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In recent, unmanned or human-robot collaborative systems are spreading in security applications in order to protect humans against sudden attack. Especially, the automated security system has to accomplish its mission even when there are limitations of its sensors in view of range or reliability. For this dependable operation, it is better to build up a security system using collective multi-robots than a single robot. So, we suggest a method how to organize collective robot behaviors for a self-localization algorithm that allows a recursive state estimation process to be collective in a multi-robot coalition team that is guaranteed connected. A leader robot in our method obtains a temporary estimate from at the current time step using information from other robots (follower-robots) and checks out whether it's followers needs to be localized. When the leader robot decides to localize a follower robot, it recovers the centralized-equivalent estimate with the help of its followers near to the follower robot. A practical implementation is finally provided for five robots to emphasize the effectiveness of the proposed collective approach to multi-robot localization problem. Moreover, we implement our robot behavior controller in OPRoS in order to enhance robot behavior SW's portability.