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.
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dvo_core
Core implementation of the motion estimation algorithm.
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dvo_ros
Integration of dvo_core with ROS.
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dvo_slam
Pose graph SLAM system based on dvo_core and integration with ROS.
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dvo_benchmark
Integration of dvo_slam with TUM RGB-D benchmark, see http://vision.in.tum.de/data/datasets/rgbd-dataset.
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sophus
ROS package wrapper for Hauke Strasdat's Sophus library, see https://github.com/strasdat/Sophus.
You can use my docker image
docker pull paopaorobot/dvo_slam
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] paopaorobot/dvo_slam
e.g.
docker run -i -t -p 5900:5900 -v /home/cwang/data/TUM/rgbd_dataset_freiburg1_360:/root/dataset paopaorobot/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
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.