In this paper, we discuss techniques for extending the sensor planning capabilities of the machine vision planning system to include motion in a well-known environment. In a typical work cell, vision sensors are needed to monitor a task and provide feedback to motion control programs or to assess task completion or failure. In planning sensor locations and parameters for such a work-cell, all motion in the environment must be taken into account in order to avoid occlusions of desired features by moving objects and, in the case where the features to be monitored are being manipulated by the robot, to insure that the features are always within the camera's view. Several different sensor locations (or a single, movable sensor) may be required in order to view the features of interest during the course of the task. The goal is to minimize the number of sensors (or to minimize the motion of the single sensor) while guaranteeing a robust view at all times during the task, where a robust view is one which is unobstructed, in focus, and sufficiently magnified. In the past, sensor planning techniques have primarily focused on static environments. We present techniques which we have been exploring to include knowledge of motion in the sensor planning problem. Possible directions for future research are also presented.