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Although there has been much effort to improve localization in both wireless sensor networks and robotics, few have combined the localization techniques of both worlds so that they can cooperatively and mutually benefit each other. Therefore, we seek to design a localization algorithm based on statistical framework that can combine the localization methodology of both autonomous robotics and sensor networks, such that a two-way cooperative localization can be accomplished instead of the usual one-way only cooperation. To achieve this, we need to integrate three important research areas: wireless sensor networks, robotics and statistical filtering. In this paper, we will present the key elements of our approach and simulation results to validate the scheme. We prove that mobile robots and static sensor nodes can cooperatively help each other in their localization by first localizing the mobile robots with the static nodes, after which the mobile robots will provide feedback to the static nodes so that the static nodes can then refine their own location estimates.