Randomized search strategies with imperfect sensors

In two previous papers we explored some of the systems aspects of applying large numbers of inexpensive robots to real world applications. The concept of coverage can help the user of such a system visualize its overall function and performance in mission-relevant terms, and thereby support necessary system command control functions. An important class of coverage applications are those that involve a search, in which a number of searching elements move about within a prescribed search area in order to find one or more target objects, which may be stationary or mobile. A simple analytical framework was employed in the previous work to demonstrate that the design of a cost-effective many-robot search system can depend sensitively on the interplay of sensor cost and performance levels with mission-specific functional and performance requirements. In the current paper we extend these results: we consider additional measures of effectiveness for area search systems to provide a broader basis for a tradeoff of coordinated versus random search models, and we explore how to deliberately achieve effectively randomized search strategies that provide uniform search coverage over a specified area.