What is camera calibration, and why is it essential for robot vision?

• A. Estimation of intrinsic and extrinsic parameters to map image pixels to real-world coordinates; enables accurate pose estimation.
• B. Adjusting camera exposure
• C. Replacing the camera with a higher resolution one
• D. Verifying that the camera is mounted level

Answer: (A)

Camera calibration establishes how a camera translates a 3D scene into a 2D image by estimating intrinsic and extrinsic parameters. Intrinsic parameters describe the camera’s internal optics—focal lengths, principal point, and lens distortion—while extrinsic parameters describe the camera’s position and orientation in the world (rotation and translation relative to a reference frame). With these parameters, you can undistort images and, crucially, map pixels to real-world coordinates, which is essential for figuring out where objects or the camera itself are in space. This enables accurate pose estimation, meaning the robot can determine the precise 3D position and orientation of objects or its own end effector from image data. Calibration typically uses a known pattern observed from many angles to solve for the projection model and the transformation between image and world coordinates. Once calibrated, vision-based tasks such as grasping, navigation, or 3D reconstruction become reliable because measurements in images correspond to real dimensions. Exposure adjustments, higher-resolution hardware, or simply mounting level affect image quality or setup but do not establish the geometric mapping needed for real-world coordinates and pose estimation.