# Expressive Robot Motion Timing

arXiv: https://arxiv.org/abs/1802.01536 · HTML: https://mlsanity.com/paper/1802.01536/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Feb 2018.

## Built on by (most cited first, 3 of 3)

- [Augmented Reality and Robotics: A Survey and Taxonomy for AR-enhanced Human-Robot Interaction and Robotic Interfaces](https://mlsanity.com/paper/2203.03254/) (2022)
- [Mining multi-modal communication patterns in interaction with explainable and non-explainable robots](https://mlsanity.com/paper/2312.14634/) (2023)
- [Re-imagining ISO 26262 in the Age of Autonomous Vehicles: Enhancing Controllability through Transferability and Predictability](https://mlsanity.com/paper/2606.07437/) (2026)

## Abstract (arXiv)

Our goal is to enable robots to time their motion in a way that is purposefully expressive of their internal states, making them more transparent to people. We start by investigating what types of states motion timing is capable of expressing, focusing on robot manipulation and keeping the path constant while systematically varying the timing. We find that users naturally pick up on certain properties of the robot (like confidence), of the motion (like naturalness), or of the task (like the weight of the object that the robot is carrying). We then conduct a hypothesis-driven experiment to tease out the directions and magnitudes of these effects, and use our findings to develop candidate mathematical models for how users make these inferences from the timing. We find a strong correlation between the models and real user data, suggesting that robots can leverage these models to autonomously optimize the timing of their motion to be expressive.