The research work on the application of cooperative visual SLAM for utilization within UAVs is addressed in this paper. This experimental study utilized a synthetic approach to fulfill a cooperative data fusing strategy for multiple UAVs equipped with stereo vision camera systems, where the collaborative estimation was implemented with an information filter and covariance intersection technique to investigate potential improvements in robustness to noise and accuracy of location determination and mapping processes, when compared to a single UAV employing vSLAM alone. The achieved performance enhancement is further discussed in terms of the relative errors as a comparison between the cooperative enhanced filtering schemes versus the single UAV implementation following the conclusion on relative merits of the methodology proposed here at the end.