Displaying 1 to 6 from 6 results

orb_slam_2_ros - A ROS implementation of ORB_SLAM2

  •    C++

ORB-SLAM2 Authors: Raul Mur-Artal, Juan D. Tardos, J. M. M. Montiel and Dorian Galvez-Lopez (DBoW2). The original implementation can be found here. This is the ROS implementation of the ORB-SLAM2 real-time SLAM library for Monocular, Stereo and RGB-D cameras that computes the camera trajectory and a sparse 3D reconstruction (in the stereo and RGB-D case with true scale). It is able to detect loops and relocalize the camera in real time. This implementation removes the Pangolin dependency, and the original viewer. All data I/O is handled via ROS topics. For visualization you can use RViz. This repository is maintained by Lennart Haller on behalf of appliedAI.

ros2-ORB_SLAM2 - ROS2 node wrapping the ORB_SLAM2 library

  •    C++

If you want to integrate ORB_SLAM2 inside your ROS2 system, consider trying this fork of ORB_SLAM2 library which drops Pangolin dependency and streams all SLAM data through ROS2 topics. Note: The vision_opencv package requires OpenCV3. Make sure to build ORB_SLAM2 with the same OpenCV version otherwise strange run errors could appear.




se2clam - SE(2)-Constrained Localization and Mapping by Fusing Odometry and Vision (IEEE Transactions on Cybernetics 2019)

  •    C++

Download DatasetRoom.zip, and extract it. In a terminal, cd into DatasetRoom/. We prepare two packages of odometry measurement data, one is more accurate (odo_raw_accu.txt), the other less accurate (odo_raw_roug.txt). To use either one of them, copy it to odo_raw.txt in DatasetRoom/.

mola - A Modular Optimization framework for Localization and mApping (MOLA)

  •    Shell

A Modular Optimization framework for Localization and mApping (MOLA). This repository holds the MOLA git superproject. Refer to the official documentation for build instructions, demos, API reference, etc.