Running an Action Server and Client with Other Nodes

Writing the Data Node

Before running the action server and client a data node needs to be created. Create learning_actionlib/src/gen_numbers.py in your favorite editor, and place the following inside it:

   1 #!/usr/bin/env python
   2 import roslib; roslib.load_manifest('learning_actionlib')
   3 import rospy
   4 from std_msgs.msg import Float32
   5 import random
   6 def gen_number():
   7     pub = rospy.Publisher('random_number', Float32)
   8     rospy.init_node('random_number_generator', log_level=roslib.msg.Log.INFO)
   9     rospy.loginfo("Generating random numbers")
  10 
  11     while not rospy.is_shutdown():
  12         pub.publish(Float32(random.normalvariate(5, 1)))
  13         rospy.sleep(0.05)
  14 
  15 if __name__ == '__main__':
  16   try:
  17     gen_number()
  18   except Exception, e:
  19     print "done"
  20 

The above code generates random numbers with a normal distribution centered around 5 with a standard deviation of 1 and publishes the numbers on the /random_number topic.

Don't forget to make the node executable:

• chmod +x gen_numbers.py

Start the Data Node

Start by bringing up the roscore in a new terminal:

$ roscore

Now start the data node in a new terminal:

rosrun learning_actionlib gen_numbers.py 

You will see:

• Generating random numbers

Viewing the Action Feedback

In a new terminal, rostopic the feedback channel to see the feedback from the action server:

$ rostopic echo /averaging/feedback

While the server is acting on the goal you will see something similar to:

• ---
  header: 
    seq: 1
    stamp: 1251489509536852000
    frame_id: 
  status: 
    goal_id: 
      stamp: 1251489509511553000
      id: 1251489509.511553000
    status: 1
    text: 
  feedback: 
    sample: 1
    data: 3.96250081062
    mean: 3.96250081062
    std_dev: 0.000687940046191
  ---
  header: 
    seq: 2
    stamp: 1251489509588828000
    frame_id: 
  status: 
    goal_id: 
      stamp: 1251489509511553000
      id: 1251489509.511553000
    status: 1
    text: 
  feedback: 
    sample: 2
    data: 5.16988706589
    mean: 4.56619405746
    std_dev: 0.60369348526
  ---

Viewing the Action Result

In a new terminal, rostopic the feedback channel to see the feedback from the action server:

$ rostopic echo /averaging/result

After the goal is completed you will see something similar to:

• ---
  header: 
    seq: 1
    stamp: 1251489786993936000
    frame_id: 
  status: 
    goal_id: 
      stamp: 1251489781746524000
      id: 1251489781.746524000
    status: 4
    text: 
  result: 
    mean: 4.99936008453
    std_dev: 1.10789334774

Viewing the Action Node Graph

Alternatively you can look at the nodes:

$ rxgraph

Start the Client and Server

Start the action server in a new terminal:

$ rosrun learning_actionlib averaging_server

When the action has completed it will print out an info message which may be succeeded or aborted depending on the random data sampled.

• [ INFO] 1251489514.736936000: /averaging: Aborted

And then run the action client in a new terminal:

$ rosrun learning_actionlib averaging_client

When the client receives notification of the completion of the goal it will also print out an info message with the result of the action:

• [ INFO] 1251489514.737339000: Action finished: ABORTED