For any robot to effectively traverse its environment, it requires a map and its pose (location along with the orientation) within that map. Often, a map will not be available if the robot is presented with an unfamiliar environment. This scenario requires a robot to construct the map and localize itself in it to navigate. The problem of concurrently building the map and localizing a robot in that environment is defined as Simultaneous Localization and Mapping (SLAM). Many SLAM applications already exist for a single robot such as navigating the unmanned mines and exploring the sites with natural calamities. With the advent of swarming robots that must interact with each other, extensive research is being conducted for the extension of the SLAM problem to multiple robots known as Multi-Robot SLAM (MR-SLAM). In the MR-SLAM environment, the efficiency is improved, and time constraints are reduced, but its implementation is restricted due to constraints such as communication bandwidth, memory requirements and problems faced during map merging and coordinate transformation.This research introduces a way to simulate a multi-robot environment in the Gazebo simulator by creating a launch file with attributes and specifications for many robots. A generalized MATLAB script is written in order to populate a Gazebo world with user defined number of TurtleBots along with their communication topics. This system is further tested with an implementation of Sparse Extended Information Filter (SEIF) with known correspondences for such multi-robot environment.