Publications

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The purpose of this LDRD is to develop technology allowing warfighters to provide high-level commands to their unmanned assets, freeing them to command a group of them or commit the bulk of their attention elsewhere. To this end, a brain-emulating cognition and control architecture (BECCA) was developed, incorporating novel and uniquely capable feature creation and reinforcement learning algorithms. BECCA was demonstrated on both a mobile manipulator platform and on a seven degree of freedom serial link robot arm. Existing military ground robots are almost universally teleoperated and occupy the complete attention of an operator. They may remove a soldier from harm's way, but they do not necessarily reduce manpower requirements. Current research efforts to solve the problem of autonomous operation in an unstructured, dynamic environment fall short of the desired performance. In order to increase the effectiveness of unmanned vehicle (UV) operators, we proposed to develop robots that can be 'directed' rather than remote-controlled. They are instructed and trained by human operators, rather than driven. The technical approach is modeled closely on psychological and neuroscientific models of human learning. Two Sandia-developed models are utilized in this effort: the Sandia Cognitive Framework (SCF), a cognitive psychology-based model of human processes, and BECCA, a psychophysical-based model of learning, motor control, and conceptualization. Together, these models span the functional space from perceptuo-motor abilities, to high-level motivational and attentional processes.

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As part of DARPA Information Processing Technology Office (IPTO) Software for Distributed Robotics (SDR) Program, Sandia National Laboratories has developed analysis and control software for coordinating tens to thousands of autonomous cooperative robotic agents (primarily unmanned ground vehicles) performing military operations such as reconnaissance, surveillance and target acquisition; countermine and explosive ordnance disposal; force protection and physical security; and logistics support. Due to the nature of these applications, the control techniques must be distributed, and they must not rely on high bandwidth communication between agents. At the same time, a single soldier must easily direct these large-scale systems. Finally, the control techniques must be provably convergent so as not to cause undo harm to civilians. In this project, provably convergent, moderate communication bandwidth, distributed control algorithms have been developed that can be regulated by a single soldier. We have simulated in great detail the control of low numbers of vehicles (up to 20) navigating throughout a building, and we have simulated in lesser detail the control of larger numbers of vehicles (up to 1000) trying to locate several targets in a large outdoor facility. Finally, we have experimentally validated the resulting control algorithms on smaller numbers of autonomous vehicles.

The concept of genetic divisors can be given a quantitative measure with a non-Archimedean p-adic metric that is both computationally convenient and physically motivated. For two particles possessing distinct mass parameters x and y, the metric distance D(x, y) is expressed on the field of rational numbers Q as the inverse of the greatest common divisor [gcd (x , y)]. As a measure of genetic similarity, this metric can be applied to (1) the mass numbers of particle states and (2) the corresponding subgroup orders of these systems. The use of the Bezout identity in the form of a congruence for the expression of the gcd (x , y) corresponding to the v{sub e} and {sub {mu}} neutrinos (a) connects the genetic divisor concept to the cosmic seesaw congruence, (b) provides support for the {delta}-conjecture concerning the subgroup structure of particle states, and (c) quantitatively strengthens the interlocking relationships joining the values of the prospectively derived (i) electron neutrino (v{sub e}) mass (0.808 meV), (ii) muon neutrino (v{sub {mu}}) mass (27.68 meV), and (iii) unified strong-electroweak coupling constant ({alpha}*{sup -1} = 34.26).

The construction of inverse states in a finite field F{sub P{sub P{alpha}}} enables the organization of the mass scale by associating particle states with residue class designations. With the assumption of perfect flatness ({Omega}total = 1.0), this approach leads to the derivation of a cosmic seesaw congruence which unifies the concepts of space and mass. The law of quadratic reciprocity profoundly constrains the subgroup structure of the multiplicative group of units F{sub P{sub {alpha}}}* defined by the field. Four specific outcomes of this organization are (1) a reduction in the computational complexity of the mass state distribution by a factor of {approximately}10{sup 30}, (2) the extension of the genetic divisor concept to the classification of subgroup orders, (3) the derivation of a simple numerical test for any prospective mass number based on the order of the integer, and (4) the identification of direct biological analogies to taxonomy and regulatory networks characteristic of cellular metabolism, tumor suppression, immunology, and evolution. It is generally concluded that the organizing principle legislated by the alliance of quadratic reciprocity with the cosmic seesaw creates a universal optimized structure that functions in the regulation of a broad range of complex phenomena.

Arithmetic conditions relating particle masses can be defined on the basis of (1) the supersymmetric conservation of congruence and (2) the observed characteristics of particle reactions and stabilities. Stated in the form of common divisors, these relations can be interpreted as expressions of genetic elements that represent specific particle characteristics. In order to illustrate this concept, it is shown that the pion triplet ({pi}{sup {+-}}, {pi}{sup 0}) can be associated with the existence of a greatest common divisor d{sub 0{+-}} in a way that can account for both the highly similar physical properties of these particles and the observed {pi}{sup {+-}}/{pi}{sup 0} mass splitting. These results support the conclusion that a corresponding statement holds generally for all particle multiplets. Classification of the respective physical states is achieved by assignment of the common divisors to residue classes in a finite field F{sub P{sub {alpha}}} and the existence of the multiplicative group of units F{sub P{sub {alpha}}} enables the corresponding mass parameters to be associated with a rich subgroup structure. The existence of inverse states in F{sub P{sub {alpha}}} allows relationships connecting particle mass values to be conveniently expressed in a form in which the genetic divisor structure is prominent. An example is given in which the masses of two neutral mesons (K{degree} {r_arrow} {pi}{degree}) are related to the properties of the electron (e), a charged lepton. Physically, since this relationship reflects the cascade decay K{degree} {r_arrow} {pi}{degree} + {pi}{degree}/{pi}{degree} {r_arrow} e{sup +} + e{sup {minus}}, in which a neutral kaon is converted into four charged leptons, it enables the genetic divisor concept, through the intrinsic algebraic structure of the field, to provide a theoretical basis for the conservation of both electric charge and lepton number. It is further shown that the fundamental source of supersymmetry can be expressed in terms of hierarchical relationships between odd and even order subgroups of F{sub P{sub {alpha}}}, an outcome that automatically reflects itself in the phenomenon of fermion/boson pairing of individual particle systems. Accordingly, supersymmetry is best represented as a group rather than a particle property. The status of the Higgs subgroup of order 4 is singular; it is isolated from the hierarchical pattern and communicates globally to the mass scale through the seesaw congruence by (1) fusing the concepts of mass and space and (2) specifying the generators of the physical masses.

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This paper describes a method of modeling swarms of UAVs and/or fighter aircraft using particle simulation concepts. Recent investigations into the use of genetic algorithms to design neural networks for the control of autonomous vehicles (i.e., robots) led to the examination of methods of simulating large collections of robots. This paper describes the successful implementation of a model of swarm dynamics using particle simulation concepts. Several examples of the complex behaviors achieved in a target/interceptor scenario are presented.

We have developed a capability to make real time concentration measurements of individual chemicals in a complex mixture using a multispectral laser remote sensing system. Our chemical recognition and analysis software consists of three parts: (1) a rigorous multivariate analysis package for quantitative concentration and uncertainty estimates, (2) a genetic optimizer which customizes and tailors the multivariate algorithm for a particular application, and (3) an intelligent neural net chemical filter which pre-selects from the chemical database to find the appropriate candidate chemicals for quantitative analyses by the multivariate algorithms, as well as providing a quick-look concentration estimate and consistency check. Detailed simulations using both laboratory fluorescence data and computer synthesized spectra indicate that our software can make accurate concentration estimates from complex multicomponent mixtures. even when the mixture is noisy and contaminated with unknowns.

We have developed a capability to make real time concentration measurements of individual chemicals in a complex mixture using a multispectral laser remote sensing system. Our chemical recognition and analysis software consists of three parts: (1) a rigorous multivariate analysis package for quantitative concentration and uncertainty estimates, (2) a genetic optimizer which customizes and tailors the multivariate algorithm for a particular application, and (3) an intelligent neural net chemical filter which pre-selects from the chemical database to find the appropriate candidate chemicals for quantitative analyses by the multivariate algorithms, as well as providing a quick-look concentration estimate and consistency check. Detailed simulations using both laboratory fluorescence data and computer synthesized spectra indicate that our software can make accurate concentration estimates from complex multicomponent mixtures, even when the mixture is noisy and contaminated with unknowns.

Relativistic high current electron beams can be transported long distances across the geomagnetic field using the IFR (Ion focused Regime) technique. IFR is a method of providing strong electrostatic focusing and guiding of the beam. The guiding is sufficiently strong to allow the beam to transport any angle with respect to geomagnetic field. In the IFR method, first an ionizing laser (or any ionizing method) is used to create a preionized cylindrical channel.

Recent experiments on Lawrence Livermore's ATA indicate that there may be problems with the IFR (Ion Focused Regime) transport of the relativistic electron beam (REB) through the ATA accelerator. For beam currents greater than about 7-kA, the beam is observed to be inverse-tailored with the beam radius increasing from beam head to tail. This inverse-tailoring is considered unfavorable for endo- atmospheric beam propagation. An unusual feature of ATA's laser- produced IFR channel is that it has a rectangular cross-section. One possible explanation for the lack of good beam transport may be ion motion in the IFR channel which disrupts the tail of the beam. In this report an ATA-like electron beam, propagating on a laser-ionized rectangular IFR channel is simulated using the 3-D magnetostatic code BUCKSHOT. The simulations demonstrate that non-axisymmetric ion motion, similar to the ion hose instability, can produce an inverse- tailored electron beam similar to those found in the experiment. The simulation results should be relevant to upcoming TROLL experiments with a laser-ionized IFR channel, with several beam parameters similar to ATA's. 1 ref., 22 figs.

One critical issue to be addressed in the compact recirculating linac program concerns optimal beam injection into a racetrack-shaped accelerator. There are at least three candidates, axial beam injection, tangential beam injection, and laser-channel-assisted beam injection. In this report these three approaches are examined using computer simulation techniques. 3 refs., 27 figs., 2 tabs.

A very simple algorithm is presented that allows particles to be loaded or initialized in a particle simulation code. The algorithm can load particle positions or velocities according to any well- behaved density or distribution function. Sample codes are given in 1, 2, and 3 dimensions. The technique is highly efficient. 2 refs., 9 figs., 3 tabs.

Preliminary BUCKSHOT simulations of a recirculating linear accelerator have been made. Two accelerator configurations have been examined for a variety of beam currents (10-40 kA). The first configuration is an attempt to simulate conditions accessible to near-term experiments. The second configuration tries to mock up a next generation application type machine. 3 figs.