OptSolution/dvo_slam

Dense Visual Odometry and SLAM

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.

Usage

You can use my docker image

docker pull optsolution/dvo_slam

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You need mount your data to docker container, you can download TUM data from here

Before the next step, you need get the assoc.txt file by run:

python2 associate.py rgb.txt depth.txt >> assoc.txt

Then, you can run

docker run -i -t -p 5900:5900 -v [data_path]:[docker_data_path] optsolution/dvo_slam

e.g.

docker run -i -t -p 5900:5900 -v /home/cwang/data/TUM/rgbd_dataset_freiburg1_360:/root/dataset optsolution/dvo_slam

option: input :5900 in vnc viewer to connect the desktop

---

you can run in the container:

cd [docker_data_path]
roslaunch dvo_benchmark benchmark.launch

e.g.

cd /root/dataset/
roslaunch dvo_benchmark benchmark.launch

Then the camera trajectory will be estimated from an RGB-D image stream.

After all, you will find the result in /root/fuerte_workspace/dvo_slam/dvo_benchmark/output

TODO

• Fix visualization

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.