Open-VICO: An Open-Source Gazebo Toolkit for Vision-based Skeleton Tracking in Human-Robot Collaboration
Open-VICO: An Open-Source Gazebo Toolkit for Vision-based Skeleton Tracking in Human-Robot Collaboration
复制标题
Open-VICO：用于人机协作中基于视觉的骨骼跟踪的开源 Gazebo 工具包
DOI：
--
复制
发表时间：
2022
期刊：
影响因子：
--
通讯作者：
A. Ajoudani
中科院分区：
文献类型：
--
作者：
Luca Fortini;M. Leonori;J. Gandarias;E. Momi;A. Ajoudani
仿真工具对于机器人研究至关重要，特别是对于那些安全至关重要的领域，例如人机协作（HRC）。然而，它是具有挑战性的，以模拟人类的行为，现有的机器人模拟器没有集成功能的人类模型。这项工作提出了Open-VICO，一个开源的工具包，以集成虚拟人模型在Gazebo专注于基于视觉的人体跟踪。特别是，Open-VICO允许联合收割机在同一个仿真环境中结合逼真的人体运动学模型，多摄像机视觉设置，人体跟踪技术沿着众多的机器人和传感器模型，感谢Gazebo。将预先记录的人体骨骼运动与运动捕捉系统相结合的可能性拓宽了人机交互（HRI）设置中人类行为分析的前景。为了描述功能并强调工具包的潜力，从该领域的相关文献挑战中选择了四个具体示例，使用我们的模拟工具开发：i）模拟中的3D多RGB-D相机校准，ii）基于OpenPose创建合成人体骨骼跟踪数据集，iii）模拟中人体骨骼跟踪的多相机场景，以及iv）人机交互示例。这项工作的关键是创建一个简单的管道，我们希望这将激励研究新的基于视觉的算法和方法，用于轻量级的人类跟踪和灵活的人机应用。
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.