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All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Review of Multi-Agent Algorithms for Collective Behavior: a Structural Taxonomy

In this paper, we review multi-agent collective behavior algorithms in the literature and classify them according to their underlying mathematical structure. For each mathematical technique, we identify the multi-agent coordination tasks it can be applied to, and we analyze its scalability, bandwidth use, and demonstrated maturity. We highlight how versatile techniques such as artificial potential functions can be used for applications ranging from low-level position control to high-level coordination and task allocation, we discuss possible reasons for the slow adoption of complex distributed coordination algorithms in the field, and we highlight areas for further research and development.

Pavone, Marco↗
NASA NTRS1998

Distributed Control with Collective Intelligence

We consider systems of interacting reinforcement learning (RL) algorithms that do not work at cross purposes , in that their collective behavior maximizes a global utility function. We call such systems COllective INtelligences (COINs). We present the theory of designing COINs. Then we present experiments validating that theory in the context of two distributed control problems: We show that COINs perform near-optimally in a difficult variant of Arthur's bar problem [Arthur] (and in particular avoid the tragedy of the commons for that problem), and we also illustrate optimal performance in the master-slave problem.

Wolpert, David H.↗
NASA NTRS2014

Reducing Size, Weight, and Power (SWaP) of Perception Systems in Small Autonomous Aerial Systems

The objectives are to examine recent trends in the reduction of size, weight, and power (SWaP) requirements of sensor systems for environmental perception and to explore new technology that may overcome limitations in current systems. Improving perception systems to facilitate situation awareness is critical in the move to introduce increasing autonomy in aerial systems. Whether the autonomy is in the current state-of-the-art of increasing automation or is enabling cognitive decisions that facilitate adaptive behavior, collection of environmental information and fusion of that information into knowledge that can direct actuation is imperative to decisions resulting in appropriate behavior. Artificial sensory systems such as cameras, radar, LIDAR, and acoustic sensors have been in use on aircraft for many years but, due to the large size and weight of the airplane and electrical power made available through powerful engines, the SWaP requirements of these sensors was inconsequential. With the proliferation of Remote Piloted Vehicles (RPV), the trend is in significant reduction in SWaP of the vehicles. This requires at least an equivalent reduction in SWaP for the sensory systems. A survey of some currently available sensor systems and changing technology will reveal the trend toward reduction of SWaP of these systems and will predict future reductions. A new technology will be introduced that provides an example of a desirable new trend. A new device replaces multiple conventional sensory devices facilitating synchronization, localization, altimetry, collision avoidance, terrain mapping, and data communication in a single integrated, small form-factor, extremely lightweight, and low power device that it is practical for integration into small autonomous vehicles and can facilitate cooperative behavior. The technology is based on Ultra WideBand (UWB) radio using short pulses of energy rather than continuous sine waves. The characteristics of UWB yield several desirable characteristics to facilitate integration of perception for autonomous activities. The capabilities of this device and its limitations will be assessed.

Jones, Kennie H.↗
NASA NTRS1993

Study of bubble behavior in weightlessness (effects of thermal gradient and acoustic stationary wave) (M-16)

The aim of this experiment is to understand how bubbles behave in a thermal gradient and acoustic stationary wave under microgravity. In microgravity, bubble or bubbles in a liquid will not rise upward as they do on Earth but will rest where they are formed because there exists no gravity-induced buoyancy. We are interested in how bubbles move and in the mechanisms which support the movement. We will try two ways to make bubbles migrate. The first experiment concerns behavior of bubbles in a thermal gradient. It is well known than an effect of surface tension which is masked by gravity on the ground becomes dominant in microgravity. The surface tension on the side of the bubble at a lower temperature is stronger than at a higher temperature. The bubble migrates toward the higher temperature side due to the surface tension difference. The migration speed depends on the so-called Marangoni number, which is a function of the temperature difference, the bubble diameter, liquid viscosity, and thermal diffusivity. At present, some experimental data about migration speeds in liquids with very small Marangoni numbers were obtained in space experiments, but cases of large Marangoni number are rarely obtained. In our experiment a couple of bubbles are to be injected into a cell filled with silicon oil, and the temperature gradient is to be made gradually in the cell by a heater and a cooler. We will be able to determine migration speeds in a very wide range of Marangoni numbers, as well as study interactions between the bubbles. We will observe bubble movements affected by hydrodynamical and thermal interactions, the two kinds of interactions which occur simultaneously. These observation data will be useful for analyzing the interactions as well as understanding the behavior of particles or drops in materials processing. The second experiment concerns bubble movement in an acoustic stationary wave. It is known that a bubble in a stationary wave moves toward the node or the loop according to whether its diameter is larger or smaller than that of the main resonant radius. In our experiment fine bubbles will be observed to move according to an acoustic field formed in a cylindrical cell. The existence of bubbles varies the acoustic speed, and the interactive force between bubbles will make the bubble behavior collective and complicated. This experiment will be very useful to development of bubble removable technology as well as to the understanding of bubble behavior.

Azuma, H.↗
NASA NTRS2005

Evolving Multi Rover Systems in Dynamic and Noisy Environments

In this chapter, we address how to evolve control strategies for a collective: a set of entities that collectively strives to maximize a global evaluation function that rates the performance of the full system. Addressing such problems by directly applying a global evolutionary algorithm to a population of collectives is unworkable because the search space is prohibitively large. Instead, we focus on evolving control policies for each member of the collective, where each member is trying to maximize the fitness of its own population. The main difficulty with this approach is creating fitness evaluation functions for the members of the collective that induce the collective to achieve high performance with respect to the system level goal. To overcome this difficulty, we derive member evaluation functions that are both aligned with the global evaluation function (ensuring that members trying to achieve high fitness results in a collective with high fitness) and sensitive to the fitness of each member (a member's fitness depends more on its own actions than on actions of other members). In a difficult rover coordination problem in dynamic and noisy environments, we show how to construct evaluation functions that lead to good collective behavior. The control policy evolved using aligned and member-sensitive evaluations outperforms global evaluation methods by up to a factor of four. in addition we show that the collective continues to perform well in the presence of high noise levels and when the environment is highly dynamic. More notably, in the presence of a larger number of rovers or rovers with noisy sensors, the improvements due to the proposed method become significantly more pronounced.

Tumer, Kagan↗
NASA NTRS2012

Multiscale Dynamics of Solar Magnetic Structures

Multiscale topological complexity of the solar magnetic field is among the primary factors controlling energy release in the corona, including associated processes in the photospheric and chromospheric boundaries.We present a new approach for analyzing multiscale behavior of the photospheric magnetic flux underlying these dynamics as depicted by a sequence of high-resolution solar magnetograms. The approach involves two basic processing steps: (1) identification of timing and location of magnetic flux origin and demise events (as defined by DeForest et al.) by tracking spatiotemporal evolution of unipolar and bipolar photospheric regions, and (2) analysis of collective behavior of the detected magnetic events using a generalized version of the Grassberger-Procaccia correlation integral algorithm. The scale-free nature of the developed algorithms makes it possible to characterize the dynamics of the photospheric network across a wide range of distances and relaxation times. Three types of photospheric conditions are considered to test the method: a quiet photosphere, a solar active region (NOAA 10365) in a quiescent non-flaring state, and the same active region during a period of M-class flares. The results obtained show (1) the presence of a topologically complex asymmetrically fragmented magnetic network in the quiet photosphere driven by meso- and supergranulation, (2) the formation of non-potential magnetic structures with complex polarity separation lines inside the active region, and (3) statistical signatures of canceling bipolar magnetic structures coinciding with flaring activity in the active region. Each of these effects can represent an unstable magnetic configuration acting as an energy source for coronal dissipation and heating.

Magnetic fields↗
NASA NTRS1987

Kinetic aspects of magnetotail dynamics - Observations

The observed kinetic (as opposed to fluid) aspects of particle behavior in the geomagnetic tail are discussed. Such behavior has been observed from thermal plasma energies to energies a few MeV or more. The importance of recognizing and analyzing the kinetic behavior of tail particles is that it provides a powerful diagnostic tool for inferring the state of the local and remote environment and the mechanisms responsible for observed tail dynamics, and a way of determining when fluid analyses (relying upon moments such as bulk velocity and temperature) may be misleading. Thus kinetic analyses provide a valuable complement to fluid-dynamics-based studies of the collective behavior of geomagnetic tail particles. Observed kinetic effects can be analyzed to examine spatial gradients; convection electric fields, distances to source regions, source-region characteristics, magnetic-field topology, heating/acceleration mechanism, boundary characteristics, and remote mechanisms affecting local particle distributions.

Mitchell, D. G.↗
NASA NTRS2004

Coordination in Large Collectives

Finding the subset of a set of imperfect devices (e.g., nano or micro devices) that results in the best aggregate device is a challenging problem. It is an abstraction of what will likely be a major difficulty in designing and controlling systems of nano or micro-scale components, particularly when a large fraction of those components may be unreliable. Rather than approaching this as a passive search problem, we transform the problem into one of coordination in a complex system by imbuing each device with simple decision making ability. In doing so we face the challenge of determining what each component should attempt to do so that the collective behavior solves the overall problem. Furthermore, in this padicular instance, we face problems of scaling (number of components in the thousands to tens of thousands), observability (components have limited sensing capabilities), and reliability (the components are faulty). We present an approach based on deriving component goals that are aligned with the overall system goal (e.g., forming best aggregate device), and can be computed using information readily (e.g., locally) available to the components. Then, each component in such a collective uses a simple reinforcement learning algorithm to selfishly pursue its own goals. Because those goals are derived in a principled manner, there is no need to use external mechanisms to force collaboration or coordination among the components to ensure that the system reaches a globally desirable solution. The results show that not only this approach provides improvements of over an order of magnitude over both traditional search methods and traditional multi-agent methods, but that the gains increase with the size of the system. This latter result makes this method ideal for domains where the number of components is currently in the thousands and will reach millions in the near future.

Tumer, Kagan↗
NASA NTRS2013

Dynamics and Control of a Disordered System in Space

In this paper, we present some ideas regarding the modeling, dynamics and control aspects of granular spacecraft. Granular spacecraft are complex multibody systems composed of a spatially disordered distribution of a large number of elements, for instance a cloud of N grains in orbit, with N greater than 10(exp 3). These grains can be large (Cubesat-size) or small (mm-size), and can be active, i.e., a fully equipped vehicle capable sensing their own position and attitude, and enabled with propulsion means, or entirely passive. The ultimate objective would be to study the behavior of the single grains and of large ensembles of grains in orbit and to identify ways to guide and control the shape of a cloud composed of these grains so that it can perform a useful function in space, for instance, as an element of an optical imaging system for astrophysical applications. This concept, in which the aperture does not need to be continuous and monolithic, would increase the aperture size several times compared to large NASA observatories such as ATLAST, allowing for a true Terrestrial Planet Imager that would be able to resolve exo-planet details and do meaningful spectroscopy on distant world. In the paper, we address the modeling and autonomous operation of a distributed assembly (the cloud) of large numbers of highly miniaturized space-borne elements (the grains). A multi-scale, multi-physics model is proposed of the dynamics of the cloud in orbit, as well as a control law for cloud shape maintenance, and preliminary simulation studies yield an estimate of the computational effort, indicating a scale factor of approximately N(exp 1.4) as a function of the number of grains. A granular spacecraft can be defined as a collection of a large number of space-borne elements (in the 1000s) designed and controlled such that a desirable collective behavior emerges, either from the interactions among neighboring grains, and/or between the grains and the environment. In this paper, each grain is considered to be a highly miniaturized spacecraft which has limited size and mass, hence it has limited actuation, limited propulsive capability, limited power, limited sensing, limited communication, limited computational resources, limited range of motion, limited lifetime, and may be expendable. The modeling and dynamics of clouds of vehicles is more challenging than with conventional vehicles because we are faced with a probabilistic vehicle composed of a large number of physically disconnected vehicles. First, different scales of motion occur simultaneously in a cloud: translations and rotations of the cloud as a whole (macro-dynamics), relative rotation and translation of one cloud member with respect to another (meso-dynamics), and individual cloud member dynamics (micro-dynamics). Second, the control design needs to be tolerant of the system complexity, of the system architecture (centralized vs. decentralized large scale system control) as well as robust to un-modeled dynamics and noise sources. Figure 1, top left, shows the kinematic parameters of a 1000 element cloud in orbit. The motion of the system is described with respect to a local vertical-local horizontal (LV-LH) orbiting reference frame (x,y,z)=F(sub ORF) of origin O(sub ORF) which rotates with mean motion omega and orbital semi-major axis R(sub 0). The orbital geometry at the initial time is defined in terms of its six orbital elements, and the orbital dynamics equation for point O(sub ORF) is propagated forward in time under the influence of the gravitational field of the primary and other external perturbations, described below. The origin of this frame coincides with the initial position of the center of mass of the system, and the coordinate axes are z along the local vertical, x toward the flight direction, and y in the orbit normal direction. The assumptions we used to model the dynamics are as follows: 1) The inertial frame is fixed at Earth's center. 2) The orbiting Frame ORF follows Keplerian orbit. 3) the cloud system dynamics is referred to ORF. 4) the attitude of each grain uses the principal body frame as body fixed frame. 5) the atmosphere is assumed to be rigidly rotating with the Earth. Regarding the grains forming the cloud: 1) each grain is modeled as a rigid body; 2) a simple attitude estimator provides attitude estimates, 3) a simple guidance logic commands the position and attitude of each grain, 4) a simple local feedback controller based on PD control of local states is used to stabilize the attitude of the vehicle. Regarding the cloud: 1) the cloud as a whole is modeled as an equivalent rigid body in orbit, and 2) an associated graph establishes agent connectivity and enables coupling between modes of motion at the micro and macro scales; 3) a simple guidance and estimation logic is modeled to estimate and command the attitude of this equivalent rigid body; 4) a cloud shape maintenance controller is based on the dynamics of a stable virtual truss in the orbiting frame. Regarding the environmental perturbations acting on the cloud: 1) a non-spherical gravity field including JO (Earth's spherical field) zonal component, J2 (Earth's oblateness) and J3 zonal components is implemented; 2) atmospheric drag is modeled with an exponential model; 3) solar pressure is modeled assuming the Sun is inertially fixed; and 4) the Earth's magnetic field is model using an equivalent dipole model. The equations of motion are written in a referential system with respect to the origin of the orbiting frame and the state is propagated forward in time using an incremental predictor-corrector scheme. A representative cloud with varying number of grains is simulated to identify the limitations in computation time as the number of grains grows. We derive a control law to track a desired surface in the ORF (equivalently to maintain a reference cloud shape) by defining an error from a desired surface shape, and designing a control law that is exponentially stable and reduces the tracking error to zero. Figure 1 (top right) shows a comparison of various requirements for simulation of single spacecraft vs. granular spacecraft, indicating the high degree of complexity that needs to be taken into consideration. The ORF components of control force required by one of the grains is, for this particular case, in the micro-Newton range. However, no attempt has been made yet to reconfigure (or re-orient) the cloud configuration internally, for which forces in the milli-Newton level are expected, depending on the time required to do the reconfiguration. Figure 1, bottom, shows the computation time as a function of the number of grains, indicating an order N(exp 1.43) scaling on a 8 Gb, 1067 MHz RAM MacOSX computer with a 3.06 GHz Intel Core 2 Duo processor. With this metric, the same simulation for a system of N=1000 grains would take 5.4 hours, and 146 hours (i.e., 6 days) for a system with N=10,000 grains. Therefore, efficient ways to simulate this complex system, where not only the time scales of natural system dynamics, but also the sampling times of the Guidance, Navigation, and Control are included, remain to be explored. Additional details on the cloud modeling, dynamics, and control will be described in the paper.

simulation↗
NASA NTRS1975

On ionospheric aerodynamics

This paper presents theoretical methods to determine the gas dynamic and the electrostatic effects due to the interaction caused by a rapidly moving body in the ionosphere. The principles of the methods are derived from the kinetic theory of collision-free plasma. It is shown that the collective behavior of the collision-free plasma makes it possible to use the fluid approach to treat the problems of ionospheric aerodynamics. Various solutions to the system of fluid and field equations that have direct bearing on the ionospheric aerodynamics are presented and discussed. Physical significances of the mathematical results are stressed. Some outstanding unsolved problems in ionospheric aerodynamics are elaborated and discussed.

Liu, V. C.↗
NASA NTRS1977

Quantum chemical calculations of interatomic potentials for computer simulation of solids

A comprehensive mathematical model by which the collective behavior of a very large number of atoms within a metal or alloy can accurately be simulated was developed. Work was done in order to predict and modify the strength of materials to suit our technological needs. The method developed is useful in studying atomic interactions related to dislocation motion and crack extension.

Source record↗
NASA NTRS1983

Settling of fixed erythrocyte suspension droplets

It is pointed out that when particles behave collectively rather than individually, the fractionation of micron-size particles on the basis of size, density, and surface characteristics by centrifugation and electrophoresis is hindered. The formation and sedimentation of droplets containing particles represent an extreme example of collective behavior and pose a major problem for these separation methods when large quantities of particles need to be fractionated. Experiments are described that measure droplet sizes and settling rates for a variety of particles and droplets. Expressions relating the particle concentration in a drop to measurable quantities of the fluids and particles are developed. The number of particles in each droplet is then estimated, together with the effective droplet density. Red blood cells from different animals fixed in glutaraldehyde provide model particle groups.

Omenyi, S. N.↗
NASA NTRS1984

Reactions to community noise

Most of the research on reactions of people to community noise is divided into studies of annoyance as measured by attitude surveys and annoyance as measured by complaint behavior, including legal actions. This research has provided means of testing the concept promulgated over 20 years ago that the average amount of noise energy from significant sources that intrudes daily into houses and living areas can be used to predict the impact of the noise on people in a community. However, research data on annoyance and complaint behavior collected over the past 10 to 20 years have shown that there are significant limitations and variables that must be considered in the fair application of the noise energy concept in its simplest form.

Source record↗
NASA NTRS1985

A granular flow model for dense planetary rings

In the present study of the viscosity of a differentially rotating particle disk, in the limiting case where the particles are densely packed and their collective behavior resembles that of a liquid, the pressure tensor is derived from both the equations of hydrodynamics and a simple kinetic model of collisions due to Haff (1983). Density waves and narrow circular rings are unstable if the liquid approximation applies, and the consequent nonlinear perturbations may generate 'splashing' of the ring material in the vertical direction. These results are pertinent to the origin of the ellipticities of ringlets, the nonaxisymmetric features near the outer edge of the Saturn B ring, and unexplained residuals in kinematic models of the Saturn and Uranus rings.

Borderies, N.↗
NASA NTRS1992

Energetic ions as remote probes of X type neutral lines in the geomagnetic tail

The study presents a summary of particle orbit signatures of a neutral line in the geomagnetic tail current sheet (CS) as a function of spatial position along the CS boundary layer, as well as within the CS. Six types of CS particle orbits are reviewed: transient B sub z, transient X line, quasi-trapped, trapped, noncrossing X line, and limiting (singular) cases. It is found that for single particle dynamics in a current sheet with neutral line, the phase space ridge is predicted to be found throughout the current sheet if it is not destroyed by collective behavior. An initially tailward flowing distribution causes asymmetries in distributions earthward vs tailward of the neutral line. It is suggested that the chaotic pitch angle scattering may be a dominant mechanism to produce nightside proton isotropy in the auroral zones.

Speiser, T. W.↗
NASA NTRS1992

Solar Array Module Plasma Interaction Experiment (SAMPIE)

The objective of the Solar Array Module Plasma Interaction Experiment (SAMPIE) is to investigate, by means of a shuttle-based flight experiment and relevant ground-based testing, the arcing and current collection behavior of materials and geometries likely to be exposed to the LEO plasma on high-voltage space power systems, in order to minimize adverse environmental interactions. An overview of the SAMPIE program is presented in outline and graphical form.

Ferguson, Dale C.↗
NASA NTRS1993

Micro- to macroscale perspectives on space plasmas

The Earth's magnetosphere is the most accessible of natural collisionless plasma environments; an astrophysical plasma 'laboratory'. Magnetospheric physics has been in an exploration phase since its origin 35 years ago but new coordinated, multipoint observations, theory, modeling, and simulations are moving this highly interdisciplinary field of plasma science into a new phase of synthesis and understanding. Plasma systems are ones in which binary collisions are relatively negligible and collective behavior beyond the microscale emerges. Most readily accessible natural plasma systems are collisional and nearest-neighbor classical interactions compete with longer-range plasma effects. Except for stars, most space plasmas are collisionless, however, and the effects of electrodynamic coupling dominate. Basic physical processes in such collisionless plasmas occur at micro-, meso-, and macroscales that are not merely reducible to each other in certain crucial ways as illustrated for the global coupling of the Earth's magnetosphere and for the nonlinear dynamics of charged particle motion in the magnetotail. Such global coupling and coherence makes the geospace environment, the domain of solar-terrestrial science, the most highly coupled of all physical geospheres.

Eastman, Timothy E.↗