Sensor networks have been used to predict the direction and intensity of tsunamis, and forest fires, the density of marine colonies, air pollutants, and other spatially, temporally distributed environmental fields. Our work developed systematic methods for optimally estimating environmental parametric fields using multiple mobile sensors, while also simultaneously addressing the issues of localization and deadlock that arise as a consequence of increased autonomy, mobility and actuation in the sensor network. This work has been summarized in a book published by IET.