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Twilight SLAM is unique framework augmenting the SLAM navigation frameworks with low-light image enhancement modules for navigating in dusky or extremely low-light or any illumination rendered featureless environments.

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DhyeyR-007/Twilight-SLAM-Navigating-Low-Light-Environments

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TwilightSLAM project created at the University of Michigan Ann Arbor with the objective of investigating state-of-the-art technologies for Simultaneous Localization and Mapping (SLAM) tasks in low-light or twilight-like environments.

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As this project operates in correspondence with various libraries and core algorithmic frameworks (keeping in mind quick real-time implementation ability), system requirements vary for each repository. Each image enhancment module and SLAM framework has a detailed readme associated in the corresponding directory for smooth implementation of our combined Twilight SLAM architectures.

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For a brief overview of our project, we recommend watching our presentation on YouTube. For a more indepth look at our project and the results, you can find the PDF of our report here or on arxiv

Each type of SLAM implementation has a detailed readme associated in the corresponding directory for smooth implementation of our combined Twilight SLAM architectures. Go Blue!

P.S. this is a combined and updated implementation with recent python and C++ library changes to our original project for concise viewing and version-based bug free experience

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Twilight SLAM is unique framework augmenting the SLAM navigation frameworks with low-light image enhancement modules for navigating in dusky or extremely low-light or any illumination rendered featureless environments.

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