https://github.com/tum-vision/dvo_slam

Dense Visual Odometry and SLAM
https://github.com/tum-vision/dvo_slam

Last synced: 6 days ago
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Dense Visual Odometry and SLAM

• Host: GitHub
• URL: https://github.com/tum-vision/dvo_slam
• Owner: tum-vision
• Created: 2013-08-14T13:55:52.000Z (about 11 years ago)
• Default Branch: fuerte
• Last Pushed: 2016-09-21T19:57:35.000Z (about 8 years ago)
• Last Synced: 2024-08-02T07:06:57.351Z (3 months ago)
• Language: C++
• Size: 266 KB
• Stars: 632
• Watchers: 73
• Forks: 305
• Open Issues: 53
• Metadata Files:
  • Readme: README.md

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• Awesome-SLAM - Dense Visual Odometry and SLAM

README

        
# Dense Visual Odometry and SLAM (dvo_slam)

*NOTE: this is an alpha release APIs and parameters are going to change in near future. No support is provided at this point.*

These packages provide an implementation of the rigid body motion estimation of an RGB-D camera from consecutive images.

 *  **dvo_core**

    

    Core implementation of the motion estimation algorithm. 

    

 *  **dvo_ros**

    

    Integration of *dvo_core* with ROS.

    

 *  **dvo_slam**

    

    Pose graph SLAM system based on *dvo_core* and integration with ROS.

    

 *  **dvo_benchmark**

    

    Integration of *dvo_slam* with TUM RGB-D benchmark, see http://vision.in.tum.de/data/datasets/rgbd-dataset.

    

 *  **sophus**

    

    ROS package wrapper for Hauke Strasdat's Sophus library, see https://github.com/strasdat/Sophus.

    

## Installation

Checkout the branch for your ROS version into a folder in your `ROS_PACKAGE_PATH` and build the packages with `rosmake`.

 *  ROS Fuerte:

    

    ```bash

    git clone -b fuerte git://github.com/tum-vision/dvo_slam.git

    rosmake dvo_core dvo_ros dvo_slam dvo_benchmark

    ```

## Usage

Estimating the camera trajectory from an RGB-D image stream:

*TODO*

For visualization:

 *  Start RVIZ

 *  Set the *Target Frame* to `/world`

 *  Add an *Interactive Marker* display and set its *Update Topic* to `/dvo_vis/update`

 *  Add a *PointCloud2* display and set its *Topic* to `/dvo_vis/cloud`

The red camera shows the current camera position. The blue camera displays the initial camera position.

## Publications

The following publications describe the approach:

 *   **Dense Visual SLAM for RGB-D Cameras** (C. Kerl, J. Sturm, D. Cremers), In Proc. of the Int. Conf. on Intelligent Robot Systems (IROS), 2013.

 *   **Robust Odometry Estimation for RGB-D Cameras** (C. Kerl, J. Sturm, D. Cremers), In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), 2013

 *   **Real-Time Visual Odometry from Dense RGB-D Images** (F. Steinbruecker, J. Sturm, D. Cremers), In Workshop on Live Dense Reconstruction with Moving Cameras at the Intl. Conf. on Computer Vision (ICCV), 2011.

## License

The packages *dvo_core*, *dvo_ros*, *dvo_slam*, and *dvo_benchmark* are licensed under the GNU General Public License Version 3 (GPLv3), see http://www.gnu.org/licenses/gpl.html.

The package *sophus* is licensed under the MIT License, see http://opensource.org/licenses/MIT.