In which scenario is 3D vision particularly advantageous?

• A. Depth information enabling pose estimation.
• B. Flat part inspection on a conveyor.
• C. Color-based classification only.
• D. 3D vision is never used with cooperative robots.

Answer: (B)

3D vision excels when you need real geometry, not just how something looks. On a conveyor, parts are moving and can arrive with different orientations and subtle surface features that aren’t obvious from color or shading alone. Depth information lets you measure true dimensions, assess flatness and thickness, and detect geometric defects like warping, dents, or missing features reliably as each part passes by. This makes inspection of flat parts robust to lighting changes and color variations, and it also helps determine the exact pose for gripping or subsequent operations. While depth data can support pose estimation, the strongest benefit in this scenario is the ability to quantify geometry and surface topology directly, which is harder to do accurately with 2D/color data.