Rishikesh-Jadhav/3D-Indoor-Mapping-and-Object-Segmentation
This repository showcases our project, presenting an innovative approach to 3D Indoor Mapping and Object Segmentation. With a primary focus on robot navigation in complex environments, we introduce a methodology that uses RGB images for mapping and object segmentation by integrating SimpleRecon and Point-Voxel CNN for efficient scene reconstruction
This project helps robots understand their surroundings by creating detailed 3D maps and identifying objects within indoor spaces. It takes standard camera images (RGB photos) as input and outputs a segmented 3D map, showing where walls, furniture, and other items are. This is used by robotics engineers and researchers developing autonomous navigation systems for robots.
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Use this if you need to equip an autonomous robot with the ability to build a 3D map of an indoor environment and segment specific objects from standard camera images for navigation.
Not ideal if you require real-time, high-precision mapping and object segmentation in extremely complex or rapidly changing environments without dedicated hardware.
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Jan 08, 2024
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