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Advancement in depth-sensing technology has allowed mobile robots to visualize the surrounding environment in 3D models. Regardless of the sensing technology (i.e. active, passive, or laser-based), a complete system that integrates recent depth data in previous 3D models in real-time is done by employing Simultaneous Localization And Mapping (SLAM) algorithms followed by a 3D reconstruction engine. Unfortunately, both the SLAM algorithm and the 3D reconstruction engine are usually executed on a single computing device, making the whole system exceptionally costly and heavy and restricting the robot's mobility. This paper proposes a decentralized, modular reconstruction system capable of employing various sensors to facilitate online 3D reconstruction from a resource-limited mobile robot.
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Rajput et al. (2020) studied this question.
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