lizhaodong / dvo_slam

Dense Visual Odometry and SLAM RGB-D相机稠密视觉里程计

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.

这些包提供了来自连续图像的rgb摄像机刚体运动估计的实现。

• dvo_core

  运动估计算法的核心实现。 Core implementation of the motion estimation algorithm.

• dvo_ros

  dvo_core与ROS的集成 Integration of dvo_core with ROS.

• dvo_slam

  基于 dvo_core的姿态图SLAM系统与ROS集成 Pose graph SLAM system based on dvo_core and integration with ROS.

• dvo_benchmark

集成 dvo_slam 和转向 rgb d 基准 Integration of dvo_slam with TUM RGB-D benchmark, see http://vision.in.tum.de/data/datasets/rgbd-dataset.

• sophus

  strasdat库 Hauke Sophus的ROS包包装器 ROS package wrapper for Hauke Strasdat's Sophus library, see https://github.com/strasdat/Sophus.

安装 Installation

Checkout the branch for your ROS version into a folder in your ROS_PACKAGE_PATH and build the packages with rosmake.

在 ROS_PACKAGE_PATH 中将你的ROS版本的分支签入到中，并使用 rosmake 构建包。

• ROS Fuerte:

  git clone -b fuerte git://github.com/tum-vision/dvo_slam.git
  rosmake dvo_core dvo_ros dvo_slam dvo_benchmark

Usage

Estimating the camera trajectory from an RGB-D image stream:

TODO

For visualization:

• Start RVIZ
• Set the Target Frame to /world
• Add an Interactive Marker display and set its Update Topic to /dvo_vis/update
• Add a PointCloud2 display and set its Topic to /dvo_vis/cloud

The red camera shows the current camera position. The blue camera displays the initial camera position.

用法
从rgb图像流估算相机轨迹：

为了可视化：

启动 RVIZ
将目标帧设置为 /world
添加交互式标记显示并将它的更新主题 /dvo_vis/update
添加 PointCloud2 显示并将它的主题 /dvo_vis/cloud
红色摄影机显示当前相机位置。 蓝色摄影机显示初始相机位置。

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.