This package extends the object tracking packages dbot and dbot_ros to track articulated rigid bodies with several degree of freedom. In addition to depth images, the robot tracker incorporates joint angle measurements at a higher rate, typically 100Hz-1kHz. Here are some of the core features
For more details on the algorithm, please check https://am.is.tuebingen.mpg.de/publications/garciacifuentes-ral.
First of all, set up and run the example, as described in the Getting Started documentation.
Now you can use the working example as a starting point. To use your own robot, you will need its URDF, and you will need to modify some launch and config files in dbrt_example. The launch files should be self explanatory and easy to adapt. You will need to edit the file fusion_tracker_gpu.launch (fusion_tracker_cpu.launch) to use your own robot model, instead of Apollo.
The main work will be to adapt the fusion_tracker_gpu.yaml (fusion_tracker_cpu.yaml) file to your robot. All the parameters for the tracking algorithm are specified in this file, and it is robot specific. You will have to adapt the link and joint names to your robot. Furthermore, you can specify which joints should be corrected using the depth images, how aggressively they should be corrected, and whether you want to estimate an offset between the true camera and the nominal camera in your robot model.
Our algorithm assumes that the frame of the depth image (specified by the camera_info topic) exists in your URDF robot model. You can check the camera frame by running:
rostopic echo /camera/depth/camera_info
If this frame does not exist in your robot URDF, you have to add such a camera frame to the part of the robot where the camera is mounted. This requires connecting a camera link through a joint to another link of the robot. Take a look at head.urdf.xacro .
The XTION camera link XTION_RGB is connected to the link B_HEAD through the joint XTION_JOINT. The transformation between the camera and the robot is not required to be very precise, since our algorithm can estimate an offset. However, it must be accurate enough to provide a rough initial pose.
@article{GarciaCifuentes.RAL,
title = {Probabilistic Articulated Real-Time Tracking for Robot Manipulation},
author = {Garcia Cifuentes, Cristina and Issac, Jan and W{\"u}thrich, Manuel and Schaal, Stefan and Bohg, Jeannette},
journal = {IEEE Robotics and Automation Letters (RA-L)},
volume = {2},
number = {2},
pages = {577-584},
month = apr,
year = {2017},
month_numeric = {4}
}