ROS2 IMU Tilt Compensation

Problem Statement

Implement a ROS2 node that reads sensor_msgs/Imu data and computes roll and pitch from the IMU's orientation quaternion, then publishes them as a geometry_msgs/Vector3Stamped (roll=x, pitch=y, yaw=z).

Requirements

Your node must:

• Subscribe to /imu/data (sensor_msgs/Imu)
• In the callback, extract the quaternion from msg.orientation (x, y, z, w)
• Implement quaternion_to_euler(x, y, z, w) -> (roll, pitch, yaw) using:

  roll  = atan2(2*(w*x + y*z), 1 - 2*(x*x + y*y))
  pitch = asin(clamp(2*(w*y - z*x), -1, 1))
  yaw   = atan2(2*(w*z + x*y), 1 - 2*(y*y + z*z))
  

• Publish geometry_msgs/Vector3Stamped on /imu/euler_angles where:
  • vector.x = roll (radians)
  • vector.y = pitch (radians)
  • vector.z = yaw (radians)
• Log roll and pitch in degrees every callback
• Log "IMU Processor Ready" on startup

Input / Output

Input: sensor_msgs/Imu on /imu/data Output: geometry_msgs/Vector3Stamped on /imu/euler_angles

🤖 Why This Matters in Real Robots

Every ground robot needs tilt estimation for stability monitoring — if a robot tips past 30°, it should emergency stop. Drones use this to level their airframe. The RPY decomposition of the orientation quaternion is one of the most commonly needed calculations in any ROS2 project, yet it's not built into the standard message types.

Input/Output Format

Input: /imu (sensor_msgs/Imu) | Output: /tilt (std_msgs/Float32)

⚠️ Common Pitfalls

• Ignoring gravity vector
• Confusing degrees and radians

📚 Helpful Resources

• ROS2 Concept: IMU Tilt Compensation