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We introduce an innovative concept for 3D imaging that utilizes a structured light principle. While our design is specifically tailored for collaborative scenarios involving mobile transport robots, it is also applicable to similar contexts. Our system pairs a standard camera with a projector that employs a diffractive optical element (DOE) and a collimated laser beam to generate a coded light pattern. This allows a three-dimensional measurement of objects from a single camera shot. The main objective of the 3D-sensor is to facilitate the development of automatic, dynamic and adaptive logistics processes capable of managing diverse and unpredictable events. The key novelty of our proposed system for triangulation-based 3D reconstruction is the unique coding of the light pattern, ensuring robust and efficient 3D data generation, even within challenging environments such as industrial settings. Our pattern relies on a perfect submap, a matrix featuring pseudorandomly distributed dots, where each submatrix of a fixed size is distinct from the others. Based on the size of the working space and known geometrical parameters of the optical components, we establish vital design constraints like minimum pattern size, uniqueness window size, and minimum Hamming distance for the design of an optimal pattern. We empirically examine the impact of these pattern constraints on the quality of the 3D data and compare our proposed encoding with some single-shot patterns found in existing literature. Additionally, we provide detailed explanations on how we addressed several challenges during the fabrication of the DOE, which are crucial in determining the usability of the application. These challenges include reducing the 0th diffraction order, accommodating a large horizontal field of view, achieving high point density, and managing a large number of points. Lastly, we propose a real-time processing pipeline that transforms an image of the captured dot pattern into a high-resolution 3D point cloud using a computationally efficient pattern decoding methodology.
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