stereo_slam package from stereo_slam repostereo_slam |
|
Package Summary
Tags | No category tags. |
Version | 0.0.1 |
License | BSD |
Build type | CATKIN |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/srv/stereo_slam.git |
VCS Type | git |
VCS Version | indigo |
Last Updated | 2016-07-13 |
Dev Status | UNMAINTAINED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Pep Lluis Negre
Authors
- Pep Lluis Negre
Stereo SLAM
stereo_slam is a ROS node to execute Simultaneous Localization And Mapping (SLAM) using only one stereo camera. The algorithm was designed and tested for underwater robotics. This node is based on the G2O library for graph optimization and uses the power of libhaloc to find loop closures between graph nodes. It uses a keyframe to multi-keyframe loop closing mechanism, based on keypoint clustering, to improve the SLAM corrections on feature-poor environments.
You can see it in action here:
Specially designed for underwater scenarios:
Video: ORB-SLAM vs Stereo SLAM (underwater)
More videos…
Video: Stereo SLAM and 3D reconstruction and Video: Stereo SLAM at UIB outdoor pond
Installation (Ubuntu + ROS Indigo)
1) Install the dependencies
sudo apt-get install ros-<your ros distro>-libg2o
sudo apt-get install libceres-dev
You also need to setup a stereo visual odometer (e.g. viso2 or fovis).
3) Download the code, save it to your ROS workspace enviroment and compile.
roscd
git clone https://github.com/srv/stereo_slam.git
cd stereo_slam
rosmake
Parameters
-
odom_topic
- Visual odometry topic (type nav_msgs::Odometry). -
camera_topic
- The namespace of your stereo camera.
Other (hard-coded) parameters
-
include/constants.h
- Contains the set of node parameters. Default parameters should work.
Run the node
You can run the node using the following launch file (please, for a better performance scale your images if more than 960px width).
<launch>
<arg name="camera" default="/stereo"/>
<!-- Run the stereo image proc -->
<node ns="$(arg camera)" pkg="stereo_image_proc" type="stereo_image_proc" name="stereo_image_proc" />
<node pkg="viso2_ros" type="stereo_odometer" name="stereo_odometer">
<remap from="stereo" to="$(arg camera)"/>
<remap from="image" to="image_rect"/>
</node>
<node pkg="stereo_slam" type="localization" name="stereo_slam" output="screen">
<param name="odom_topic" value="/stereo_odometer/odometry"/>
<param name="camera_topic" value="$(arg camera)"/>
</node>
</launch>
Published Topics
-
/stereo_slam/odometry
- The vehicle pose (type nav_msgs::Odometry). -
/stereo_slam/graph_poses
- The updated graph poses (type stereo_slam::GraphPoses). -
/stereo_slam/keyframes
- Number of inserted keyframes (type std_msgs::String). -
/stereo_slam/keypoints_clustering
- Image containing the keypoint clusters (type sensor_msgs::Image). -
/stereo_slam/loop_closing_matchings
- Image of the loop closing correspondences. Correspondences are keyframe-to-multi-keyframe (type sensor_msgs::Image). -
/stereo_slam/loop_closing_queue
- Number of keyframes waiting on the loop closing queue. Please monitor this topic, to check the real-time performance: if this number grows indefinitely it means that your system is not able to process all the keyframes, then, scale your images. (type std_msgs::String). -
/stereo_slam/loop_closings
- Number of loop closings found (type std_msgs::String). -
/stereo_slam/pointcloud
- The pointcloud for every keyframe (type sensor_msgs::PointCloud2). -
/stereo_slam/tracking_overlap
- Image containing a representation of the traking overlap. Used to decide when to insert a new keyframe into the graph (type sensor_msgs::Image). -
/stereo_slam/camera_params
- The optimized (calibrated) camera parameters after every loop closure (type stereo_slam::CameraParams).
Saved data
The node stores some data into the stereo_slam directory during the execution:
-
haloc
- A folder containing all the files needed for the libhaloc library, which is responsible for loop closing detection. You do not need this folder at all. -
keyframes
- Stores the left stereo image for every keyframe (with the possibility of drawing the keypoint clustering over the image). -
loop_closures
- Stores all the images published in the topic/stereo_slam/loop_closing_matchings
. -
pointclouds
- Stores all the pointclouds published in the topic/stereo_slam/pointcloud
.
Online graph viewer
The node provides a python script to visualize the results of the stereo_slam during the execution: scripts/graph_viewer.py:
usage: graph_viewer.py [-h]
ground_truth_file visual_odometry_file
graph_vertices_file graph_edges_file
or (automatically detect the graph files):
roscd stereo_slam
./scripts/graph_viewer.py
The odometry file can be recorded directly from ros using:
rostopic echo -p /your_odometry_topic/odometry > odometry.txt
The ground truth file must have the same format than the odometry.
Post processing
The node provides a python script to evaluate the results of the stereo_slam once the execution finishes: scripts/slam_evaluation.py:
usage: slam_evaluation.py [-h]
ground_truth_file visual_odometry_file
graph_vertices_file graph_edges_file
This script perform a set of operations in order to evaluate the performance of the stereo_slam algorithm:
1) Align all the curves (ground truth, visual_odometry and graph vertices) to the same origin.
2) Compute the average translation error.
3) Plot the error vs trajectory distance.
Wiki Tutorials
Package Dependencies
System Dependencies
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged stereo_slam at Robotics Stack Exchange
stereo_slam package from stereo_slam repostereo_slam |
|
Package Summary
Tags | No category tags. |
Version | 0.0.1 |
License | BSD |
Build type | CATKIN |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/srv/stereo_slam.git |
VCS Type | git |
VCS Version | indigo |
Last Updated | 2016-07-13 |
Dev Status | UNMAINTAINED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Pep Lluis Negre
Authors
- Pep Lluis Negre
Stereo SLAM
stereo_slam is a ROS node to execute Simultaneous Localization And Mapping (SLAM) using only one stereo camera. The algorithm was designed and tested for underwater robotics. This node is based on the G2O library for graph optimization and uses the power of libhaloc to find loop closures between graph nodes. It uses a keyframe to multi-keyframe loop closing mechanism, based on keypoint clustering, to improve the SLAM corrections on feature-poor environments.
You can see it in action here:
Specially designed for underwater scenarios:
Video: ORB-SLAM vs Stereo SLAM (underwater)
More videos…
Video: Stereo SLAM and 3D reconstruction and Video: Stereo SLAM at UIB outdoor pond
Installation (Ubuntu + ROS Indigo)
1) Install the dependencies
sudo apt-get install ros-<your ros distro>-libg2o
sudo apt-get install libceres-dev
You also need to setup a stereo visual odometer (e.g. viso2 or fovis).
3) Download the code, save it to your ROS workspace enviroment and compile.
roscd
git clone https://github.com/srv/stereo_slam.git
cd stereo_slam
rosmake
Parameters
-
odom_topic
- Visual odometry topic (type nav_msgs::Odometry). -
camera_topic
- The namespace of your stereo camera.
Other (hard-coded) parameters
-
include/constants.h
- Contains the set of node parameters. Default parameters should work.
Run the node
You can run the node using the following launch file (please, for a better performance scale your images if more than 960px width).
<launch>
<arg name="camera" default="/stereo"/>
<!-- Run the stereo image proc -->
<node ns="$(arg camera)" pkg="stereo_image_proc" type="stereo_image_proc" name="stereo_image_proc" />
<node pkg="viso2_ros" type="stereo_odometer" name="stereo_odometer">
<remap from="stereo" to="$(arg camera)"/>
<remap from="image" to="image_rect"/>
</node>
<node pkg="stereo_slam" type="localization" name="stereo_slam" output="screen">
<param name="odom_topic" value="/stereo_odometer/odometry"/>
<param name="camera_topic" value="$(arg camera)"/>
</node>
</launch>
Published Topics
-
/stereo_slam/odometry
- The vehicle pose (type nav_msgs::Odometry). -
/stereo_slam/graph_poses
- The updated graph poses (type stereo_slam::GraphPoses). -
/stereo_slam/keyframes
- Number of inserted keyframes (type std_msgs::String). -
/stereo_slam/keypoints_clustering
- Image containing the keypoint clusters (type sensor_msgs::Image). -
/stereo_slam/loop_closing_matchings
- Image of the loop closing correspondences. Correspondences are keyframe-to-multi-keyframe (type sensor_msgs::Image). -
/stereo_slam/loop_closing_queue
- Number of keyframes waiting on the loop closing queue. Please monitor this topic, to check the real-time performance: if this number grows indefinitely it means that your system is not able to process all the keyframes, then, scale your images. (type std_msgs::String). -
/stereo_slam/loop_closings
- Number of loop closings found (type std_msgs::String). -
/stereo_slam/pointcloud
- The pointcloud for every keyframe (type sensor_msgs::PointCloud2). -
/stereo_slam/tracking_overlap
- Image containing a representation of the traking overlap. Used to decide when to insert a new keyframe into the graph (type sensor_msgs::Image). -
/stereo_slam/camera_params
- The optimized (calibrated) camera parameters after every loop closure (type stereo_slam::CameraParams).
Saved data
The node stores some data into the stereo_slam directory during the execution:
-
haloc
- A folder containing all the files needed for the libhaloc library, which is responsible for loop closing detection. You do not need this folder at all. -
keyframes
- Stores the left stereo image for every keyframe (with the possibility of drawing the keypoint clustering over the image). -
loop_closures
- Stores all the images published in the topic/stereo_slam/loop_closing_matchings
. -
pointclouds
- Stores all the pointclouds published in the topic/stereo_slam/pointcloud
.
Online graph viewer
The node provides a python script to visualize the results of the stereo_slam during the execution: scripts/graph_viewer.py:
usage: graph_viewer.py [-h]
ground_truth_file visual_odometry_file
graph_vertices_file graph_edges_file
or (automatically detect the graph files):
roscd stereo_slam
./scripts/graph_viewer.py
The odometry file can be recorded directly from ros using:
rostopic echo -p /your_odometry_topic/odometry > odometry.txt
The ground truth file must have the same format than the odometry.
Post processing
The node provides a python script to evaluate the results of the stereo_slam once the execution finishes: scripts/slam_evaluation.py:
usage: slam_evaluation.py [-h]
ground_truth_file visual_odometry_file
graph_vertices_file graph_edges_file
This script perform a set of operations in order to evaluate the performance of the stereo_slam algorithm:
1) Align all the curves (ground truth, visual_odometry and graph vertices) to the same origin.
2) Compute the average translation error.
3) Plot the error vs trajectory distance.