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.