Paper ID: 2502.02967 • Published Feb 5, 2025
Demonstrating a Control Framework for Physical Human-Robot Interaction Toward Industrial Applications
Bastien Muraccioli (CNRS-AIST JRL), Celerier Mathieu (CNRS-AIST JRL), Benallegue Mehdi (CNRS-AIST JRL), Venture Gentiane (CNRS-AIST JRL...
TL;DR
Get AI-generated summaries with premium
Get AI-generated summaries with premium
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, 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 at
the robot's end-effector to demonstrate the framework's capabilities. This
setup enables seamless dynamic switching between the modes, and real-time
adjustment 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,
to ensure reproducibility for both research and industrial deployment, this
framework demonstrates industrial-grade performance and repeatability,
showcasing its potential as a robust pHRI control system for industrial
environments.