AprilTag is a visual fiducial system popular in robotics research. This repository contains the most recent version of AprilTag, AprilTag 3, which includes a faster (>2x) detector, improved detection rate on small tags, flexible tag layouts, and pose estimation. AprilTag consists of a small C library with minimal dependencies.
You can find tag images for the pre-generated layouts here. We recommend using the tagStandard41h12 layout.
AprilTag is the subject of the following papers.
AprilTag: A robust and flexible visual fiducial system
AprilTag 2: Efficient and robust fiducial detection
Flexible Layouts for Fiducial Tags
Officially only linux operating systems are supported, although users have had success installing on windows too.
The default installation will place headers in /usr/local/include and shared library in /usr/local/lib. It also installs a pkg-config script into /usr/local/lib/pkgconfig and will install a python wrapper if python3 is installed.
If you have CMake installed or it is not difficult to install, then do:
$ cmake .
$ sudo make install
Otherwise, we have a handwritten makefile you can use (be warned it will do slightly different things):
$ make
$ sudo make install
To install to a different directory than /usr/local:
$ PREFIX=/some/path sudo make install
AprilTag 3 supports a wide variety of possible tag layouts in addition to the classic layout supported in AprilTag 2. The tag's data bits can now go outside of the tag border, and it is also possible to define layouts with "holes" inside of the tag border where there are no data bits. In this repo we have included:
- Two families of the new standard layout. This layout adds a layer of data bits around the outside of the tag border, increasing data density, and the number of possible tags, at the cost of a slight decrease in detection distance.
- Two families of circular tags.
- One family which has a hole in the middle. This could be used for example for drone applications by placing different sized tags inside of each other to allow detection over a wide range of distances.
You can generate your own tag families using our other repo, AprilTag-Generation.
Please create an issue on this github for any questions instead of sending a private message. This allows other people with the same question to find your answer.