cam_map_localization

cam_map_localization is a ros-package using a predefined map of fiducial markers to localize the camera with respect to a marker set as origin.

Prerequisites

• Generate the map of the markers using Ref-I: Mapping and Localization from Planar Markers. Basically, it is a file.yml containing all detected markers in the scene and their position. Example:

%YAML:1.0
---
aruco_bc_dict: TAG36h11
aruco_bc_nmarkers: 25
aruco_bc_mInfoType: 1
aruco_bc_markers:
   - { id:0, corners:[ [ 1.0879868268966675e+00, -2.2400319576263428e-01,
       5.3463661670684814e-01 ], [ 1.0820814371109009e+00,
       -1.0438479483127594e-01, 4.3158048391342163e-01 ], [
       1.0862079858779907e+00, -2.0736083388328552e-01,
       3.1181859970092773e-01 ], [ 1.0921133756637573e+00,
       -3.2697921991348267e-01, 4.1487473249435425e-01 ] ] }
   - { id:2, corners:[  
   .
   .
   .

Then copy the generated file in /config folder in cam_map_localization

• Calibration:

You need to calibration the camera and copy the generated file in /config folder in cam_map_localization

• Install Aruco 3:

ArUco: a minimal library for Augmented Reality applications based on OpenCV

Launch the package

roslaunch cam_map_localization camera_marker_detection.launch

Once a marker of the map is detected, you'll get the pose of the camera published in the topic /poseStampedDsr and you can visulize it in Rviz

See also the point cloud generated by Ref-I in Rviz

rosrun pcl_ros pcd_to_pointcloud markerset.pcd 0.158 _frame_id:=/map

References

I. Marker Mapper paper "Mapping and localization from planar markers" RafaelMuñoz-Salinas, Manuel J.Marín-Jimenez, Enrique Yeguas-Bolivar, R.Medina-Carnicer, , Pattern Recognition, To appear. https://www.sciencedirect.com/science/article/pii/S0031320317303151 [Read PDF]

II. Main ArUco paper: "Automatic generation and detection of highly reliable fiducial markers under occlusion" http://www.sciencedirect.com/science/article/pii/S0031320314000235 [DOWNLOAD PDF] [DOWNLOAD Bibtex]

III. Generation of marker dictionaries: "Generation of fiducial marker dictionaries using mixed integer linear programming" http://www.sciencedirect.com/science/article/pii/S0031320315003544 [DOWNLOAD PDF] [DOWNLOAD Bibtex]