This paper considers the challenges to mobile wireless robots (WRs) in disaster environments: the unknown environment; the complexity of the environment, namely obstacles in the environment; and the limited capability and number of robots. The goals are to maintain WR communication, maximize coverage of task locations (known ones anyway), and maximize coverage of the environment.

The proposed “strategy enables WRs with limited moving, sensing, and communication capabilities to collect ... information about the tasks.” Further, it enables a WR “with only a local view ... to find suitable deployment locations” that cover the tasks and maintain the communication network.

The aim: a maximum number of tasks and locations should be within the sensing range of WRs while maintaining communication between WRs. For each WR, the procedure uses a search process followed by path choice. The search process creates the next location for a WR using the mean shift location algorithm, which uses the average value of task locations to maximize the number of covered tasks in the area.

A* is used to find a path to the new location. The procedure then checks that WR has the energy to reach the new location; if so, it moves there. The deployment portion of the process positions a WR so that it and a previously uncovered task are on the borders of the communication network.

The authors show that a deployment location can always be found and give an algorithm for doing so. The complexity of the algorithms used in the system is given. Three experiments are described, and graphs showing the effects of increasing the number of WRs are given. In future work, the authors intend to consider dynamically changing environments.