Authors: Shreyas Athreya Venkatesh, Nitin Vinod. Advised by Dr Lukasz Ziarek (all associated with the State University of New York at Buffalo)
ORBSLAM3 suffers from memory leaks owing to the lack of a deletion scheme for keyframes and map points. This work is an attempt to alleviate this issue by providing a custom reference counting scheme. The scheme successfully deletes most keyframes and mappoints without segmentation faults. This was tested on the sequences in the EuRoC dataset. This work further explores reference counting using "compare and swap".
We recommend the branch called "release_branch" as this should have statisitics that are printed while the code executes.
Authors: Carlos Campos, Richard Elvira, Juan J. Gómez Rodríguez, José M. M. Montiel, Juan D. Tardos.
The Changelog describes the features of each version.
ORB-SLAM3 is the first real-time SLAM library able to perform Visual, Visual-Inertial and Multi-Map SLAM with monocular, stereo and RGB-D cameras, using pin-hole and fisheye lens models. In all sensor configurations, ORB-SLAM3 is as robust as the best systems available in the literature, and significantly more accurate.
We provide examples to run ORB-SLAM3 in the EuRoC dataset using stereo or monocular, with or without IMU, and in the TUM-VI dataset using fisheye stereo or monocular, with or without IMU. Videos of some example executions can be found at ORB-SLAM3 channel.
This software is based on ORB-SLAM2 developed by Raul Mur-Artal, Juan D. Tardos, J. M. M. Montiel and Dorian Galvez-Lopez (DBoW2).