Depth camera integration in ROS - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ component_behavior

intermediate

What is the output of this ROS node subscribing to a depth camera topic?

Consider a ROS node subscribing to the topic /camera/depth/image_raw which publishes sensor_msgs/Image messages. The node prints the depth value at pixel (320, 240). What will the node output if the depth image encoding is 16UC1 and the pixel value at (320, 240) is 1000?

ROS

import rclpy
from rclpy.node import Node
from sensor_msgs.msg import Image
import numpy as np

class DepthListener(Node):
    def __init__(self):
        super().__init__('depth_listener')
        self.subscription = self.create_subscription(
            Image,
            '/camera/depth/image_raw',
            self.listener_callback,
            10)

    def listener_callback(self, msg):
        # Convert raw data to numpy array
        depth_array = np.frombuffer(msg.data, dtype=np.uint16).reshape(msg.height, msg.width)
        depth_value = depth_array[240, 320]
        self.get_logger().info(f'Depth at (320,240): {depth_value}')

rclpy.init()
node = DepthListener()
rclpy.spin(node)
node.destroy_node()
rclpy.shutdown()

A Runtime error due to wrong data type

B Depth at (320,240): 0.1

C Depth at (320,240): 1000.0

D Depth at (320,240): 1000

💡 Hint

Remember that 16UC1 encoding means unsigned 16-bit integers per pixel.

The depth image encoding 16UC1 means each pixel is an unsigned 16-bit integer. The numpy dtype np.uint16 matches this. The pixel value 1000 is read directly as 1000, so the output logs 'Depth at (320,240): 1000'.

📝 Syntax

intermediate

Which option correctly initializes a ROS2 publisher for depth images?

You want to create a ROS2 publisher node that publishes depth images on the topic /camera/depth/image_raw with message type sensor_msgs/msg/Image. Which code snippet correctly creates this publisher?

ROS

import rclpy
from rclpy.node import Node
from sensor_msgs.msg import Image

class DepthPublisher(Node):
    def __init__(self):
        super().__init__('depth_publisher')
        # Publisher initialization here

rclpy.init()
node = DepthPublisher()
rclpy.spin(node)
node.destroy_node()
rclpy.shutdown()

A self.publisher_ = self.create_publisher('/camera/depth/image_raw', Image, 10)

B self.publisher_ = self.create_publisher(Image, '/camera/depth/image_raw', 10)

C self.publisher_ = self.create_publisher(Image, 10, '/camera/depth/image_raw')

D self.publisher_ = self.create_publisher('/camera/depth/image_raw', 10, Image)

💡 Hint

The create_publisher method takes message type first, then topic name, then queue size.

In ROS2 Python, create_publisher is called as create_publisher(msg_type, topic_name, qos). Option B follows this order correctly.

🔧 Debug

advanced

Why does this ROS node fail to convert depth image data correctly?

This ROS node subscribes to a depth image topic with encoding '32FC1' but prints incorrect depth values. What is the likely cause?

ROS

def listener_callback(self, msg):
    depth_array = np.frombuffer(msg.data, dtype=np.uint16).reshape(msg.height, msg.width)
    depth_value = depth_array[240, 320]
    self.get_logger().info(f'Depth: {depth_value}')

A Using np.uint16 instead of np.float32 causes incorrect data interpretation

B The topic name is incorrect, so no data is received

C The reshape dimensions are reversed, causing wrong indexing

D The callback is not registered properly, so it never runs

💡 Hint

Check the encoding type and matching numpy dtype.

The encoding '32FC1' means 32-bit float per pixel. Using np.uint16 reads the bytes incorrectly, resulting in wrong values.

❓ state_output

advanced

What is the value of the variable 'distance' after processing this depth image message?

Given a depth image message with encoding '16UC1' and pixel value 2000 at (100, 150), what is the value of distance after this code runs?

ROS

depth_array = np.frombuffer(msg.data, dtype=np.uint16).reshape(msg.height, msg.width)
distance = depth_array[150, 100] / 1000.0  # convert mm to meters

A 0.2

B 2000

C 2.0

D Raises IndexError

💡 Hint

Remember the pixel coordinates order in numpy arrays is [row, column].

The pixel at (100,150) means column=100, row=150, so depth_array[150, 100] accesses the correct pixel. Value 2000 mm converted to meters is 2.0.

🧠 Conceptual

expert

Which ROS2 QoS profile is best suited for reliable depth camera data streaming in a noisy wireless environment?

You are integrating a depth camera in a ROS2 system over a wireless network prone to packet loss. Which QoS profile should you choose to ensure the most reliable data delivery?

A Reliable reliability with volatile durability

B Reliable reliability with transient local durability

C Best effort reliability with transient local durability

D Best effort reliability with volatile durability

💡 Hint

Reliable means guaranteed delivery; durability controls message persistence.

Reliable reliability ensures message delivery despite packet loss. Volatile durability means messages are not saved for late joiners, suitable for streaming data like depth images.

Practice

1. What is the main purpose of integrating a depth camera in a ROS robot system?

easy

A. To send commands to other robots

B. To measure distances and perceive 3D space around the robot

C. To control the robot's motors directly

D. To store large amounts of data on the robot

Solution

1. Step 1: Understand depth camera function

   A depth camera captures distance information and 3D structure of the environment.

2. Step 2: Identify its role in ROS

   In ROS, depth cameras help robots sense obstacles and navigate safely by providing spatial data.

3. Final Answer:

   To measure distances and perceive 3D space around the robot -> Option B

4. Quick Check:

   Depth camera = 3D sensing [OK]

Hint: Depth cameras help robots see distance and shapes [OK]

Common Mistakes:

• Confusing depth camera with motor control
• Thinking it stores data instead of sensing environment
• Assuming it sends commands to other robots

2. Which ROS launch file command correctly starts a depth camera node named depth_camera_node?

easy

A.

B.

C.

D.

Solution

1. Step 1: Recall ROS launch syntax for nodes

   ROS launch files use the <node> tag with attributes pkg, type, and name to start nodes.

2. Step 2: Match correct syntax

   uses , which is correct syntax.

3. Final Answer:

   <launch><node pkg="camera_pkg" type="depth_camera_node" name="depth_camera_node"/></launch> -> Option A

4. Quick Check:

   Use <node> tag with pkg and type [OK]

Hint: Use <node> tag with pkg and type attributes [OK]

Common Mistakes:

• Using incorrect tags like <start> or <run>
• Missing the name attribute
• Confusing node and type attributes

3. Given this ROS Python snippet subscribing to a depth image topic, what will be printed when a message arrives?

import rospy
from sensor_msgs.msg import Image

def callback(data):
    print(f"Received depth image with width: {data.width}")

rospy.init_node('depth_listener')
rospy.Subscriber('/camera/depth/image_raw', Image, callback)
rospy.spin()

medium

A. No output because callback is never called

B. Received depth image with width: data.width

C. Error: 'Image' object has no attribute 'width'

D. Received depth image with width: 640

Solution

1. Step 1: Understand the callback function

   The callback prints the width attribute of the received Image message.

2. Step 2: Recognize typical Image message fields

   sensor_msgs/Image messages include a width field with the image width, e.g., 640 pixels.

3. Final Answer:

   Received depth image with width: 640 -> Option D

4. Quick Check:

   Image.width prints actual width value [OK]

Hint: Image messages have width attribute with pixel count [OK]

Common Mistakes:

• Thinking width is a string 'data.width'
• Assuming Image message lacks width attribute
• Believing callback never triggers

4. You wrote this ROS launch snippet to start a depth camera node but get an error:

<launch>
  <node pkg="camera_pkg" type="depth_camera" name="depth_camera"/>
</launch>

What is the likely cause of the error?

medium

A. Missing closing tag for <launch>

B. The package 'camera_pkg' is not installed

C. The node type 'depth_camera' does not match the executable name

D. The node name cannot be the same as the package name

Solution

1. Step 1: Check node type and executable name

   The 'type' attribute must exactly match the executable file name in the package.

2. Step 2: Identify mismatch causing error

   If the executable is named 'depth_camera_node' but 'depth_camera' is used, ROS cannot find it.

3. Final Answer:

   The node type 'depth_camera' does not match the executable name -> Option C

4. Quick Check:

   Node type must match executable name [OK]

Hint: Node type must exactly match executable filename [OK]

Common Mistakes:

• Assuming missing closing tag causes error
• Ignoring package installation issues
• Thinking node name conflicts cause this error

5. You want to visualize depth data from a ROS topic /camera/depth/image_raw using OpenCV in Python. Which code snippet correctly converts the ROS Image message to an OpenCV image for display?

hard

A. from cv_bridge import CvBridge
bridge = CvBridge()
cv_image = bridge.imgmsg_to_cv2(data, desired_encoding='passthrough')

B. import cv2
cv_image = cv2.imread('/camera/depth/image_raw')

C. cv_image = data.data.decode('utf-8')

D. cv_image = numpy.array(data)

Solution

1. Step 1: Use cv_bridge to convert ROS Image

   cv_bridge provides imgmsg_to_cv2 to convert ROS Image messages to OpenCV format.

2. Step 2: Apply correct conversion call

   from cv_bridge import CvBridge bridge = CvBridge() cv_image = bridge.imgmsg_to_cv2(data, desired_encoding='passthrough') uses bridge.imgmsg_to_cv2 with 'passthrough' encoding, which preserves depth data correctly.

3. Final Answer:

   from cv_bridge import CvBridge bridge = CvBridge() cv_image = bridge.imgmsg_to_cv2(data, desired_encoding='passthrough') -> Option A

4. Quick Check:

   Use cv_bridge.imgmsg_to_cv2 for ROS to OpenCV [OK]

Hint: Use cv_bridge to convert ROS Image to OpenCV image [OK]

Common Mistakes:

• Trying to read ROS topic as file with cv2.imread
• Decoding raw data as UTF-8 string
• Directly converting data to numpy array without bridge