explain some of the previously poorly understood features of MSA. Recognition that MSA entails persistent, constitutive autonomic tone requires a significant revision of our concepts of its diagnosis and therapy. We will review recent evidence bearing on autonomic tone in MSA and discuss their therapeutic implications, particularly in terms of the possible development of a bionic baroreflex for better control of blood pressure.

Autonomous interplanetary constellation design

NASA Astrophysics Data System (ADS)

Chow, Cornelius Channing, II

According to NASA's integrated space technology roadmaps, space-based infrastructures are envisioned as necessary ingredients to a sustained effort in continuing space exploration. Whether it be for extra-terrestrial habitats, roving/cargo vehicles, or space tourism, autonomous space networks will provide a vital communications lifeline for both future robotic and human missions alike. Projecting that the Moon will be a bustling hub of activity within a few decades, a near-term opportunity for in-situ infrastructure development is within reach. This dissertation addresses the anticipated need for in-space infrastructure by investigating a general design methodology for autonomous interplanetary constellations; to illustrate the theory, this manuscript presents results from an application to the Earth-Moon neighborhood. The constellation design methodology is formulated as an optimization problem, involving a trajectory design step followed by a spacecraft placement sequence. Modeling the dynamics as a restricted 3-body problem, the investigated design space consists of families of periodic orbits which play host to the constellations, punctuated by arrangements of spacecraft autonomously guided by a navigation strategy called LiAISON (Linked Autonomous Interplanetary Satellite Orbit Navigation). Instead of more traditional exhaustive search methods, a numerical continuation approach is implemented to map the admissible configuration space. In particular, Keller's pseudo-arclength technique is used to follow folding/bifurcating solution manifolds, which are otherwise inaccessible with other parameter continuation schemes. A succinct characterization of the underlying structure of the local, as well as global, extrema is thus achievable with little a priori intuition of the solution space. Furthermore, the proposed design methodology offers benefits in computation speed plus the ability to handle mildly stochastic systems. An application of the constellation design methodology to the restricted Earth-Moon system, reveals optimal pairwise configurations for various L1, L2, and L5 (halo, axial, and vertical) periodic orbit families. Navigation accuracies, ranging from O (10+/-1) meters in position space, are obtained for the optimal Earth-Moon constellations, given measurement noise on the order of 1 meter.

[Effects of inflammation and stimulant diets on functions of autonomic nervous system (author's transl)].

PubMed

Akaeda, H; Nagai, K; Okuda, Y; Shinoto, M; Okuda, H

1981-06-01

In usual medical consultation, we have been met a lot of female patients suffering from disturbances of autonomic nervous system such as headache, shoulder-ache and so on. Experiments were designed to elucidate whether or not these disturbances of autonomic nervous system were induced by inflammation and accelerated by stimulant diets. Functions of autonomic nervous system were examined by lipolysis in rat epididymal adipose tissue which was partly controlled by sympathetic nervous system. It was found that free fatty acid release from the epididymal adipose tissue was considerably elevated by inflammation which was formed in abdominal wall or in abdominal cavity or oral administration of stimulant diets such as red pepper and white pepper, and that such elevation of lipolysis was significantly reduced by resection of the autonomic nerve. These results indicated that the inflammation and the stimulant diets induced excitement of sympathetic nerve which controlled the epididymal adipose tissue. Experiments were now in progress to clarify relationship between such excitement of sympathetic nervous system induced by the inflammation or by the stimulant diet and irregular complaints due to disturbances of autonomic nervous system.

Simultaneous Planning and Control for Autonomous Ground Vehicles

DTIC Science & Technology

2009-02-01

these applications is called A * ( A -star), and it was originally developed by Hart, Nilsson, and Raphael [HAR68]. Their research presented the formal...sequence, rather than a dynamic programming approach. A * search is a technique originally developed for Artificial Intelligence 43 applications ... developed at the Center for Intelligent Machines and Robotics, serves as a platform for the implementation and testing discussed. autonomous

DualTrust: A Distributed Trust Model for Swarm-Based Autonomic Computing Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maiden, Wendy M.; Dionysiou, Ioanna; Frincke, Deborah A.

2011-02-01

For autonomic computing systems that utilize mobile agents and ant colony algorithms for their sensor layer, trust management is important for the acceptance of the mobile agent sensors and to protect the system from malicious behavior by insiders and entities that have penetrated network defenses. This paper examines the trust relationships, evidence, and decisions in a representative system and finds that by monitoring the trustworthiness of the autonomic managers rather than the swarming sensors, the trust management problem becomes much more scalable and still serves to protect the swarm. We then propose the DualTrust conceptual trust model. By addressing themore » autonomic manager’s bi-directional primary relationships in the ACS architecture, DualTrust is able to monitor the trustworthiness of the autonomic managers, protect the sensor swarm in a scalable manner, and provide global trust awareness for the orchestrating autonomic manager.« less

A general architecture for intelligent training systems

NASA Technical Reports Server (NTRS)

Loftin, R. Bowen

1987-01-01

A preliminary design of a general architecture for autonomous intelligent training systems was developed. The architecture integrates expert system technology with teaching/training methodologies to permit the production of systems suitable for use by NASA, other government agencies, industry, and academia in the training of personnel for the performance of complex, mission-critical tasks. The proposed architecture consists of five elements: a user interface, a domain expert, a training session manager, a trainee model, and a training scenario generator. The design of this architecture was guided and its efficacy tested through the development of a system for use by Mission Control Center Flight Dynamics Officers in training to perform Payload-Assist Module Deploys from the orbiter.

Sufficient conditions for asymptotic stability and stabilization of autonomous fractional order systems

NASA Astrophysics Data System (ADS)

Lenka, Bichitra Kumar; Banerjee, Soumitro

2018-03-01

We discuss the asymptotic stability of autonomous linear and nonlinear fractional order systems where the state equations contain same or different fractional orders which lie between 0 and 2. First, we use the Laplace transform method to derive some sufficient conditions which ensure asymptotic stability of linear fractional order systems. Then by using the obtained results and linearization technique, a stability theorem is presented for autonomous nonlinear fractional order system. Finally, we design a control strategy for stabilization of autonomous nonlinear fractional order systems, and apply the results to the chaotic fractional order Lorenz system in order to verify its effectiveness.

UAV Research at NASA Langley: Towards Safe, Reliable, and Autonomous Operations

NASA Technical Reports Server (NTRS)

Davila, Carlos G.

2016-01-01

Unmanned Aerial Vehicles (UAV) are fundamental components in several aspects of research at NASA Langley, such as flight dynamics, mission-driven airframe design, airspace integration demonstrations, atmospheric science projects, and more. In particular, NASA Langley Research Center (Langley) is using UAVs to develop and demonstrate innovative capabilities that meet the autonomy and robotics challenges that are anticipated in science, space exploration, and aeronautics. These capabilities will enable new NASA missions such as asteroid rendezvous and retrieval (ARRM), Mars exploration, in-situ resource utilization (ISRU), pollution measurements in historically inaccessible areas, and the integration of UAVs into our everyday lives all missions of increasing complexity, distance, pace, and/or accessibility. Building on decades of NASA experience and success in the design, fabrication, and integration of robust and reliable automated systems for space and aeronautics, Langley Autonomy Incubator seeks to bridge the gap between automation and autonomy by enabling safe autonomous operations via onboard sensing and perception systems in both data-rich and data-deprived environments. The Autonomy Incubator is focused on the challenge of mobility and manipulation in dynamic and unstructured environments by integrating technologies such as computer vision, visual odometry, real-time mapping, path planning, object detection and avoidance, object classification, adaptive control, sensor fusion, machine learning, and natural human-machine teaming. These technologies are implemented in an architectural framework developed in-house for easy integration and interoperability of cutting-edge hardware and software.

Dynamic RSA: Examining parasympathetic regulatory dynamics via vector-autoregressive modeling of time-varying RSA and heart period.

PubMed

Fisher, Aaron J; Reeves, Jonathan W; Chi, Cyrus

2016-07-01

Expanding on recently published methods, the current study presents an approach to estimating the dynamic, regulatory effect of the parasympathetic nervous system on heart period on a moment-to-moment basis. We estimated second-to-second variation in respiratory sinus arrhythmia (RSA) in order to estimate the contemporaneous and time-lagged relationships among RSA, interbeat interval (IBI), and respiration rate via vector autoregression. Moreover, we modeled these relationships at lags of 1 s to 10 s, in order to evaluate the optimal latency for estimating dynamic RSA effects. The IBI (t) on RSA (t-n) regression parameter was extracted from individual models as an operationalization of the regulatory effect of RSA on IBI-referred to as dynamic RSA (dRSA). Dynamic RSA positively correlated with standard averages of heart rate and negatively correlated with standard averages of RSA. We propose that dRSA reflects the active downregulation of heart period by the parasympathetic nervous system and thus represents a novel metric that provides incremental validity in the measurement of autonomic cardiac control-specifically, a method by which parasympathetic regulatory effects can be measured in process. © 2016 Society for Psychophysiological Research.

Information driven self-organization of complex robotic behaviors.

PubMed

Martius, Georg; Der, Ralf; Ay, Nihat

2013-01-01

Information theory is a powerful tool to express principles to drive autonomous systems because it is domain invariant and allows for an intuitive interpretation. This paper studies the use of the predictive information (PI), also called excess entropy or effective measure complexity, of the sensorimotor process as a driving force to generate behavior. We study nonlinear and nonstationary systems and introduce the time-local predicting information (TiPI) which allows us to derive exact results together with explicit update rules for the parameters of the controller in the dynamical systems framework. In this way the information principle, formulated at the level of behavior, is translated to the dynamics of the synapses. We underpin our results with a number of case studies with high-dimensional robotic systems. We show the spontaneous cooperativity in a complex physical system with decentralized control. Moreover, a jointly controlled humanoid robot develops a high behavioral variety depending on its physics and the environment it is dynamically embedded into. The behavior can be decomposed into a succession of low-dimensional modes that increasingly explore the behavior space. This is a promising way to avoid the curse of dimensionality which hinders learning systems to scale well.

Self-optimized construction of transition rate matrices from accelerated atomistic simulations with Bayesian uncertainty quantification

NASA Astrophysics Data System (ADS)

Swinburne, Thomas D.; Perez, Danny

2018-05-01

A massively parallel method to build large transition rate matrices from temperature-accelerated molecular dynamics trajectories is presented. Bayesian Markov model analysis is used to estimate the expected residence time in the known state space, providing crucial uncertainty quantification for higher-scale simulation schemes such as kinetic Monte Carlo or cluster dynamics. The estimators are additionally used to optimize where exploration is performed and the degree of temperature acceleration on the fly, giving an autonomous, optimal procedure to explore the state space of complex systems. The method is tested against exactly solvable models and used to explore the dynamics of C15 interstitial defects in iron. Our uncertainty quantification scheme allows for accurate modeling of the evolution of these defects over timescales of several seconds.

Neural Regulation of Cardiovascular Response to Exercise: Role of Central Command and Peripheral Afferents

PubMed Central

Nobrega, Antonio C. L.; O'Leary, Donal; Silva, Bruno Moreira; Piepoli, Massimo F.; Crisafulli, Antonio

2014-01-01

During dynamic exercise, mechanisms controlling the cardiovascular apparatus operate to provide adequate oxygen to fulfill metabolic demand of exercising muscles and to guarantee metabolic end-products washout. Moreover, arterial blood pressure is regulated to maintain adequate perfusion of the vital organs without excessive pressure variations. The autonomic nervous system adjustments are characterized by a parasympathetic withdrawal and a sympathetic activation. In this review, we briefly summarize neural reflexes operating during dynamic exercise. The main focus of the present review will be on the central command, the arterial baroreflex and chemoreflex, and the exercise pressure reflex. The regulation and integration of these reflexes operating during dynamic exercise and their possible role in the pathophysiology of some cardiovascular diseases are also discussed. PMID:24818143

Asymptotic behavior of dynamical variables and naked singularity formation in spherically symmetric gravitational collapse

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kawakami, Hayato; Mitsuda, Eiji; Nambu, Yasusada

In considering the gravitational collapse of matter, it is an important problem to clarify what kind of conditions leads to the formation of naked singularity. For this purpose, we apply the 1+3 orthonormal frame formalism introduced by Uggla et al. to the spherically symmetric gravitational collapse of a perfect fluid. This formalism allows us to construct an autonomous system of evolution and constraint equations for scale-invariant dynamical variables normalized by the volume expansion rate of the timelike orthonormal frame vector. We investigate the asymptotic evolution of such dynamical variables towards the formation of a central singularity and present a conjecturemore » that the steep spatial gradient for the normalized density function is a characteristic of the naked singularity formation.« less

Pattern Analysis in Social Networks with Dynamic Connections

NASA Astrophysics Data System (ADS)

Wu, Yu; Zhang, Yu

In this paper, we explore how decentralized local interactions of autonomous agents in a network relate to collective behaviors. Most existing work in this area models social network in which agent relations are fixed; instead, we focus on dynamic social networks where agents can rationally adjust their neighborhoods based on their individual interests. We propose a new connection evaluation rule called the Highest Weighted Reward (HWR) rule, with which agents dynamically choose their neighbors in order to maximize their own utilities based on the rewards from previous interactions. Our experiments show that in the 2-action pure coordination game, our system will stabilize to a clustering state where all relationships in the network are rewarded with the optimal payoff. Our experiments also reveal additional interesting patterns in the network.

Mathematical assessment of the role of temperature and rainfall on mosquito population dynamics.

PubMed

Abdelrazec, Ahmed; Gumel, Abba B

2017-05-01

A new stage-structured model for the population dynamics of the mosquito (a major vector for numerous vector-borne diseases), which takes the form of a deterministic system of non-autonomous nonlinear differential equations, is designed and used to study the effect of variability in temperature and rainfall on mosquito abundance in a community. Two functional forms of eggs oviposition rate, namely the Verhulst-Pearl logistic and Maynard-Smith-Slatkin functions, are used. Rigorous analysis of the autonomous version of the model shows that, for any of the oviposition functions considered, the trivial equilibrium of the model is locally- and globally-asymptotically stable if a certain vectorial threshold quantity is less than unity. Conditions for the existence and global asymptotic stability of the non-trivial equilibrium solutions of the model are also derived. The model is shown to undergo a Hopf bifurcation under certain conditions (and that increased density-dependent competition in larval mortality reduces the likelihood of such bifurcation). The analyses reveal that the Maynard-Smith-Slatkin oviposition function sustains more oscillations than the Verhulst-Pearl logistic function (hence, it is more suited, from ecological viewpoint, for modeling the egg oviposition process). The non-autonomous model is shown to have a globally-asymptotically stable trivial periodic solution, for each of the oviposition functions, when the associated reproduction threshold is less than unity. Furthermore, this model, in the absence of density-dependent mortality rate for larvae, has a unique and globally-asymptotically stable periodic solution under certain conditions. Numerical simulations of the non-autonomous model, using mosquito surveillance and weather data from the Peel region of Ontario, Canada, show a peak mosquito abundance for temperature and rainfall values in the range [Formula: see text]C and [15-35] mm, respectively. These ranges are recorded in the Peel region between July and August (hence, this study suggests that anti-mosquito control effects should be intensified during this period).

Engineering Sensorial Delay to Control Phototaxis and Emergent Collective Behaviors

NASA Astrophysics Data System (ADS)

Mijalkov, Mite; McDaniel, Austin; Wehr, Jan; Volpe, Giovanni

2016-01-01

Collective motions emerging from the interaction of autonomous mobile individuals play a key role in many phenomena, from the growth of bacterial colonies to the coordination of robotic swarms. For these collective behaviors to take hold, the individuals must be able to emit, sense, and react to signals. When dealing with simple organisms and robots, these signals are necessarily very elementary; e.g., a cell might signal its presence by releasing chemicals and a robot by shining light. An additional challenge arises because the motion of the individuals is often noisy; e.g., the orientation of cells can be altered by Brownian motion and that of robots by an uneven terrain. Therefore, the emphasis is on achieving complex and tunable behaviors from simple autonomous agents communicating with each other in robust ways. Here, we show that the delay between sensing and reacting to a signal can determine the individual and collective long-term behavior of autonomous agents whose motion is intrinsically noisy. We experimentally demonstrate that the collective behavior of a group of phototactic robots capable of emitting a radially decaying light field can be tuned from segregation to aggregation and clustering by controlling the delay with which they change their propulsion speed in response to the light intensity they measure. We track this transition to the underlying dynamics of this system, in particular, to the ratio between the robots' sensorial delay time and the characteristic time of the robots' random reorientation. Supported by numerics, we discuss how the same mechanism can be applied to control active agents, e.g., airborne drones, moving in a three-dimensional space. Given the simplicity of this mechanism, the engineering of sensorial delay provides a potentially powerful tool to engineer and dynamically tune the behavior of large ensembles of autonomous mobile agents; furthermore, this mechanism might already be at work within living organisms such as chemotactic cells.

Autonomic Intelligent Cyber Sensor to Support Industrial Control Network Awareness

DOE PAGES

Vollmer, Todd; Manic, Milos; Linda, Ondrej

2013-06-01

The proliferation of digital devices in a networked industrial ecosystem, along with an exponential growth in complexity and scope, has resulted in elevated security concerns and management complexity issues. This paper describes a novel architecture utilizing concepts of Autonomic computing and a SOAP based IF-MAP external communication layer to create a network security sensor. This approach simplifies integration of legacy software and supports a secure, scalable, self-managed framework. The contribution of this paper is two-fold: 1) A flexible two level communication layer based on Autonomic computing and Service Oriented Architecture is detailed and 2) Three complementary modules that dynamically reconfiguremore » in response to a changing environment are presented. One module utilizes clustering and fuzzy logic to monitor traffic for abnormal behavior. Another module passively monitors network traffic and deploys deceptive virtual network hosts. These components of the sensor system were implemented in C++ and PERL and utilize a common internal D-Bus communication mechanism. A proof of concept prototype was deployed on a mixed-use test network showing the possible real world applicability. In testing, 45 of the 46 network attached devices were recognized and 10 of the 12 emulated devices were created with specific Operating System and port configurations. Additionally the anomaly detection algorithm achieved a 99.9% recognition rate. All output from the modules were correctly distributed using the common communication structure.« less

An agent-based peer-to-peer architecture for semantic discovery of manufacturing services across virtual enterprises

NASA Astrophysics Data System (ADS)

Zhang, Wenyu; Zhang, Shuai; Cai, Ming; Jian, Wu

2015-04-01

With the development of virtual enterprise (VE) paradigm, the usage of serviceoriented architecture (SOA) is increasingly being considered for facilitating the integration and utilisation of distributed manufacturing resources. However, due to the heterogeneous nature among VEs, the dynamic nature of a VE and the autonomous nature of each VE member, the lack of both sophisticated coordination mechanism in the popular centralised infrastructure and semantic expressivity in the existing SOA standards make the current centralised, syntactic service discovery method undesirable. This motivates the proposed agent-based peer-to-peer (P2P) architecture for semantic discovery of manufacturing services across VEs. Multi-agent technology provides autonomous and flexible problemsolving capabilities in dynamic and adaptive VE environments. Peer-to-peer overlay provides highly scalable coupling across decentralised VEs, each of which exhibiting as a peer composed of multiple agents dealing with manufacturing services. The proposed architecture utilises a novel, efficient, two-stage search strategy - semantic peer discovery and semantic service discovery - to handle the complex searches of manufacturing services across VEs through fast peer filtering. The operation and experimental evaluation of the prototype system are presented to validate the implementation of the proposed approach.

[Signs and symptoms of autonomic dysfunction in dysphonic individuals].

PubMed

Park, Kelly; Behlau, Mara

2011-01-01

To verify the occurrence of signs and symptoms of autonomic nervous system dysfunction in individuals with behavioral dysphonia, and to compare it with the results obtained by individuals without vocal complaints. Participants were 128 adult individuals with ages between 14 and 74 years, divided into two groups: behavioral dysphonia (61 subjects) and without vocal complaints (67 subjects). It was administered the Protocol of Autonomic Dysfunction, containing 46 questions: 22 related to the autonomic nervous system and had no direct relationship with voice, 16 related to both autonomic nervous system and voice, six non-relevant questions, and two reliability questions. There was a higher occurrence of reported neurovegetative signs in the group with behavioral dysphonia, in questions related to voice, such as frequent throat clearing, frequent swallowing need, fatigability when speaking, and sore throat. In questions not directly related to voice, dysphonic individuals presented greater occurrence of three out of 22 symptoms: gas, tinnitus and aerophagia. Both groups presented similar results in questions non-relevant to the autonomic nervous system. Reliability questions needed reformulation. Individuals with behavioral dysphonia present higher occurrence of neurovegetative signs and symptoms, particularly those with direct relationship with voice, indicating greater lability of the autonomic nervous system in these subjects.

Micro Autonomous Systems Research: Systems Engineering Processes for Micro Autonomous Systems

DTIC Science & Technology

2016-11-01

product family design and reconfigurable system design with recent developments in the fields of automated manufacturing and micro-autonomous...mapped to design parameters. These mappings are the mechanism by which physical product designs are formulated. Finally, manufacture of the product ... design tools and manufacturing and testing the resulting design . The final products were inspected and flight tested so that their

Predicting Adaptive Behavior in the Environment from Central Nervous System Dynamics

PubMed Central

Proekt, Alex; Wong, Jane; Zhurov, Yuriy; Kozlova, Nataliya; Weiss, Klaudiusz R.; Brezina, Vladimir

2008-01-01

To generate adaptive behavior, the nervous system is coupled to the environment. The coupling constrains the dynamical properties that the nervous system and the environment must have relative to each other if adaptive behavior is to be produced. In previous computational studies, such constraints have been used to evolve controllers or artificial agents to perform a behavioral task in a given environment. Often, however, we already know the controller, the real nervous system, and its dynamics. Here we propose that the constraints can also be used to solve the inverse problem—to predict from the dynamics of the nervous system the environment to which they are adapted, and so reconstruct the production of the adaptive behavior by the entire coupled system. We illustrate how this can be done in the feeding system of the sea slug Aplysia. At the core of this system is a central pattern generator (CPG) that, with dynamics on both fast and slow time scales, integrates incoming sensory stimuli to produce ingestive and egestive motor programs. We run models embodying these CPG dynamics—in effect, autonomous Aplysia agents—in various feeding environments and analyze the performance of the entire system in a realistic feeding task. We find that the dynamics of the system are tuned for optimal performance in a narrow range of environments that correspond well to those that Aplysia encounter in the wild. In these environments, the slow CPG dynamics implement efficient ingestion of edible seaweed strips with minimal sensory information about them. The fast dynamics then implement a switch to a different behavioral mode in which the system ignores the sensory information completely and follows an internal “goal,” emergent from the dynamics, to egest again a strip that proves to be inedible. Key predictions of this reconstruction are confirmed in real feeding animals. PMID:18989362

A Multiscale Closed-Loop Cardiovascular Model, with Applications to Heart Pacing and Hemorrhage

NASA Astrophysics Data System (ADS)

Canuto, Daniel; Eldredge, Jeff; Chong, Kwitae; Benharash, Peyman; Dutson, Erik

2017-11-01

A computational tool is developed for simulating the dynamic response of the human cardiovascular system to various stressors and injuries. The tool couples zero-dimensional models of the heart, pulmonary vasculature, and peripheral vasculature to one-dimensional models of the major systemic arteries. To simulate autonomic response, this multiscale circulatory model is integrated with a feedback model of the baroreflex, allowing control of heart rate, cardiac contractility, and peripheral impedance. The performance of the tool is demonstrated in two scenarios: increasing heart rate by stimulating the sympathetic nervous system, and an acute 10 percent hemorrhage from the left femoral artery.

Learning Agents for Autonomous Space Asset Management (LAASAM)

NASA Astrophysics Data System (ADS)

Scally, L.; Bonato, M.; Crowder, J.

2011-09-01

Current and future space systems will continue to grow in complexity and capabilities, creating a formidable challenge to monitor, maintain, and utilize these systems and manage their growing network of space and related ground-based assets. Integrated System Health Management (ISHM), and in particular, Condition-Based System Health Management (CBHM), is the ability to manage and maintain a system using dynamic real-time data to prioritize, optimize, maintain, and allocate resources. CBHM entails the maintenance of systems and equipment based on an assessment of current and projected conditions (situational and health related conditions). A complete, modern CBHM system comprises a number of functional capabilities: sensing and data acquisition; signal processing; conditioning and health assessment; diagnostics and prognostics; and decision reasoning. In addition, an intelligent Human System Interface (HSI) is required to provide the user/analyst with relevant context-sensitive information, the system condition, and its effect on overall situational awareness of space (and related) assets. Colorado Engineering, Inc. (CEI) and Raytheon are investigating and designing an Intelligent Information Agent Architecture that will provide a complete range of CBHM and HSI functionality from data collection through recommendations for specific actions. The research leverages CEI’s expertise with provisioning management network architectures and Raytheon’s extensive experience with learning agents to define a system to autonomously manage a complex network of current and future space-based assets to optimize their utilization.

A VLF-based technique in applications to digital control of nonlinear hybrid multirate systems

NASA Astrophysics Data System (ADS)

Vassilyev, Stanislav; Ulyanov, Sergey; Maksimkin, Nikolay

2017-01-01

In this paper, a technique for rigorous analysis and design of nonlinear multirate digital control systems on the basis of the reduction method and sublinear vector Lyapunov functions is proposed. The control system model under consideration incorporates continuous-time dynamics of the plant and discrete-time dynamics of the controller and takes into account uncertainties of the plant, bounded disturbances, nonlinear characteristics of sensors and actuators. We consider a class of multirate systems where the control update rate is slower than the measurement sampling rates and periodic non-uniform sampling is admitted. The proposed technique does not use the preliminary discretization of the system, and, hence, allows one to eliminate the errors associated with the discretization and improve the accuracy of analysis. The technique is applied to synthesis of digital controller for a flexible spacecraft in the fine stabilization mode and decentralized controller for a formation of autonomous underwater vehicles. Simulation results are provided to validate the good performance of the designed controllers.

An interactive physics-based unmanned ground vehicle simulator leveraging open source gaming technology: progress in the development and application of the virtual autonomous navigation environment (VANE) desktop

NASA Astrophysics Data System (ADS)

Rohde, Mitchell M.; Crawford, Justin; Toschlog, Matthew; Iagnemma, Karl D.; Kewlani, Guarav; Cummins, Christopher L.; Jones, Randolph A.; Horner, David A.

2009-05-01

It is widely recognized that simulation is pivotal to vehicle development, whether manned or unmanned. There are few dedicated choices, however, for those wishing to perform realistic, end-to-end simulations of unmanned ground vehicles (UGVs). The Virtual Autonomous Navigation Environment (VANE), under development by US Army Engineer Research and Development Center (ERDC), provides such capabilities but utilizes a High Performance Computing (HPC) Computational Testbed (CTB) and is not intended for on-line, real-time performance. A product of the VANE HPC research is a real-time desktop simulation application under development by the authors that provides a portal into the HPC environment as well as interaction with wider-scope semi-automated force simulations (e.g. OneSAF). This VANE desktop application, dubbed the Autonomous Navigation Virtual Environment Laboratory (ANVEL), enables analysis and testing of autonomous vehicle dynamics and terrain/obstacle interaction in real-time with the capability to interact within the HPC constructive geo-environmental CTB for high fidelity sensor evaluations. ANVEL leverages rigorous physics-based vehicle and vehicle-terrain interaction models in conjunction with high-quality, multimedia visualization techniques to form an intuitive, accurate engineering tool. The system provides an adaptable and customizable simulation platform that allows developers a controlled, repeatable testbed for advanced simulations. ANVEL leverages several key technologies not common to traditional engineering simulators, including techniques from the commercial video-game industry. These enable ANVEL to run on inexpensive commercial, off-the-shelf (COTS) hardware. In this paper, the authors describe key aspects of ANVEL and its development, as well as several initial applications of the system.

Real-Time Systems

DTIC Science & Technology

1992-02-01

Postgraduate School Autonomous Under Vehicle (AUV) are then examined. Autonomous underwater vehicle (AUV), hard real-time system, real - time operating system , real-time programming language, real-time system, soft real-time system.

Field dynamics inference via spectral density estimation

NASA Astrophysics Data System (ADS)

Frank, Philipp; Steininger, Theo; Enßlin, Torsten A.

2017-11-01

Stochastic differential equations are of utmost importance in various scientific and industrial areas. They are the natural description of dynamical processes whose precise equations of motion are either not known or too expensive to solve, e.g., when modeling Brownian motion. In some cases, the equations governing the dynamics of a physical system on macroscopic scales occur to be unknown since they typically cannot be deduced from general principles. In this work, we describe how the underlying laws of a stochastic process can be approximated by the spectral density of the corresponding process. Furthermore, we show how the density can be inferred from possibly very noisy and incomplete measurements of the dynamical field. Generally, inverse problems like these can be tackled with the help of Information Field Theory. For now, we restrict to linear and autonomous processes. To demonstrate its applicability, we employ our reconstruction algorithm on a time-series and spatiotemporal processes.

Field dynamics inference via spectral density estimation.

PubMed

Frank, Philipp; Steininger, Theo; Enßlin, Torsten A

2017-11-01

Stochastic differential equations are of utmost importance in various scientific and industrial areas. They are the natural description of dynamical processes whose precise equations of motion are either not known or too expensive to solve, e.g., when modeling Brownian motion. In some cases, the equations governing the dynamics of a physical system on macroscopic scales occur to be unknown since they typically cannot be deduced from general principles. In this work, we describe how the underlying laws of a stochastic process can be approximated by the spectral density of the corresponding process. Furthermore, we show how the density can be inferred from possibly very noisy and incomplete measurements of the dynamical field. Generally, inverse problems like these can be tackled with the help of Information Field Theory. For now, we restrict to linear and autonomous processes. To demonstrate its applicability, we employ our reconstruction algorithm on a time-series and spatiotemporal processes.

Design and Analysis of Morpheus Lander Flight Control System

NASA Technical Reports Server (NTRS)

Jang, Jiann-Woei; Yang, Lee; Fritz, Mathew; Nguyen, Louis H.; Johnson, Wyatt R.; Hart, Jeremy J.

2014-01-01

The Morpheus Lander is a vertical takeoff and landing test bed vehicle developed to demonstrate the system performance of the Guidance, Navigation and Control (GN&C) system capability for the integrated autonomous landing and hazard avoidance system hardware and software. The Morpheus flight control system design must be robust to various mission profiles. This paper presents a design methodology for employing numerical optimization to develop the Morpheus flight control system. The design objectives include attitude tracking accuracy and robust stability with respect to rigid body dynamics and propellant slosh. Under the assumption that the Morpheus time-varying dynamics and control system can be frozen over a short period of time, the flight controllers are designed to stabilize all selected frozen-time control systems in the presence of parametric uncertainty. Both control gains in the inner attitude control loop and guidance gains in the outer position control loop are designed to maximize the vehicle performance while ensuring robustness. The flight control system designs provided herein have been demonstrated to provide stable control systems in both Draper Ares Stability Analysis Tool (ASAT) and the NASA/JSC Trick-based Morpheus time domain simulation.

Mapping a Path to Autonomous Flight in the National Airspace

NASA Technical Reports Server (NTRS)

Lodding, Kenneth N.

2011-01-01

The introduction of autonomous flight, whether military, commercial, or civilian, into the National Airspace System (NAS) will present significant challenges. Minimizing the impact and preventing the changes from becoming disruptive, rather than an enhancing technology will not be without difficulty. From obstacle detection and avoidance to real-time verification and validation of system behavior, there are significant problems which must be solved prior to the general acceptance of autonomous systems. This paper examines some of the key challenges and the multi-disciplinary collaboration which must occur for autonomous systems to be accepted as equal partners in the NAS.

A Briefing on Metrics and Risks for Autonomous Decision-Making in Aerospace Applications

NASA Technical Reports Server (NTRS)

Frost, Susan; Goebel, Kai Frank; Galvan, Jose Ramon

2012-01-01

Significant technology advances will enable future aerospace systems to safely and reliably make decisions autonomously, or without human interaction. The decision-making may result in actions that enable an aircraft or spacecraft in an off-nominal state or with slightly degraded components to achieve mission performance and safety goals while reducing or avoiding damage to the aircraft or spacecraft. Some key technology enablers for autonomous decision-making include: a continuous state awareness through the maturation of the prognostics health management field, novel sensor development, and the considerable gains made in computation power and data processing bandwidth versus system size. Sophisticated algorithms and physics based models coupled with these technological advances allow reliable assessment of a system, subsystem, or components. Decisions that balance mission objectives and constraints with remaining useful life predictions can be made autonomously to maintain safety requirements, optimal performance, and ensure mission objectives. This autonomous approach to decision-making will come with new risks and benefits, some of which will be examined in this paper. To start, an account of previous work to categorize or quantify autonomy in aerospace systems will be presented. In addition, a survey of perceived risks in autonomous decision-making in the context of piloted aircraft and remotely piloted or completely autonomous unmanned autonomous systems (UAS) will be presented based on interviews that were conducted with individuals from industry, academia, and government.

Autonomous Attitude Determination System (AADS). Volume 1: System description

NASA Technical Reports Server (NTRS)

Saralkar, K.; Frenkel, Y.; Klitsch, G.; Liu, K. S.; Lefferts, E.; Tasaki, K.; Snow, F.; Garrahan, J.

1982-01-01

Information necessary to understand the Autonomous Attitude Determination System (AADS) is presented. Topics include AADS requirements, program structure, algorithms, and system generation and execution.

A Single RF Emitter-Based Indoor Navigation Method for Autonomous Service Robots.

PubMed

Sherwin, Tyrone; Easte, Mikala; Chen, Andrew Tzer-Yeu; Wang, Kevin I-Kai; Dai, Wenbin

2018-02-14

Location-aware services are one of the key elements of modern intelligent applications. Numerous real-world applications such as factory automation, indoor delivery, and even search and rescue scenarios require autonomous robots to have the ability to navigate in an unknown environment and reach mobile targets with minimal or no prior infrastructure deployment. This research investigates and proposes a novel approach of dynamic target localisation using a single RF emitter, which will be used as the basis of allowing autonomous robots to navigate towards and reach a target. Through the use of multiple directional antennae, Received Signal Strength (RSS) is compared to determine the most probable direction of the targeted emitter, which is combined with the distance estimates to improve the localisation performance. The accuracy of the position estimate is further improved using a particle filter to mitigate the fluctuating nature of real-time RSS data. Based on the direction information, a motion control algorithm is proposed, using Simultaneous Localisation and Mapping (SLAM) and A* path planning to enable navigation through unknown complex environments. A number of navigation scenarios were developed in the context of factory automation applications to demonstrate and evaluate the functionality and performance of the proposed system.

A Single RF Emitter-Based Indoor Navigation Method for Autonomous Service Robots

PubMed Central

Sherwin, Tyrone; Easte, Mikala; Wang, Kevin I-Kai; Dai, Wenbin

2018-01-01

Location-aware services are one of the key elements of modern intelligent applications. Numerous real-world applications such as factory automation, indoor delivery, and even search and rescue scenarios require autonomous robots to have the ability to navigate in an unknown environment and reach mobile targets with minimal or no prior infrastructure deployment. This research investigates and proposes a novel approach of dynamic target localisation using a single RF emitter, which will be used as the basis of allowing autonomous robots to navigate towards and reach a target. Through the use of multiple directional antennae, Received Signal Strength (RSS) is compared to determine the most probable direction of the targeted emitter, which is combined with the distance estimates to improve the localisation performance. The accuracy of the position estimate is further improved using a particle filter to mitigate the fluctuating nature of real-time RSS data. Based on the direction information, a motion control algorithm is proposed, using Simultaneous Localisation and Mapping (SLAM) and A* path planning to enable navigation through unknown complex environments. A number of navigation scenarios were developed in the context of factory automation applications to demonstrate and evaluate the functionality and performance of the proposed system. PMID:29443906

Autonomous learning based on cost assumptions: theoretical studies and experiments in robot control.

PubMed

Ribeiro, C H; Hemerly, E M

2000-02-01

Autonomous learning techniques are based on experience acquisition. In most realistic applications, experience is time-consuming: it implies sensor reading, actuator control and algorithmic update, constrained by the learning system dynamics. The information crudeness upon which classical learning algorithms operate make such problems too difficult and unrealistic. Nonetheless, additional information for facilitating the learning process ideally should be embedded in such a way that the structural, well-studied characteristics of these fundamental algorithms are maintained. We investigate in this article a more general formulation of the Q-learning method that allows for a spreading of information derived from single updates towards a neighbourhood of the instantly visited state and converges to optimality. We show how this new formulation can be used as a mechanism to safely embed prior knowledge about the structure of the state space, and demonstrate it in a modified implementation of a reinforcement learning algorithm in a real robot navigation task.

Autonomous navigation using lunar beacons

NASA Technical Reports Server (NTRS)

Khatib, A. R.; Ellis, J.; French, J.; Null, G.; Yunck, T.; Wu, S.

1983-01-01

The concept of using lunar beacon signal transmission for on-board navigation for earth satellites and near-earth spacecraft is described. The system would require powerful transmitters on the earth-side of the moon's surface and black box receivers with antennae and microprocessors placed on board spacecraft for autonomous navigation. Spacecraft navigation requires three position and three velocity elements to establish location coordinates. Two beacons could be soft-landed on the lunar surface at the limits of allowable separation and each would transmit a wide-beam signal with cones reaching GEO heights and be strong enough to be received by small antennae in near-earth orbit. The black box processor would perform on-board computation with one-way Doppler/range data and dynamical models. Alternatively, GEO satellites such as the GPS or TDRSS spacecraft can be used with interferometric techniques to provide decimeter-level accuracy for aircraft navigation.

An autonomous observation and control system based on EPICS and RTS2 for Antarctic telescopes

NASA Astrophysics Data System (ADS)

Zhang, Guang-yu; Wang, Jian; Tang, Peng-yi; Jia, Ming-hao; Chen, Jie; Dong, Shu-cheng; Jiang, Fengxin; Wu, Wen-qing; Liu, Jia-jing; Zhang, Hong-fei

2016-01-01

For unattended telescopes in Antarctic, the remote operation, autonomous observation and control are essential. An EPICS-(Experimental Physics and Industrial Control System) and RTS2-(Remote Telescope System, 2nd Version) based autonomous observation and control system with remoted operation is introduced in this paper. EPICS is a set of open source software tools, libraries and applications developed collaboratively and used worldwide to create distributed soft real-time control systems for scientific instruments while RTS2 is an open source environment for control of a fully autonomous observatory. Using the advantage of EPICS and RTS2, respectively, a combined integrated software framework for autonomous observation and control is established that use RTS2 to fulfil the function of astronomical observation and use EPICS to fulfil the device control of telescope. A command and status interface for EPICS and RTS2 is designed to make the EPICS IOC (Input/Output Controller) components integrate to RTS2 directly. For the specification and requirement of control system of telescope in Antarctic, core components named Executor and Auto-focus for autonomous observation is designed and implemented with remote operation user interface based on browser-server mode. The whole system including the telescope is tested in Lijiang Observatory in Yunnan Province for practical observation to complete the autonomous observation and control, including telescope control, camera control, dome control, weather information acquisition with the local and remote operation.

Autonomic neural control of dynamic cerebral autoregulation in humans

NASA Technical Reports Server (NTRS)

Zhang, Rong; Zuckerman, Julie H.; Iwasaki, Kenichi; Wilson, Thad E.; Crandall, Craig G.; Levine, Benjamin D.

2002-01-01

BACKGROUND: The purpose of the present study was to determine the role of autonomic neural control of dynamic cerebral autoregulation in humans. METHODS AND RESULTS: We measured arterial pressure and cerebral blood flow (CBF) velocity in 12 healthy subjects (aged 29+/-6 years) before and after ganglion blockade with trimethaphan. CBF velocity was measured in the middle cerebral artery using transcranial Doppler. The magnitude of spontaneous changes in mean blood pressure and CBF velocity were quantified by spectral analysis. The transfer function gain, phase, and coherence between these variables were estimated to quantify dynamic cerebral autoregulation. After ganglion blockade, systolic and pulse pressure decreased significantly by 13% and 26%, respectively. CBF velocity decreased by 6% (P<0.05). In the very low frequency range (0.02 to 0.07 Hz), mean blood pressure variability decreased significantly (by 82%), while CBF velocity variability persisted. Thus, transfer function gain increased by 81%. In addition, the phase lead of CBF velocity to arterial pressure diminished. These changes in transfer function gain and phase persisted despite restoration of arterial pressure by infusion of phenylephrine and normalization of mean blood pressure variability by oscillatory lower body negative pressure. CONCLUSIONS: These data suggest that dynamic cerebral autoregulation is altered by ganglion blockade. We speculate that autonomic neural control of the cerebral circulation is tonically active and likely plays a significant role in the regulation of beat-to-beat CBF in humans.