通过multipanda ros2弥合仿真到现实的差距：一种用于多手系统的真实时间ROS2框架
Bridging the Sim-to-Real Gap with multipanda_ros2: A Real-Time ROS2 Framework for Multimanual Systems
AI总结：
multipanda_ros2通过实时ROS2框架和高保真仿真整合，实现了多机器人系统的高精度控制与sim2real差距的弥合。
摘要：
我们提出了multipanda_ros2，一种新的开源ROS2架构，用于Franka Robotics机器人的多机器人控制。利用ros2控制，该框架提供原生的ROS2接口，可以从单个进程控制任意数量的机器人。我们的核心贡献解决了实时扭矩控制中的关键挑战，包括交互控制和机器人-环境建模。本工作的一个重点是维持1kHz的控制频率，这对于实时控制以及安全标准所需的最低频率至关重要。此外，我们引入了一种控制let-特征设计模式，使控制器切换延迟不超过2毫秒，从而促进可重复的基准测试和复杂的多机器人交互场景。为了弥合仿真到现实（sim2real）的差距，我们整合了高保真的MuJoCo仿真，并引入了定量指标，用于 kinematic 准确性和动态一致性（扭矩、力和控制误差）。此外，我们证明了现实世界惯性参数识别可以显著提高力和扭矩的准确性，提供了一种迭代物理修正的方法。我们的工作将软机器人方法扩展到刚性双臂、接触丰富的任务，展示了减少sim2real差距的有希望的方法，并提供了一个稳健、可重复的平台，用于高级机器人研究。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
