In particular, for a practical mobile robot team to perform such a task as that of carrying out a search and rescue mission in a disaster area, the network connectivity and localization have to be guaranteed even in an environment where the network infrastructure is destroyed or a Global Positioning System is unavailable. This paper proposes the new collective intelligence network management architecture of multiple mobile robots supporting seamless network connectivity and cooperative localization. The proposed architecture includes a resource manager that makes the robots move around and not disconnect from the network link by considering the strength of the network signal and link quality. The location manager in the architecture supports localizing robots seamlessly by finding the relative locations of the robots as they move from a global outdoor environment to a local indoor position. The proposed schemes assuring network connectivity and localization were validated through numerical simulations and applied to a search and rescue robot team.Keywords: Network connectivity and localization, seamless routing, cooperative localization, global positioning system, resource manager, location manager, CINeMA. Manuscript received Aug. 10, 2014; revised Dec. 11, 2014; accepted Dec. 26, 2014
I. IntroductionMultiple cooperative mobile robots performing search and rescue missions in disaster areas always require communication links to the human operator located at a remote station. However, the network infrastructure constructing the communication link is often destroyed in disaster areas; thus, a multi-hop mesh network connecting all robots and the operator station is needed for maintaining the link connectivity. In a multi-hop mesh network where the link environment is poor, the network configuration and routing of mobile robots are very important issues to guarantee the quality of service (QoS) of the communication link.Addressing these issues, J. Fink and others [1]-[2] proposed a k-connectivity method and resolved the end-to-end network connectivity problem using a probabilistic approach. In the DARPA LANdroids project [3], a self-configuring network scheme was developed, where the global network connectivity is maintained even in the case of a local connection failure. L. Sabattini and others [4]; S. Zickler and M. Veloso [5]; M.M. Zavlanos and others [6]; and N. Bezzo and others [7] analyzed the graph theoretical connectivity in mobile robot networks and developed optimization-based connectivity control methods. However, most previous approaches assumed that the network was connected within a fixed range of communication and that it relied on direct line-of-sight signals. Moreover, they used only the distance data between robots, which may not reflect the network connection information reasonably. In indoor or dynamic environments, a multi-path problem typically occurs; thus, the range information may become irregular. Therefore,