A Robot Teleoperation Framework for Human Motion Transfer
A Robot Teleoperation Framework for Human Motion Transfer
复制标题
用于人体运动转移的机器人远程操作框架
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
C. Torras
中科院分区：
文献类型：
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作者：
Miguel Arduengo;Ana Arduengo;Adrià Colomé;J. Lobo;C. Torras
将人类运动转移到移动的机器人操纵器并确保安全的人机物理交互是在人类共享环境中实现复杂操纵任务自动化的关键步骤。在这项工作中，我们提出了一个机器人全身遥操作框架的人体运动转移。我们提出了一个一般的解决方案的对应问题：一个映射，定义了机器人和观察到的人类姿势之间的等价。为了实现实时遥操作和有效的冗余解决方案，我们利用全身范式与适当的任务层次，并提出了一种差分驱动控制算法的轮式机器人基地。为了确保安全的物理人机交互，我们提出了一个可变导纳控制器，稳定地适应动态的末端执行器之间切换刚性和顺应性的行为。我们通过使用TIAGo机器人的几个实验来验证我们的方法。结果表明，有效的实时模仿和动态行为适应。这可能是一个简单的方法，非专家教一个粗略的操作技能的辅助机器人。
Transferring human motion to a mobile robotic manipulator and ensuring safe physical human-robot interaction are crucial steps towards automating complex manipulation tasks in human-shared environments. In this work we present a robot whole-body teleoperation framework for human motion transfer. We propose a general solution to the correspondence problem: a mapping that defines an equivalence between the robot and observed human posture. For achieving real-time teleoperation and effective redundancy resolution, we make use of the whole-body paradigm with an adequate task hierarchy, and present a differential drive control algorithm to the wheeled robot base. To ensure safe physical human-robot interaction, we propose a variable admittance controller that stably adapts the dynamics of the end-effector to switch between stiff and compliant behaviors. We validate our approach through several experiments using the TIAGo robot. Results show effective real-time imitation and dynamic behavior adaptation. This could be an easy way for a non-expert to teach a rough manipulation skill to an assistive robot.