1. A system for automatically locating and identifying an object in an environment, the system comprising: at least one sensor to acquire sensor data representing at least a portion of the environment; at least one processor operably coupled to the at least one sensor; and at least one memory operably coupled to the at least one processor, the at least one memory storing instructions that, when executed by the at least one processor, cause the at least one processor to implement: a spatial attention module to produce a foveated representation of the object based at least in part on the sensor data, to track a position of the object within the environment based at least in part on the foveated representation, and to select another portion of the environment to be sensed by the at least one sensor based at least in part on the foveated representation of the object; and a semantics module to determine an identity of the object based at least in part on the foveated representation of the object, wherein the spatial attention module comprises a segmentation module to generate at least one contour representation of the object based at least in part on the sensor data, wherein the spatial attention module further comprises a figure/ground segregation module to determine at least one spatial shroud fitting a form of the object based at least in part on the at least one contour representation of the object, and wherein the sensor data comprises a plurality of images and the semantics module comprises: a view layer to group views of the object in the plurality of images based at least in part on the at least one spatial shroud; an object layer to map the views of the object to an object node associated with the object; and a name layer to classify the object based at least in part on the object node.