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We study the effect of familiarization on the predictability of robot motion. Predictable motion is motion that matches the observer's expectation. Because of the difficulty robots have in learning motion from user demonstrations, we explore the idea of having users learn from robot demonstrations --- how accurate do users get at predicting how the robot will move? We find that although familiarization significantly increases predictability, its utility depends on how natural the motion is. Overall, familiarization shows great promise, but needs to be combined with other methods that generate appropriate motion with which to be familiarized.
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Stored only when both papers are in the corpus — 43 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.