Bridging the Sim-to-Real Gap with multipanda ros2: A Real-Time ROS2 Framework for Multimanual Systems

TL;DR

This paper introduces multipanda_ros2, a real-time ROS2 framework enabling multi-robot control with high-frequency torque control, simulation integration, and rapid controller switching, aimed at reducing the sim2real gap in robotics.

Contribution

It presents a novel ROS2 architecture with high-frequency control, controller-switching capabilities, and integration of high-fidelity simulation for improved sim2real transfer in multi-robot systems.

Findings

Achieves 1kHz control frequency for real-time torque control.

Controller-switching delays are reduced to ≤ 2 ms.

High-fidelity MuJoCo simulation improves kinematic and dynamic accuracy.

Abstract

We present $multipanda\_ros2$, a novel open-source ROS2 architecture for multi-robot control of Franka Robotics robots. Leveraging ros2 control, this framework provides native ROS2 interfaces for controlling any number of robots from a single process. Our core contributions address key challenges in real-time torque control, including interaction control and robot-environment modeling. A central focus of this work is sustaining a 1kHz control frequency, a necessity for real-time control and a minimum frequency required by safety standards. Moreover, we introduce a controllet-feature design pattern that enables controller-switching delays of $\le 2$ ms, facilitating reproducible benchmarking and complex multi-robot interaction scenarios. To bridge the simulation-to-reality (sim2real) gap, we integrate a high-fidelity MuJoCo simulation with quantitative metrics for both kinematic accuracy and dynamic consistency (torques, forces, and control errors). Furthermore, we demonstrate that real-world inertial parameter identification can significantly improve force and torque accuracy, providing a methodology for iterative physics refinement. Our work extends approaches from soft robotics to rigid dual-arm, contact-rich tasks, showcasing a promising method to reduce the sim2real gap and providing a robust, reproducible platform for advanced robotics research.