Data-driven architecture to encode information in the kinematics of robots and artificial avatars

2024/03/11 by Francesco De Lellis, Marco Coraggio, De Lellis, Francesco +9 · 1 citation
Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Electrical engineering #Human Motion and Animation #Human Pose and Action Recognition #Image Processing and 3D Reconstruction #Machine Learning (cs.LG) #Robotics (cs.RO) #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2403.06557

openalex publication_date 2024/03/11 · openalex created_date 2024/03/13 · openalex updated_date 2026/07/28

Abstract

We present a data-driven control architecture for modifying the kinematics of robots and artificial avatars to encode specific information such as the presence or not of an emotion in the movements of an avatar or robot driven by a human operator. We validate our approach on an experimental dataset obtained during the reach-to-grasp phase of a pick-and-place task.

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