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.
Core implementation of the motion estimation algorithm.
Integration of dvo_core with ROS.
Pose graph SLAM system based on dvo_core and integration with ROS.
Integration of dvo_slam with TUM RGB-D benchmark, see http://vision.in.tum.de/data/datasets/rgbd-dataset.
ROS package wrapper for Hauke Strasdat's Sophus library, see https://github.com/strasdat/Sophus.
Checkout the branch for your ROS version into a folder in your
ROS_PACKAGE_PATH and build the packages with
git clone -b fuerte git://github.com/tum-vision/dvo_slam.git rosmake dvo_core dvo_ros dvo_slam dvo_benchmark
Estimating the camera trajectory from an RGB-D image stream:
- Start RVIZ
- Set the Target Frame to
- Add an Interactive Marker display and set its Update Topic to
- Add a PointCloud2 display and set its Topic to
The red camera shows the current camera position. The blue camera displays the initial camera position.
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.
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.