Recent research in active vision has show that creating a visual system for a robot interacting with an unstructured, dynamic world differs vastly from interpreting a static image. On one hand, the constraints of real-time performance force optimizations such as a focus of attention and spatially variant sensing. On the other hand, the availability of a large number of views, whose acquisition is controlled by the robot, has proven to simplify problems enormously. In addition, the processing necessary to permit intelligent behavior has been found to be easier to achieve than the difficult goal of reconstruction and full interpretation of a science form a single image. This research explores two open problems suggested by ongoing research in active vision. One problem is the study the control of a spatially variant (foveal) sensor using the low- resolution formation available in the periphery. In particular, this research will examine the use of color information, which has been shown to be well preserved under low resolution. The other problem is the integration of set of visual modules, each capable of sustaining a particular task, with a suitable robot architecture sos that the resulting system is capable of timely, flexible interaction with a dynamic world. //