#!/usr/bin/env python
import roslib
roslib.load_manifest('learning_tf')

import rospy
import tf

if __name__=='__main__':
    rospy.init_node('my_tf_broadcaster')
    br=tf.TransformBroadcaster()
    rate=rospy.Rate(10.0)
    while not rospy.is_shutdown():
        br.sendTransform((0.0,2.0,0.0),
                        (0.0,0.0,0.0,1.0),
                        rospy.Time.now(),
                        "carrot1",
                        "turtle1")
        rate.sleep()
dfb1cd4aefb016020fd489642ec443a6a155a0d8
<mask token>

<mask token>
roslib.load_manifest('learning_tf')
<mask token>
if __name__ == '__main__':
    rospy.init_node('my_tf_broadcaster')
    br = tf.TransformBroadcaster()
    rate = rospy.Rate(10.0)
    while not rospy.is_shutdown():
        br.sendTransform((0.0, 2.0, 0.0), (0.0, 0.0, 0.0, 1.0), rospy.Time.
            now(), 'carrot1', 'turtle1')
        rate.sleep()

import roslib
roslib.load_manifest('learning_tf')
import rospy
import tf
if __name__ == '__main__':
    rospy.init_node('my_tf_broadcaster')
    br = tf.TransformBroadcaster()
    rate = rospy.Rate(10.0)
    while not rospy.is_shutdown():
        br.sendTransform((0.0, 2.0, 0.0), (0.0, 0.0, 0.0, 1.0), rospy.Time.
            now(), 'carrot1', 'turtle1')
        rate.sleep()

#!/usr/bin/env python
import roslib
roslib.load_manifest('learning_tf')

import rospy
import tf

if __name__=='__main__':
    rospy.init_node('my_tf_broadcaster')
    br=tf.TransformBroadcaster()
    rate=rospy.Rate(10.0)
    while not rospy.is_shutdown():
        br.sendTransform((0.0,2.0,0.0),
                        (0.0,0.0,0.0,1.0),
                        rospy.Time.now(),
                        "carrot1",
                        "turtle1")
        rate.sleep()