This paper addresses research into the application of cooperative visual SLAM for utilization within UAVs. The research utilized a synthetic approach to examine 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 demonstrated error and robustness as a comparison between the cooperative UAV enhanced filtering scheme versus the single UAV implementation without the proposed fusing enhancements. To conclude, the relative merits of the methodology proposed by this research are also discussed.