ヒューマンロボットインタラクションのためのマーカーレス複数人追従におけるロバストフィルタ
A Robust Filter for Marker-less Multi-person Tracking in Human-Robot Interaction Scenarios
単一のRGB-Dカメラと姿勢推定から得られる不完全な3D人間姿勢をフィルタリングし、遮蔽やノイズに対処することで、ロボットのジッタを抑え滑らかなインタラクションを実現する手法を提案。
著者: Enrico Martini, Harshil Parekh, Shaoting Peng, Nicola Bombieri, Nadia Figueroa
分類: cs.RO, cs.AI, cs.HC
原文アブストラクト
Pursuing natural and marker-less human-robot interaction (HRI) has been a long-standing robotics research focus, driven by the vision of seamless collaboration without physical markers. Marker-less approaches promise an improved user experience, but state-of-the-art struggles with the challenges posed by intrinsic errors in human pose estimation (HPE) and depth cameras. These errors can lead to issues such as robot jittering, which can significantly impact the trust users have in collaborative systems. We propose a filtering pipeline that refines incomplete 3D human poses from an HPE backbone and a single RGB-D camera to address these challenges, solving for occlusions that can degrade the interaction. Experimental results show that using the proposed filter leads to more consistent and noise-free motion representation, reducing unexpected robot movements and enabling smoother interaction.
