In routine pick-and-place, why is repeatability often more important than absolute encoder accuracy?

• A. Because tasks require reaching the same discrete locations repeatedly, and absolute accuracy may be within tolerance.
• B. Because repeatability includes absolute measurement error across all tasks.
• C. Because absolute accuracy is impossible to measure.
• D. Because variance in repeatability is more forgiving than offset.

Answer: (A)

In routine pick-and-place, consistency in hitting the same spots is what drives reliable operation. Repeatability measures how tightly the robot can return to a given pose from cycle to cycle. When repeatability is high, each cycle lands in essentially the same location, so the gripper can pick and place reliably even if the robot’s reported absolute position isn’t perfect. The absolute encoder accuracy tells you how close the measured position is to the true world position, but that global accuracy isn’t as critical if you can define and reuse the same target poses. Any small constant offset or drift can be compensated with a fixed calibration, a jig, or a quick vision alignment at the moment of pick/place, so long as the robot can repeat the same location consistently.

So the reason this is best is that the task requires repeatedly reaching the same discrete locations; high repeatability ensures those hits are consistent, while absolute accuracy can be managed or corrected within the cycle. The other statements don’t capture this practical emphasis: repeatability is about returning to the same pose, not across all tasks; absolute accuracy can be measured and is not inherently immeasurable; and the idea that variance is more forgiving than offset doesn’t explain why hitting the same spot reliably matters in this context.