English

Demonstrating a Control Framework for Physical Human-Robot Interaction Toward Industrial Applications

Robotics 2025-05-19 v2 Systems and Control Systems and Control

Abstract

Physical Human-Robot Interaction (pHRI) is critical for implementing Industry 5.0, which focuses on human-centric approaches. However, few studies explore the practical alignment of pHRI to industrial-grade performance. This paper introduces a versatile control framework designed to bridge this gap by incorporating the torque-based control modes: compliance control, null-space compliance, and dual compliance, all in static and dynamic scenarios. Thanks to our second-order Quadratic Programming (QP) formulation, strict kinematic and collision constraints are integrated into the system as safety features, and a weighted hierarchy guarantees singularity-robust task tracking performance. The framework is implemented on a Kinova Gen3 collaborative robot (cobot) equipped with a Bota force/torque sensor. A DualShock 4 game controller is attached to the robot's end-effector to demonstrate the framework's capabilities. This setup enables seamless dynamic switching between the modes, and real-time adjustments of parameters, such as transitioning between position and torque control or selecting a more robust custom-developed low-level torque controller over the default one. Built on the open-source robotic control software mc_rtc, our framework ensures reproducibility for both research and industrial deployment, this framework demonstrates a step toward industrial-grade performance and repeatability, showcasing its potential as a robust pHRI control system for industrial environments.

Keywords

Cite

@article{arxiv.2502.02967,
  title  = {Demonstrating a Control Framework for Physical Human-Robot Interaction Toward Industrial Applications},
  author = {Bastien Muraccioli and Mathieu Celerier and Mehdi Benallegue and Gentiane Venture},
  journal= {arXiv preprint arXiv:2502.02967},
  year   = {2025}
}

Comments

Demo Paper submitted to Robotics: Science and Systems (RSS2025), accepted

R2 v1 2026-06-28T21:33:07.514Z