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ヒューマンロボット協調arXiv:2203.14733

Open-VICO: Gazebo上で人間の骨格追跡を可能にするオープンソースツールキット

Open-VICO: An Open-Source Gazebo Toolkit for Vision-based Skeleton Tracking in Human-Robot Collaboration

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Gazebo上で仮想人間モデル・複数カメラ・骨格追跡技術を統合し、人間とロボットの協調研究を支援するオープンソースツールキットを提案した。

著者: Luca Fortini, Mattia Leonori, Juan M. Gandarias, Elena De Momi, Arash Ajoudani

分類: cs.RO, cs.CV, cs.HC

原文アブストラクト

Simulation tools are essential for robotics research, especially for those domains in which safety is crucial, such as Human-Robot Collaboration (HRC). However, it is challenging to simulate human behaviors, and existing robotics simulators do not integrate functional human models. This work presents Open-VICO, an open-source toolkit to integrate virtual human models in Gazebo focusing on vision-based human tracking. In particular, Open-VICO allows to combine in the same simulation environment realistic human kinematic models, multi-camera vision setups, and human-tracking techniques along with numerous robot and sensor models thanks to Gazebo. The possibility to incorporate pre-recorded human skeleton motion with Motion Capture systems broadens the landscape of human performance behavioral analysis within Human-Robot Interaction (HRI) settings. To describe the functionalities and stress the potential of the toolkit four specific examples, chosen among relevant literature challenges in the field, are developed using our simulation utils: i) 3D multi-RGB-D camera calibration in simulation, ii) creation of a synthetic human skeleton tracking dataset based on OpenPose, iii) multi-camera scenario for human skeleton tracking in simulation, and iv) a human-robot interaction example. The key of this work is to create a straightforward pipeline which we hope will motivate research on new vision-based algorithms and methodologies for lightweight human-tracking and flexible human-robot applications.

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