Assignment

Assignment

At the end of this assignment you will have a set of tools that you can use during the practical part of the workshop. So do your best to make it as useful and easy-to-use as possible.

First part of the assignment

Using the joint state publisher and a simulated robot save various joint and Cartesian space configurations into a Pickle file. Use the scripts that you wrote in the previous assignment.

Make sure to store at least 4 configurations and make them "more or less" meaningful. For instance, a "home" position, an "approach" position, an "away from everythin" position, etc.

Here are a couple of hints that will make your life easier on the long-term (but you will hate on the short-term):

• Always save both joints and Cartesian space data: data['frame1'] = [joints, transform]
• Use raw_input to define the name under which you want to store data:

...
new_name = raw_input("Please provide the name for the new item")
...
transform.child_frame_id = new_name
data[new_name] = transform
...

• Visualize the frames in Rviz
• Try to define the full path of the location of the file
• The names should following the "snake case" style: this_is_a_name

Second part of the assignment

Using the Pickle file that you created in the first part of the assignment, you will publish the messages that were stored as TransformStamped onto TF. You will do so using the script that you write in the previous assignments.

Next, you will move the simulated robot into these configurations. Help yourselves with the convenient methods: transformstamped_to_pose and get_pose_from_tf. You will find the code snippets below.

transformstamped_to_pose

def transformstamped_to_pose(transform_stamped):
    """Convert from geometry_msgs/TransformStamped to geometry_msgs/Pose

    Args:
        transform_stamped (geometry_msgs/TransformStamped): The geometry_msgs/TransformStamped message to convert

    Returns:
        Pose: The geometry_msgs/Pose message
    """
    return Pose(position=transform_stamped.transform.translation, orientation=transform_stamped.transform.rotation)

get_pose_from_tf

def get_pose_from_tf(target, tf_buffer, relative_to='base_link'):
    """Return a Pose object to the desired TF frame

    Args:
        target (str): TF frame that we are interested in
        tf_buffer (tf2_ros.Buffer): A TF buffer. Don't forget to initialize it with the listener!!!
        relative_to (str, optional): Relative to ...

    Return:
        Pose: The TF frame expressed as geometry_msgs/Pose
    """

    rospy.sleep(0.1)
    target_transform = tf_buffer.lookup_transform(relative_to, target, rospy.Time(0))
    return transformstamped_to_pose(target_transform)

The assignment is completed once you show that your robot moved in at least 4 configurations, both in joint and Cartesian space.

Good luck.