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The emergence of new risks to homeland security requires a greater reliance on innovative remote sensing and monitoring systems deployed on Unmanned Vehicles (UxVs) for protecting borders and critical infrastructure. Robust autonomous control technologies that can reliably coordinate these sensors and platforms are needed. We describe a class of algorithms based on digital pheromones that enables robust, complex, intelligent behavior. These algorithms have been implemented on a variety of UxVs and sensor platforms and demonstrated in surveillance and infrastructure protection applications. The algorithms autonomously adapt to a rapidly changing environment as well as failures or changes in the composition of the sensor assets. They can support mixed manned and unmanned teaming environments. An Operator System Interface (OSI) enables a single operator to monitor and manage the system. We describe the results from various tests and the challenges faced in implementing these algorithms on actual hardware.

Bond inspection is one of the most critical NDE tasks addressing the aging aircraft problem. This paper is aimed at reviewing and furthering the use of ultrasonic guided waves for the inspection of bonded components, particularly lap joints between thin plates such as those found in aircraft skins. The transfer matrix theory of wave propagation in multilayered components is used to predict the sensitivity of the wave dispersion behavior to the bond state. The experimental study includes the use of non-contact air-coupled transducers to excite and detect guided waves in a pitch-catch arrangement. It is shown that by monitoring the ultrasound amplitude leaking through the bondline it is possible to detect disbonds as well as low-strength bonds. A photoelastic study confirms this result. It is reaffirmed that those modes with predominant shear-type deformations at the bondline are the most sensitive to the bond state.

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