实现千赫级实时控制,降低机器人仿真到现实的差距。
Bridging the Sim-to-Real Gap with multipanda ros2: A Real-Time ROS2 Framework for Multimanual Systems
- 基于ROS2构建多机械臂控制框架,支持单进程控制任意数量机器人。
- 保持1kHz控制频率,控制器切换延迟≤2毫秒,满足安全标准。
- 结合高保真仿真与物理参数优化,提升现实任务中力控精度。
我们提出 multipanda_ros2,一个面向Franka Robotics机器人的开源ROS2架构,用于多机器人协同控制。该框架利用ros2 control,从单一进程提供对任意数量机器人的原生ROS2接口。核心贡献解决实时力矩控制中的关键挑战,包括交互控制和机器人-环境建模。本工作重点在于维持1kHz控制频率,这是实时控制的必要条件,也符合安全标准最低要求。此外,我们引入controllet功能设计模式,实现控制器切换延迟≤2毫秒,支持可复现的基准测试与复杂多机器人交互场景。为缩小仿真到现实(sim2real)的差距,我们集成高保真MuJoCo仿真,并采用运动学精度与动力学一致性(力矩、力、控制误差)的定量指标。进一步表明,通过真实世界惯性参数辨识可显著提升力与力矩精度,提供迭代物理模型优化方法。本研究将软体机器人方法扩展至刚性双臂、接触密集型任务,展示了一种有效降低sim2real差距的途径,并提供了一个稳健、可复现的先进机器人研究平台。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。