Dense Visual Odometry (dvo)

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_benchmark

  Integration of dvo_core 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 paopaorobot/dvo

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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 -e RESOLUTION=[width]x[hight] -v [data_path]:[docker_data_path] paopaorobot/dvo

e.g.

docker run -i -t -p 5900:5900 -e RESOLUTION=1920x1080 -v /home/cwang/data/TUM/rgbd_dataset_freiburg1_360:/root/dataset paopaorobot/dvo

and input :5900 in vnc viewer to connect the desktop

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you can run in the desktop:

roslaunch dvo_benchmark benchmark.launch dataset:=[docker_data_path]

e.g.

roslaunch dvo_benchmark benchmark.launch dataset:=/root/dataset/

Maybe you cannot see anything now, the key r need to be pressed. Now you can see the groudtruth. If you want to estimation the trajectory, the key p need to be pressed. Now you can see trajecoties in the window. After all, you will find the result in /root/fuerte_workspace/dvo/dvo_benchmark/output

Publications

The following publications describe the approach:

• 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, 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.