Volume-DROID is a novel SLAM architecture created by combining the recent works: DROID-SLAM and NeuralBKI. Volume-DROID takes camera images (monocular or stereo) or frames from video as input and outputs online, 3D semantic mapping of the environment via combination of DROID-SLAM, point cloud registration, off-the-shelf semantic segmentation and ConvBKI. The novelty of our method lies in the fusion of DROID-SLAM and ConvBKI by the introduction of point cloud generation from RGB-Depth frames and optimized camera poses. By having only camera images or a stereo video as input, we achieved functional real-time online 3D semantic mapping.

All of our code is original, adapted from the NeuralBKI codebase, or adapted from the DROID-SLAM codebase.

NeuralBKI code adapted from: https://github.com/UMich-CURLY/NeuralBKI DROID-SLAM code adapted from: https://github.com/princeton-vl/DROID-SLAM