保持Franka Emika Panda机器人正常运行：具备可靠位置接口的ROS 2软件栈
Keeping the Franka Emika Panda alive: a ROS 2 stack with a reliable position interface
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中文总结 AI 辅助
本文提出开源ROS 2软件栈，解决Franka Emika Panda机器人外部位置接口不可靠问题，经多场景验证，降低人机协作应用开发门槛。
中文摘要 AI 辅助
本文提出了一个开源软件栈，该软件栈可恢复Franka Emika Panda机器人的ROS 2支持，同时解决其外部位置控制接口长期存在的不可靠性问题。我们首先分析了位置控制不稳定的根本原因，表明观察到的振动和保护性停机源于外部控制回路的时序和采样抖动，而非机器人本身的限制。基于此分析，我们引入了一种异步硬件接口，将实时通信与ROS 2控制回路解耦，为较慢的命令源设计了速率匹配机制，还提出了一种位置域参考生成策略，可生成可靠、平滑的位置命令。实验验证表明，所提架构通过减少官方实现引入的运动伪影，能可靠地跟踪速度参考；该软件栈在两个独立的Panda平台上，经过运动规划、柔顺控制、位置控制操作和触觉遥操作的验证。通过为Panda机器人恢复现代、可靠且开放的ROS 2生态系统，本研究降低了开发安全、响应迅速且可复现的人机协作应用的门槛，这类应用可整合规划、感知、交互与共享自主能力。代码和视频可在我们的网站（此https URL）获取。
英文摘要
This paper presents an open-source software stack that restores ROS 2 support for the Franka Emika Panda robot while resolving the long-standing unreliability of its external position control interface. We first analyze the root causes of unstable position control and show that the observed vibrations and protective stops arise from the timing of the external control loop and sampling jitter, rather than from limitations of the robot itself. Building on this analysis, we introduce an asynchronous hardware interface that decouples real-time communication from the ROS 2 control loop, a rate-matching mechanism for slower command sources, and a position-domain reference generation strategy that produces reliable, smooth position commands. Experimental validation shows that the proposed architecture reliably tracks velocity references by reducing motion artifacts introduced by the official implementation, and the stack is validated across motion planning, compliance control, position-controlled manipulation, and haptic teleoperation on two independent Panda platforms. By restoring a modern, reliable, and open ROS 2 ecosystem for the Panda, this work lowers the barrier to developing safe, responsive, and reproducible human-robot collaboration applications that integrate planning, perception, interaction, and shared autonomy. Code and videos are available on our website at https://sites.google.com/view/fer-ros2/.
发表机构
- University of Salerno（萨勒诺大学）
机构由 AI 辅助整理，请以论文原文为准。
