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Visual SLAM","Table of Contents","Software","四 视觉SLAM从入门到进阶","视觉SLAM","Projects"],"sub_categories":["RGB-D","2.4 RGBD","Code"],"readme":"# Dense Visual Odometry and SLAM (dvo_slam)\n\n*NOTE: this is an alpha release APIs and parameters are going to change in near future. No support is provided at this point.*\n\nThese packages provide an implementation of the rigid body motion estimation of an RGB-D camera from consecutive images.\n\n *  **dvo_core**\n    \n    Core implementation of the motion estimation algorithm. \n    \n *  **dvo_ros**\n    \n    Integration of *dvo_core* with ROS.\n    \n *  **dvo_slam**\n    \n    Pose graph SLAM system based on *dvo_core* and integration with ROS.\n    \n *  **dvo_benchmark**\n    \n    Integration of *dvo_slam* with TUM RGB-D benchmark, see http://vision.in.tum.de/data/datasets/rgbd-dataset.\n    \n *  **sophus**\n    \n    ROS package wrapper for Hauke Strasdat's Sophus library, see https://github.com/strasdat/Sophus.\n    \n\n## Installation\n\nCheckout the branch for your ROS version into a folder in your `ROS_PACKAGE_PATH` and build the packages with `rosmake`.\n\n *  ROS Fuerte:\n    \n    ```bash\n    git clone -b fuerte git://github.com/tum-vision/dvo_slam.git\n    rosmake dvo_core dvo_ros dvo_slam dvo_benchmark\n    ```\n\n## Usage\n\nEstimating the camera trajectory from an RGB-D image stream:\n\n*TODO*\n\nFor visualization:\n\n *  Start RVIZ\n *  Set the *Target Frame* to `/world`\n *  Add an *Interactive Marker* display and set its *Update Topic* to `/dvo_vis/update`\n *  Add a *PointCloud2* display and set its *Topic* to `/dvo_vis/cloud`\n\nThe red camera shows the current camera position. The blue camera displays the initial camera position.\n\n## Publications\n\nThe following publications describe the approach:\n\n *   **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.\n *   **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\n *   **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.\n\n## License\n\nThe 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.\n\nThe package *sophus* is licensed under the MIT License, see http://opensource.org/licenses/MIT.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftum-vision%2Fdvo_slam","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftum-vision%2Fdvo_slam","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftum-vision%2Fdvo_slam/lists"}