apriltaglocal_deploy

The goal of this project is to quickly build an accurate (calibration-free) localization system in indoor medium & large-scale scenarios.

In the project, we define the 0th Tag as the base tag for each Tag family. The output pose is related to the base tag. Thus, we use the method of common view to construct a series of April tag pose associations. After that, we will use the available tag in each frame to calculate the global camera pose and finish the localization task.

Frame work

The whole system consists of two parts: the Tag Generator module & the Localization module.

• The Tag Generator module will get tag information (Tag Family, Tag Size / Tag print PPI, Extend Dot size/position) from the YAML file and generate a Tag image with Extend dot.

• The localization module will get information (Tag info, Camera Intrinsic parameter/Distortion coefficient, Tag pre-calibration pose) from the YAML file and do the localization task. Finally, the output should be the camera pose related to the base tag.

Environment

Ros Noetic

Dependency Required

• AprilTag
• Yaml-cpp
• Glog
• Ceres
• Opencv4
• Eigen3

Install with apt-get

sudo apt install -y libyaml-cpp-dev libgoogle-glog-dev libeigen3-dev libceres-dev
sudo apt install -y libopencv-dev git cmake
mkdir 3rdparty && cd 3rdparty
git clone https://github.com/AprilRobotics/apriltag && cd apriltag
cmake -B build -DCMAKE_BUILD_TYPE=Release
sudo cmake --build build --target install

Catkin build instruction

cd ${catkin_ws}/src
git clone https://github.com/sjtuyuxuan/ExtendAprilTagLocal
cd .. && catkin_make

Yaml Definition

Name	Discription	Module
TagFamily	The TagFamily used by both localization module and generator	localization &  generator
ImagePath	The raw tag image path	generator
ImageCount	The raw tag input image path	generator
GenTags	The tag id used by tag generator	generator
GenPath	The extend tag output image path	generator
Tag ID as key	File : The raw tag input image name Size : The size of tag edge (mm) Canvas : The size of canvas (mm) [W, H] Extand_Dot : The position and size of extend dot (mm) [X, Y, R] Pixpermm : PPI for image Extrinsic : Pre-calibrate pose for tag (option)	localization &  generator
ImageTopic	The input image topic	localization (Ros only)
ImageSize	The input image size [W, H]	localization
ImageIntrinsic	Intrinsic parameter of the camera   [$f_x$, 0, $c_x$, 0, $f_y$, $c_y$, 0, 0, 1]	localization
ImageDistrotion	Distrotion parameter of the camera   [$k_1$, $k_2$, $p_1$, $p_2$, ($k_3$)]	localization
T_b_c	deprecate /	/
PosePublishTopic	The output camera pose topic	localization
DebugPlot	Choose whether to plot the debug image (close to get better performance)	localization(Pi only)

How to run

rosrun extend_april_local localization

Sample

Test

Check whether camera is working

   Use rqt to check wether ros camera is working

Simulate Test with bag

bag is in [link](bag - Google Drive)

rosrun extend_april_local localization

rosbag play test.bag

rviz

Camera calibration

You need to calibrate the camera manually. Ros camera calibration maybe a good choice.

You need to get $f_x$ $f_y$ $c_x$ $c_y$ for intrinsic and $k_1$ $k_2$ $p_1$ $p_2$ $(k_3)$ for distortion coefficients. Tipically you should not use camera with high distortion.

Output check

see whether the tf tree work in rviz