SOURCE-LINKED INTELLIGENCE
PAMoR: Parameterized Affective Motion Generation in Real Time for Humanoid Robots
People read a humanoid robot's motion in social settings not only for the action performed but for the affect conveyed. Motion carrying that affect has so far been generated for human avatars, where style is taken from a reference clip or an emotion word, neither of which can be quantitatively parameterized. We present PAMoR, which turns affect into a measured control parameter: a valence-arousal (V-A) coordinate computed natively on robot kinematics. It is obtained in closed form from postural expansion and movement energy, and these measurements serve directly as generation conditions, with
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-28T11:32:33.000Z
First collected: 2026-09-21T08:21:55.975Z. This is not the publication date.