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Creators/Authors contains: "Xanthidis, Marios"

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  1. In this paper we present a complete framework for Underwater SLAM utilizing a single inexpensive sensor. Over the recent years, imaging technology of action cameras is producing stunning results even under the challenging conditions of the underwater domain. The GoPro 9 camera provides high definition video in synchronization with an Inertial Measurement Unit (IMU) data stream encoded in a single mp4 file. The visual inertial SLAM framework is augmented to adjust the map after each loop closure. Data collected at an artificial wreck of the coast of South Carolina and in caverns and caves in Florida demonstrate the robustness of the proposed approach in a variety of conditions. 
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  2. This paper discusses a novel approach for the exploration of an underwater structure. A team of robots splits into two roles: certain robots approach the structure collecting detailed information (proximal observers) while the rest (distal observers) keep a distance providing an overview of the mission and assist in the localization of the proximal observers via a Cooperative Localization framework. Proximal observers utilize a novel robust switching model-based/visual-inertial odometry to overcome vision-based localization failures. Exploration strategies for the proximal and the distal observer are discussed. 
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  3. Visual monitoring operations underwater require both observing in close-proximity the objects of interest, and tracking the few feature-rich areas necessary for state estimation. This paper introduces the first navigation framework, called AquaVis, that produces on-line visibility-aware motion plans that enable Autonomous Underwater Vehicles (AUVs), to track multiple visual objectives with an arbitrary camera configuration in real-time. Using the proposed pipeline, AUVs can efficiently move in 3D, reach their goals while avoiding obstacles safely, and maximizing the visibility of multiple objectives along the path within a specified proximity. The method is sufficiently fast to be executed in real-time and is suitable for single or multiple camera configurations. Experimental results show the significant improvement on tracking multiple automatically-extracted points of interest, with low computational overhead and fast re-planning times. 
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