We proceed similarly to create the object for the table, which is also approximated by a box. Therefore, we simply remove any previous object and add the table. In this case, the object name is table:

# Retrieve params: 
self._table_object_name = rospy.get_param('~table_object_name', 
 'table')

# Clean the scene: 
self._scene.remove_world_object(self._table_object_name) 
 
# Add table and Coke can objects to the planning scene: 
self._pose_table = self._add_table(self._table_object_name) 

The _add_table method adds the table to the planning scene:

def _add_table(self, name): 
    p = PoseStamped() 
    p.header.frame_id = self._robot.get_planning_frame() 
    p.header.stamp = rospy.Time.now() 
 
    p.pose.position.x = 1.0 
    p.pose.position.y = 0.0 
    p.pose.position.z = 1.0 
 
    q = quaternion_from_euler(0.0, 0.0, numpy.deg2rad(90.0)) 
    p.pose.orientation = Quaternion(*q) 
 
    self._scene.add_box(name, p, (1.5, 0.8, 0.03)) 
 
    returnp.pose 

We can visualize the planning scene objects in RViz running the following commands:

    $ roslaunch rosbook_arm_gazebo rosbook_arm_grasping_world.launch
    $ roslaunch rosbook_arm_moveit_config moveit_rviz.launch config:=true
    $ roslaunch rosbook_arm_pick_and_place grasp_generator_server.launch
    $ rosrun rosbook_arm_pick_and_place pick_and_place.py
  

This actually runs the whole pick and place task, which we will continue to explain later. Right after starting the pick_and_place.py program, you will see the boxes that model the table and the can of Coke in green, matching perfectly with the point cloud seen by the RGB-D sensor, as shown in the following figure: