Matlab interface for the dVRK ROS topics

Interface class used to subscribe and publish to the dVRK (da Vinci Research Kit) ROS topics in Matlab (client side). To use this class, one must first start the cisst/SAW based C++ controller with the ROS interfaces (server).

See in dvrk-ros (on github: https://github.com/jhu-dvrk/dvrk-ros), package dvrk_robot, application dvrk_console_json. To compile and install dvrk-ros, see https://github.com/jhu-dvrk/sawIntuitiveResearchKit/wiki/CatkinBuild.

To configure your Matlab path and make sure the CRTK custom messages support is all set, please read CRTK Matlab client README.

The class dvrk.arm contains the matlab interface to the dVRK ROS topics. It also handles data conversion from ROS messages (Poses to 4x4 homogeneous transformations) as well as timer based wait for blocking commands (i.e. wait for state transitions and end of trajectories). The dVRK Matlab client classes rely on the CRTK Matlab client package (see crtk.utils).

Warning

The default classes in the dVRK Matlab package subscribe to all the dVRK topics we can subscribe to. This is convenient to test your code or use in an interactive shell. For a user application, it is recommended to create your own arm class and only add the features you need. This will reduce the amount of network messages and computing load on both sides (dVRK and Matlab). You should likely copy the file +dvrk/arm.m and remove the features you don't need.

Usage

You will need Matlab 2015a or higher with the Robotic System Toolbox: http://www.mathworks.com/products/robotics/. To test on Matlab on the same computer:

• Start the application dvrk_console_json or any application using the standard ROS dVRK topics outside Matlab
• In Matlab:
  • See examples in examples directory!
  • Start ROS using rosinit
  • Find the robot name using rostopic list. You should see a list of namespaces for each arm. For example /MTML/measured_js indicates that the arm MTML is available.
  • Create an interface for your arm using: r = arm('MTML);
  • All units are SI (radians and meters)
  • r will have the following methods (e.g. MTM has 7 joints):
    • r.setpoint_cp() [4x4 floats]
    • [position, velocity, effort] = r.setpoint_js() [n floats, empty, n floats] (output of PID)
    • r.measured_cp() [4x4 floats]
    • [position, velocity, effort] = r.setpoint_js() [n floats, n floats, n floats] (based on encoder and motor current feedback)
  • To control the arm, one can do:
    • r.enable(60) enables (powers on) the robot and wait for up to 60 seconds, will return false if it was not able to enable.
    • r.home(30) request homing and will wait until the arm is homed. Also returns false if the "method" fails.
    • r.servo_jp() defines a new PID setpoint in joint space. Input is a vector of joint positions.
    • r.servo_jr() adds to the current joint setpoint (i.e. relative).
    • r.move_jp() sets a new goal for the trajectory generator, in joint space. Input is a vector of joints positions. move_ commands return the time the command was sent to the robot.
    • r.move_jp().wait() move and wait until move is complete. wait can be used with all move_ commands returning a wait_move_handle.
    • r.servo_cp() and r.move_cp() are similar to servo_jp and move_jp execpt in cartesian space. Input is a 4x4 matrix of floats (i.e. homogeneous transformation).

Notes

• There are also classes derived from dvrk.arm for arm specific features, e.g. dvrk.mtm, dvrk.psm. These classes add methods for the gripper and jaw.
• One of the nice features of the Matlab ROS toolbox is that you can now run your code on a different computer (even if it's running Windows or MacOS) and communicate with the dVRK PC running Ubuntu using ROS topics. If you're using two computers on the same subnet, make sure your resolv.conf or whatever file is used to resolve the full computer name is set so you can ping each computer using the short name (e.g. don't ping lcsr-dv-stereo.hwcampus.jhu.edu, ping lcsr-dv-stereo). Otherwise, ROS might show you the topics but will still not be able to publish or subscribe. On some systems you might even have to hard code the IP addresses of the remote host on both the "client" and "server" in the hosts file (google will tell you where to find the equivalent of /etc/hosts on different OSs).
• If you modify the arm.m file, send us a pull request or use the dVRK google group to let us know. Your contributions are always welcome!
• The current code doesn't do a great job at cleaning up. You might have to use rosshutdown and delete your robot instances manually.
• To create 4x4 matrices, take a look at the matlab commands axang2tform, eul2tform, ...