Towards Context-Aware Human-like Pointing Gestures with RL Motion Imitation

Anna Deichler, Siyang Wang, Simon Alexanderson, Jonas Beskow
9/16/2025
cs.ROcs.HCcs.LG

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Abstract

Pointing is a key mode of interaction with robots, yet most prior work has focused on recognition rather than generation. We present a motion capture dataset of human pointing gestures covering diverse styles, handedness, and spatial targets. Using reinforcement learning with motion imitation, we train policies that reproduce human-like pointing while maximizing precision. Results show our approach enables context-aware pointing behaviors in simulation, balancing task performance with natural dynamics.

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Cite this paper

@article{deichler2025towards,
  title  = {Towards Context-Aware Human-like Pointing Gestures with RL Motion Imitation},
  author = {Anna Deichler and Siyang Wang and Simon Alexanderson and Jonas Beskow},
  year   = {2025},
  eprint = {2509.12880},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2509.12880v1}
}

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