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Monocular Vision based Autonomous Navigation for a Cost-Effective Open-Source MAVs in GPS-denied Environments

In this paper, we present monocular vision guided autonomous navigation system for Micro Aerial Vehicles (MAVs) in GPS-denied environments. The major problem of a monocular system is that the depth scale of the scene can not be determined without prior knowledge or other sensors. To address this problem we solve a cost function, which consists of a drift-free altitude measurement together with up-to-scaled position estimation from a visual sensor. We also evaluate the proposed system in terms of: accuracy of scale estimator, controller performance and accuracy of state estimation by comparing with motion capture ground truthed data. All resources including source code, tutorial documentation and system models are available online4.