In this article we describe the use of Artificial Neural Networks (ANN) with synaptic time delays between the nodes as a means to increase the capabilities of the usual control modules used in behavior based robotics. This inclusion allows the controllers to manage explicit temporal information in different levels. In the sensing level, it permits the use of virtual sensors that improve the precision of the information provided by sensors through a temporal correlation of their values. In the actuation level we use the network with an infra-sensorized robot in a problem that requires active sensing, where the control and actuation mechanisms are coordinated in order to obtain a better sensorial image of the environment by means of a spatio-temporal representation of a perception sequence. The decision of the appropriate delays is automated through learning and evolution.