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This paper considers a class of deploy and search strategies for multi-robotsystems and evaluates their performance. The application framework used is asystem of autonomous mobile robots equipped with required sensors andcommunication equipment deployed in a search space to gather information. Thelack of information about the search space is modeled as an uncertainty densitydistribution over the search space. A {\em combined deploy and search} (CDS)strategy has been formulated as a modification to {\em sequential deploy andsearch} (SDS) strategy presented in our previous work. The optimal deploymentstrategy using Voronoi partition forms the basis for these two searchstrategies. The strategies are analyzed in presence of constraints on robotspeed and limit on sensor range for convergence of trajectories withcorresponding control laws responsible for the motion of robots. SDS and CDSstrategies are compared with standard greedy and random search strategies onthe basis of time taken to achieve reduction in the uncertainty density below adesired level. The simulation experiments reveal several important issuesrelated to the dependence of the relative performances of the strategies onparameters such as number of robots, speed of robots, and their sensor rangelimits.

Performance of a Class of Multi-Robot Deploy and Search Strategies based on Centroidal Voronoi Configurations