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

• URL: http://arxiv.org/abs/2509.12880v1
• Date: Tue, 16 Sep 2025 09:30:42 GMT
• Title: Towards Context-Aware Human-like Pointing Gestures with RL Motion Imitation
• Authors: Anna Deichler, Siyang Wang, Simon Alexanderson, Jonas Beskow,
• Abstract summary: We present a motion capture dataset of human pointing gestures covering diverse styles, handedness, and spatial targets.<n>Using reinforcement learning with motion imitation, we train policies that reproduce human-like pointing while maximizing precision.
• Score: 19.868403110796105
• License: http://creativecommons.org/licenses/by/4.0/
• 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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