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We introduce DROID-SLAM, a new deep learning based SLAM system. DROID-SLAMconsists of recurrent iterative updates of camera pose and pixelwise depththrough a Dense Bundle Adjustment layer. DROID-SLAM is accurate, achievinglarge improvements over prior work, and robust, suffering from substantiallyfewer catastrophic failures. Despite training on monocular video, it canleverage stereo or RGB-D video to achieve improved performance at test time.The URL to our open source code is https://github.com/princeton-vl/DROID-SLAM.

DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D Cameras