We demonstrate a multiple micro aerial vehicle (MAV) system capable of supporting autonomous exploration and navigation in unknown environments using only a sensor commonly found in low-cost, commercially available MAVs—a front-facing monocular camera. We adapt a popular open source monocular SLAM library, ORB-SLAM, to support multiple inputs and present a system capable of effective cross-map alignment that can be theoretically generalized for use with other monocular SLAM libraries. Using our system, a single central ground control station is capable of supporting up to five MAVs simultaneously without a loss in mapping quality as compared to single-MAV ORB-SLAM. We conduct testing using both benchmark datasets and real-world trials to demonstrate the capability and real-time effectiveness.
Computer Science (MS)
Department, Program, or Center
Computer Science (GCCIS)
Hollenbach, Andrew, "Low-Cost Multiple-MAV SLAM Using Open Source Software" (2018). Thesis. Rochester Institute of Technology. Accessed from
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