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

Hardware & OS

Raspberry pi 3, 3b, 3b+, 4, Zero 2W

Raspberry pi Os 32bit LTS With Legacy Camera API

DLL Required

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

Install dll 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

Build Instruction (or direct run exe file with dll)

mkdir build && cd build
cmake ..
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 demo

./localization

or manually set config path by ./localization ${path_to_yaml_file}

Sample

How to use it

Directly add code onto the base

You can add code at the position we use cout to print the position to the terminal and add the user defined behavior code at that postion.

Use it as a library

TBD

Trouble shooting

Check whether camera is working

Camera Type We test v1 & v2 raspberry camera. But it should work with all camera which support Legacy Camera API on Raspberry Pi

• Plugin camera

• Open Legacy Camera interface with rasp raspi-config

• Reboot

• Install opencv python to run test script sudo apt install -y python3-opencv

• Using test script cameratest.py to test whether camera workwell

Check whether the dll is working

Run the release exe file after doing Install dll with apt-get

Simulate Test with video

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 the Image out check whether everything goes well and check whether the xyz on the left top corner make sence unit is (m)