This PDF file contains the front matter associated with SPIE Proceedings Volume 7321, including the Title Page, Copyright information, Table of Contents, Introduction, and the Conference Committee listing.

SERS-active substrates are fabricated by oblique angle deposition and patterned by a polymer-molding technique to provide a uniform array for high throughput biosensing and multiplexing. Using a conventional SERS-active molecule, 1,2-Bis(4-pyridyl)ethylene (BPE), we show that this device provides a uniform Raman signal enhancement from well to well. The patterning technique employed in this study demonstrates a flexibility allowing for patterning control and customization, and performance optimization of the substrate. Avian influenza is analyzed to demonstrate the ability of this multi-well patterned SERS substrate for biosensing.

Diatoms are single-celled photosynthetic algae that make silica shells or "frustules" with intricate features patterned at the nano and microscales. In this study, antibody-functionalized diatom biosilica frustules serve as a biosensor platform for selective and label free antibody-antigen immunocomplex formation by enhanced photoluminescence. Biosilica frustules of 10 micron diameter were isolated from cells of the centric marine diatom Cyclotella sp. They were then mounted on glass and covalently functionalized with the model antibody Rabbit Immunoglobulin G (IgG) to yield a uniform nanostructured surface that selectively binds to its complimentary antigen, Goat anti-Rabbit IgG. Diatom frustules possess an intrinsic capacity to emit blue light when excited with a UV laser light source, a property called photoluminescence. Binding the antibody-functionalized diatom frustule with its complimentary antigen selectively enhanced the intrinsic photoluminescence intensity of the diatom frustule by a factor of three, whereas challenging the antibody-functionalized diatom frustule with a non-complimentary antigen, Goat anti-human IgG did not change the intrinsic photoluminescence intensity. The nucleophilic immunocomplex increases the photoluminescence by donating electrons to non-radiative sites on the photoluminescent diatom biosilica, thereby decreasing non-radiative electron decay and increasing radiative emission. The intensified photoluminescence intensity is correlated to the antigen, goat anti-rabbit IgG concentration, with a binding constant of 2.8 ± 0.7x10^-7 M.

Electrochemical aptamer-based sensors (E-AB sensors) represent a promising new approach to the detection of small molecules. E-AB sensors comprise an aptamer that is attached at one end to an electrode surface. The distal end of the aptamer probed is modified with an electroactive redox marker for signal transduction. Herein we report on the optimization of a cocaine-detecting E-AB sensor via optimization of the geometry of the aptamer. We explore two new aptamer architectures, one in which we concatenate three cocaine aptamers into a poly-aptamer and a second in which we divide the cocaine aptamer into pieces connected via an unstructured, 60-thymine linker. Both of these structures are designed such that the reporting redox tag will be located farther from the electrode in the unfolded, target-free conformation. Consistent with this, we find that signal gains of these two constructs are two to three times higher than that of the original E-AB architecture. Likewise all three architectures are selective enough to deploy directly in complex sample matrices, such as undiluted whole blood, with all three sensors successfully detecting the presence of cocaine. The findings in this ongoing study should be of value in future efforts to optimize the signaling of electrochemical aptamer-based sensors.

Three approaches to detection of biological agents based on biological processes will be presented. The first example demonstrates the use of dendrimers to deliver a membrane-impermeable fluorescent dye into live bacteria, similar to viral infection and delivery of DNA/RNA into a bacterial cell. The second example mimics collection and capture of airborne biological particles by the respiratory mucosa through the use of a hygroscopic sensing membrane. The third example is based on the use of multiple fluorescent probes with diverse functionalities to detect airborne biological agents in a manner similar to the olfactory receptors in the nasal tract.

Robotics are rapidly becoming an integral tool on the battlefield and in homeland security, replacing humans in hazardous conditions. To enhance the effectiveness of robotic assets and their interaction with human operators, smart sensors are required to give more autonomous function to robotic platforms. Biologically inspired sensors are an essential part of this development of autonomous behavior and can increase both capability and performance of robotic systems. Smart, biologically inspired acoustic sensors have the potential to extend autonomous capabilities of robotic platforms to include sniper detection, vehicle tracking, personnel detection, and general acoustic monitoring. The key to enabling these capabilities is biomimetic acoustic processing using a time domain processing method based on the neural structures of the mammalian auditory system. These biologically inspired algorithms replicate the extremely adaptive processing of the auditory system yielding high sensitivity over broad dynamic range. The algorithms provide tremendous robustness in noisy and echoic spaces; properties necessary for autonomous function in real world acoustic environments. These biomimetic acoustic algorithms also provide highly accurate localization of both persistent and transient sounds over a wide frequency range, using baselines on the order of only inches. A specialized smart sensor has been developed to interface with an iRobot Packbot® platform specifically to enhance its autonomous behaviors in response to personnel and gunfire. The low power, highly parallel biomimetic processor, in conjunction with a biomimetic vestibular system (discussed in the companion paper), has shown the system's autonomous response to gunfire in complicated acoustic environments to be highly effective.

Limited autonomous behaviors are fast becoming a critical capability in the field of robotics as robotic applications are used in more complicated and interactive environments. As additional sensory capabilities are added to robotic platforms, sensor fusion to enhance and facilitate autonomous behavior becomes increasingly important. Using biology as a model, the equivalent of a vestibular system needs to be created in order to orient the system within its environment and allow multi-modal sensor fusion. In mammals, the vestibular system plays a central role in physiological homeostasis and sensory information integration (Fuller et al, Neuroscience 129 (2004) 461-471). At the level of the Superior Colliculus in the brain, there is multimodal sensory integration across visual, auditory, somatosensory, and vestibular inputs (Wallace et al, J Neurophysiol 80 (1998) 1006-1010), with the vestibular component contributing a strong reference frame gating input. Using a simple model for the deep layers of the Superior Colliculus, an off-the-shelf 3-axis solid state gyroscope and accelerometer was used as the equivalent representation of the vestibular system. The acceleration and rotational measurements are used to determine the relationship between a local reference frame of a robotic platform (an iRobot Packbot®) and the inertial reference frame (the outside world), with the simulated vestibular input tightly coupled with the acoustic and optical inputs. Field testing of the robotic platform using acoustics to cue optical sensors coupled through a biomimetic vestibular model for "slew to cue" gunfire detection have shown great promise.

We are developing low-power microcircuitry that implements classification and direction finding systems of very small size and small acoustic aperture. Our approach was inspired by the fact that small mammals are able to localize sounds despite their ears may be separated by as little as a centimeter. Gerbils, in particular are good low-frequency localizers, which is a particularly difficult task, since a wavelength at 500 Hz is on the order of two feet. Given such signals, crosscorrelation- based methods to determine direction fail badly in the presence of a small amount of noise, e.g. wind noise and noise clutter common to almost any realistic environment. Circuits are being developed using both analog and digital techniques, each of which process signals in fundamentally the same way the peripheral auditory system of mammals processes sound. A filter bank represents filtering done by the cochlea. The auditory nerve is implemented using a combination of an envelope detector, an automatic gain stage, and a unique one-bit A/D, which creates what amounts to a neural impulse. These impulses are used to extract pitch characteristics, which we use to classify sounds such as vehicles, small and large weaponry from AK-47s to 155mm cannon, including mortar launches and impacts. In addition to the pitchograms, we also use neural nets for classification.

The supersensitive ears of the parasitoid fly Ormia ochracea have inspired researchers to develop bio-inspired directional microphone for sound localization. Although the fly ear is optimized for localizing the narrow-band calling song of crickets at 5 kHz, experiments and simulation have shown that it can amplify directional cues for a wide frequency range. In this article, a theoretical investigation is presented to study the use of fly-ear inspired directional microphones for gunshot localization. Using an equivalent 2-DOF model of the fly ear, the time responses of the fly ear structure to a typical shock wave are obtained and the associated time delay is estimated by using cross-correlation. Both near-field and far-field scenarios are considered. The simulation shows that the fly ear can greatly amplify the time delay by ~20 times, which indicates that with an interaural distance of only 1.2 mm the fly ear is able to generate a time delay comparable to that obtained by a conventional microphone pair with a separation as large as 24 mm. Since the parameters of the fly ear structure can also be tuned for muzzle blast and other impulse stimulus, fly-ear inspired acoustic sensors offers great potential for developing portable gunshot localization systems.

We present a microscale implementation of an acoustic localization device inspired by the auditory organ of the parasitic fly Ormia Ochracea. The device consists of a pair of circular membranes coupled together with a beam. The coupling serves to amplify the difference in magnitude and phase between the response of the two membranes as the incident angle of the sound changes, allowing directional information to be deduced from the coupled device response. The device was fabricated using MEMS technology and tested with laser Doppler vibrometery. Amplification factors of up to 7 times were observed in the phase difference between the membranes at 90 degree incident sound angles, with directional sensitivity of up to 0.3μs/degree.

Inspired by the snake locomotion, modular snake robots have different locomotion capabilities by coordinating their internal degrees of freedom. They have the potential to access restricted spaces where humans cannot go. They can also traverse rough terrains while conventional wheeled and legged robots cannot. Modular robots have other features including versatility, robustness, low-cost, and fast-prototyping. We have built our first prototype that costs less than $200. In this paper, we describe the electronics architecture of our prototyped robot, and present a model for the locomotion of pitch-yaw snake robots that allows them to perform different gaits. Each mode of the robot is controlled by a sinusoidal oscillator with four parameters: amplitude, frequency, phase, and offset. We show the parameters that achieve snake-like locomotion.

Research from the Institute for Collaborative Biotechnologies (ICB) at the University of California at Santa Barbara (UCSB) has identified swarming algorithms used by flocks of birds and schools of fish that enable these animals to move in tight formation and cooperatively track prey with minimal estimation errors, while relying solely on local communication between the animals. This paper describes ongoing work by UCSB, the University of Florida (UF), and the Toyon Research Corporation on the utilization of these algorithms to dramatically improve the capabilities of small unmanned aircraft systems (UAS) to cooperatively locate and track ground targets. Our goal is to construct an electronic system, called GeoTrack, through which a network of hand-launched UAS use dedicated on-board processors to perform multi-sensor data fusion. The nominal sensors employed by the system will EO/IR video cameras on the UAS. When GMTI or other wide-area sensors are available, as in a layered sensing architecture, data from the standoff sensors will also be fused into the GeoTrack system. The output of the system will be position and orientation information on stationary or mobile targets in a global geo-stationary coordinate system. The design of the GeoTrack system requires significant advances beyond the current state-of-the-art in distributed control for a swarm of UAS to accomplish autonomous coordinated tracking; target geo-location using distributed sensor fusion by a network of UAS, communicating over an unreliable channel; and unsupervised real-time image-plane video tracking in low-powered computing platforms.

Foveated imaging has been explored for compression and tele-presence, but gaps exist in the study of foveated imaging applied to acquisition and tracking systems. Results are presented from two sets of experiments comparing simple foveated and uniform resolution targeting (acquisition and tracking) algorithms. The first experiments measure acquisition performance when locating Gabor wavelet targets in noise, with fovea placement driven by a mutual information measure. The foveated approach is shown to have lower detection delay than a notional uniform resolution approach when using video that consumes equivalent bandwidth. The second experiments compare the accuracy of target position estimates from foveated and uniform resolution tracking algorithms. A technique is developed to select foveation parameters that minimize error in Kalman filter state estimates. Foveated tracking is shown to consistently outperform uniform resolution tracking on an abstract multiple target task when using video that consumes equivalent bandwidth. Performance is also compared to uniform resolution processing without bandwidth limitations. In both experiments, superior performance is achieved at a given bandwidth by foveated processing because limited resources are allocated intelligently to maximize operational performance. These findings indicate the potential for operational performance improvements over uniform resolution systems in both acquisition and tracking tasks.

Naturally-occurring sensory signal processing algorithms, such as those that inspired fuzzy-logic control, can be integrated into non-naturally-occurring high-performance technology, such as programmable logic devices, to realize novel bio-inspired designs. Research is underway concerning an investigation into using field programmable logic devices (FPLD's) to implement fuzzy logic sensory processing. A discussion is provided concerning the commonality between bio-inspired fuzzy logic algorithms and coarse coding that is prevalent in naturally-occurring sensory systems. Undergraduate design projects using fuzzy logic for an obstacle-avoidance robot has been accomplished at our institution and other places; numerous other successful fuzzy logic applications can be found as well. The long-term goal is to leverage such biomimetic algorithms for future applications. This paper outlines a design approach for implementing fuzzy-logic algorithms into reconfigurable computing devices. This paper is presented in an effort to connect with others who may be interested in collaboration as well as to establish a starting point for future research.

The Army requires passive uncooled IR sensors for use in numerous vehicle and weapons platforms, including driver vision enhancement (DVE), rifle sights, seeker munitions, and unattended ground sensors (UGSs) and unattended aerial vehicles (UAVs). Recent advances in bio-inspired/biomimetic nanomaterials synthesis, laser material processing, and sensor design and performance testing, offer the opportunity to create uncooled IR detector focal-plane arrays with improved sensitivity, low thermal mass, and fast response times, along with amenability to low-cost, rapid prototype manufacture. We are exploring the use of genotype-inspired, digitally-scripted laser direct-write techniques, in conjunction with the kinetically controlled catalytic process for the growth of nanostructured multimetallic perovskites, to develop a novel approach to the fabrication of precision patterned 2-D focal-plane arrays of pyroelectric perovskite-based materials. The bio-inspired growth of nanostructured, multimetallic perovskite thin-films corresponds to the use of kinetically controlled vapor diffusion for the slow growth of pure, highly crystalline 6-nm barium titanate (BaTiO₃) nanoparticles. This unique vapor-diffusion sol-gel route enables the formation of stoichiometric cubic-phase nanoparticles at room temperature and ambient pressure in the absence of a structure-directing template. Novel laser direct-write processing and synchronized electro-optic pulse modulation techniques have been utilized to induce site-selective, patterned phase transformation of microscale aggregates of the BaTiO₃ nanoparticles from the non-pyroelectric cubic polymorph to the pyroelectric tetragonal polymorph. This paper reports on our initial collaborative investigations, including comprehensive structural characterization (XRD, TEM, and SEM) of the BaTiO₃ nanoparticles and thin-films, along with preliminary laser-induced phase transformation results.