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Only released in EOL distros:  

vslam: bpcg | frame_common | g2o | posest | sba | sparselib | vocabulary_tree | vslam_system

Package Summary

Visual SLAM with sparse bundle adjustment

WARNING

vslam is experimental research code. It is not actively being supported, and should be used at your own risk, but patches are welcome.

If you would like a robust method of localization and mapping with a stereo camera or kinect, use the 2D slam_gmapping stack. See the pointcloud_to_laserscan package from the turtlebot stack and the SLAM Gmapping with Kinect Tutorial for the turtlebot.

Installing vslam

There are two ways to install vslam. If you want to use vslam without modifying it, it is available as a debian package under diamondback or unstable:

$ sudo apt-get install ros-diamondback-vslam

If you want to modify the source code, you can install it from source as an overlay to diamondback or unstable. Make a new directory VSLAMDIR under the current directory, and download the source:

# Download vslam sources
$ svn co https://code.ros.org/svn/ros-pkg/stacks/vslam/trunk VSLAMDIR

# Set up environment
$ . VSLAMDIR/setup.sh

# Build
$ rosmake --rosdep-install vslam_system

This checks out the new packages under VSLAMDIR; you can of course have VSLAMDIR anywhere in your filesystem tree. The setup.sh file puts VSLAMDIR into $ROS_PACKAGE_PATH (if you are unclear on what this means, refer to the Stack Installation Tutorial ) or add path as

export ROS_PACKAGE_PATH=/path_to_slam_directory/VSLAMDIR:$ROS_PACKAGE_PATH

Documentation

If you would like to use visual SLAM within ROS, on images coming in on a ROS topic, you will want to use the vslam_system see the Running VSLAM on Stereo Data tutorial.

To use Sparse Bundle Adjustment, the underlying large-scale camera pose and point position optimizer library, start with the Introduction to SBA tutorial.

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2019-11-30 13:24