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<p>This paper proposes an integrated framework for real-time remote control and safety monitoring of the 7-DoF Franka Emika Panda manipulator. Based on the leader-follower structure, the remote control system and the Ruckig algorithm realize precise trajectory generation and smooth robot motion. The safety monitoring system integrates depth cameras, fiducial markers, and skeleton detection techniques to enable accurate tracking of human body positions in robot coordinates. The risk of collision is evaluated by comparing the Euclidean distance between the end effector and the tracked human center point to the protected separation distance defined by the ISO/TS 15066 speed-and-separation monitoring model. In the experiment, the system identifies potential collisions and adjusts the speed scaling factor to safely decelerate the robot to continue its work. These results provide safe control in a dynamic human-robot environment while the proposed framework provides millimeter-level remote control accuracy. All software is open-sourced and can be found on our website: <a href="https://github.com/IRaC-Lab/franka-open-mp-integration">https://github.com/IRaC-Lab/franka-open-mp-integration</a>.</p>

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Remote Synchronization and Dynamic Safety Control for Robot Manipulators with Heterogeneous Kinematic Structures

  • 期刊论文

  • 发表日期：

    2026年4月21日

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  • Ju-Hwan Kang,
  • Yeong-Bin Kim,
  • Nak-Won Choi,
  • Bum Yong Park

摘要

This paper proposes an integrated framework for real-time remote control and safety monitoring of the 7-DoF Franka Emika Panda manipulator. Based on the leader-follower structure, the remote control system and the Ruckig algorithm realize precise trajectory generation and smooth robot motion. The safety monitoring system integrates depth cameras, fiducial markers, and skeleton detection techniques to enable accurate tracking of human body positions in robot coordinates. The risk of collision is evaluated by comparing the Euclidean distance between the end effector and the tracked human center point to the protected separation distance defined by the ISO/TS 15066 speed-and-separation monitoring model. In the experiment, the system identifies potential collisions and adjusts the speed scaling factor to safely decelerate the robot to continue its work. These results provide safe control in a dynamic human-robot environment while the proposed framework provides millimeter-level remote control accuracy. All software is open-sourced and can be found on our website: https://github.com/IRaC-Lab/franka-open-mp-integration.