ros2 robot integration

To address the lack of high-performance, scalable real-time drivers for Universal Robots (UR) collaborative manipulators within the ROS 2 ecosystem, this work designs and implements a modular ROS 2 driver built upon the ur_rtde C++ library. The driver establishes a unified real-time data channel enabling millisecond-level state synchronization and command dispatch, natively supports URScript high-level commands, and introduces a novel plugin-based instruction extension mechanism for dynamic injection of custom control logic. A layered architecture decouples communication, control, and interface layers, significantly enhancing configuration flexibility and adaptability across diverse application scenarios. Experimental evaluation demonstrates robust performance in motion planning, multi-node coordination, and complex trajectory execution, along with cross-platform compatibility. The open-source implementation provides a reliable, extensible foundation for UR robot research and deployment in ROS 2 environments.

This work addresses the tight coupling between reference signal processing and control law implementation in ROS 2 controllers, which leads to code redundancy and poor reusability. To resolve this, the authors propose a modular architecture that decouples reference generation logic from the controller for the first time in ROS 2, introducing a dedicated Reference Generator component. This component uniformly handles reference acquisition, validation, and interpolation in both joint and Cartesian spaces, and integrates seamlessly with downstream controllers via the ros2_control chainable controller mechanism. Leveraging this architecture, several novel controllers—including PD with gravity compensation, Cartesian pose, and admittance controllers—were developed. Experimental validation on Universal Robots and Franka Emika manipulators demonstrates stable and reliable reference tracking, significantly reduced code duplication, and enhanced controller reusability and development efficiency.

To address the lack of unified, flexible, and real-time inverse dynamics (ID) computation across simulation and real-robot deployments, this paper introduces a lightweight, robot-agnostic ID software library built natively for ROS 2. Methodologically, it employs an abstract interface layer to decouple underlying dynamics engines (KDL/Pinocchio) and hardware specifics, integrates DDS natively for deterministic real-time communication, and supports URDF parsing and cross-platform deployment. Its key contributions include: (i) the first ROS 2-native, extensible ID module architecture enabling seamless integration across simulation and physical robots (UR10, Franka), and (ii) experimental validation demonstrating sub-millisecond latency, high computational accuracy, and robust runtime stability. The implementation is open-source and officially integrated into the ROS 2 GBP ecosystem.

This work proposes multipanda_ros2, an open-source multi-arm control framework built on ROS 2 to address the challenges of control accuracy, real-time performance, and dynamic consistency in sim-to-real transfer for multi-manipulator systems. The framework enables single-process real-time control of an arbitrary number of Franka arms, integrates high-fidelity MuJoCo simulation, and enhances force/torque accuracy through inertial parameter identification. It introduces a novel controllet-feature design pattern that achieves controller switching latency of ≤2 ms and extends soft robotics methodologies to rigid dual-arm contact tasks, establishing quantitative metrics to bridge the sim-to-real gap. Experimental results demonstrate stable 1 kHz torque control and significantly improved consistency between simulation and physical execution, offering a reproducible, high-fidelity platform for complex multi-arm cooperative tasks.

The Fanuc CRX-series robots lack an open-source, standards-compliant ROS 2 hardware interface. Method: This paper designs and implements a real-time hardware interface compliant with the ROS 2 Control framework, built upon the R-30iB Plus controller’s communication protocol and integrating an EtherNet/IP/Fieldbus adaptation layer. It supports closed-loop feedback, motion control, trajectory tracking, collision avoidance, and dynamic velocity scaling, and is tightly coupled with MoveIt 2 for high-level motion planning. Contribution/Results: To our knowledge, this is the first modular, open-source ROS 2 hardware interface for the CRX series. It is validated across four representative industrial tasks: command response latency remains stable and bounded; trajectory tracking error stays below joint resolution while respecting velocity constraints; and collision avoidance responses are robust and deterministic. The complete implementation is publicly released under an open-source license, establishing a reusable integration blueprint for industrial robots within the ROS 2 ecosystem.

This study addresses the challenge of simultaneously achieving spatial abstraction, temporal predictability, and state continuity in ROS 2 middleware operating within dynamic, resource-constrained wireless environments. For the first time, it introduces a three-dimensional “space–time–state” analytical framework, integrating architectural analysis, formal modeling, and a comprehensive literature review to systematically investigate the underlying mechanisms and structural trade-offs of ROS 2 middleware—particularly DDS and Zenoh—in discovery protocols, data exchange, and state management. The work uncovers critical performance bottlenecks in existing approaches concerning modular deployment, real-time control, and disconnected operation recovery. These insights lay a theoretical foundation and offer concrete design guidelines for developing robust, scalable next-generation robotic middleware.

This work addresses the limited generalizability and transferability of current foundation models in robotics, which often require custom integration of perception, actuation, and safety mechanisms. To overcome this, the authors propose ROSClaw—a model-agnostic execution layer that enables plug-and-play deployment of arbitrary foundation models on any ROS 2 robot by integrating the OpenClaw agent runtime with ROS 2. Key innovations include standardized capability discovery, multimodal observation normalization, action validation within configurable safety bounds, and structured audit logging. Experiments across three robotic platforms and four foundation models demonstrate up to a 4.8× difference in non-policy action proposal rates and show that the proposed execution layer significantly improves task success rates and safety across diverse frameworks.

This work proposes a lightweight and scalable multi-robot orchestration framework based on ROS 2 to address the challenges of flexible configuration, rapid reconfiguration, and efficient coordination in high-mix, low-volume manufacturing environments. The framework encapsulates robot functionalities as deployable skills and leverages Compute Continuum principles to automatically construct isolated execution units, dynamically instantiate skill deployments, and enable resource-aware communication coordination. Experimental results demonstrate that the system significantly reduces CPU, memory, and network overhead in idle states, outperforming K3s-based solutions in energy efficiency and overall performance, thereby making it well-suited for large-scale edge deployment scenarios.