Migrating From ROS1 Combined Robot HW To ROS2 For Synchronized Multi-Arm Control

Jul 31, 2025 by Axel Sørensen 81 views

Migrating from ROS1 Combined Robot HW to ROS2: A Comprehensive Guide for Synchronized Multi-Arm Control

Hey everyone! Are you grappling with the transition from ROS1's combined_robot_hw to ROS2, especially when dealing with multiple robot arms that need synchronized control? You're not alone! Many developers face this challenge when moving to ROS2, and the good news is, there are definitely ways to achieve this. Let's dive into how we can set up your dual-arm system in ROS2 to ensure simultaneous read/write operations, making your robots work together seamlessly.

Understanding the Challenge: Synchronizing Multi-Arm Systems in ROS2

When dealing with multi-arm robots, the core challenge lies in ensuring that the control commands are executed simultaneously across all arms. This synchronization is critical for coordinated tasks, such as assembly, material handling, or any application where the arms need to work in tandem. In ROS1, the combined_robot_hw package provided a convenient way to manage multiple hardware interfaces within a single process, simplifying the synchronization problem. However, ROS2 takes a more modular and distributed approach, which means we need to explore new strategies to achieve the same level of synchronization.

One of the key differences in ROS2 is the emphasis on real-time performance and deterministic behavior. This is achieved through the use of DDS (Data Distribution Service) as the underlying communication middleware, which allows for fine-grained control over data flow and timing. However, this also means that the traditional ROS1 methods of shared memory and direct access to hardware interfaces are no longer the primary approach. Instead, we need to leverage ROS2's communication primitives and control architecture to build a synchronized system.

To effectively synchronize multiple robot arms in ROS2, we need to consider several factors. First, the hardware interfaces for each arm need to be properly defined and exposed to the ROS2 control system. This typically involves creating custom hardware interfaces that inherit from the rclcpp::HardwareInterface class and implement the necessary read and write functions. Second, we need to ensure that the control loop is executed at a consistent rate and that the control commands are distributed to the arms with minimal latency. This can be achieved by using ROS2's real-time capabilities and carefully designing the communication architecture. Finally, we need to monitor the system's performance and ensure that the synchronization is maintained under various operating conditions. This may involve using diagnostic tools and logging mechanisms to track the timing of the control loop and the communication latency.

Diving into Solutions: Approaches to Synchronized Control in ROS2

So, how do we replicate the functionality of combined_robot_hw in ROS2? Here's a breakdown of the common strategies:

1. Multi-Interface Hardware Components

One approach is to create a single hardware component that manages multiple robot arm interfaces. Think of it as a unified control hub for all your arms. This component would encapsulate the read and write operations for each arm, ensuring that they happen within the same process and, therefore, are synchronized. This approach provides a centralized point of control and can simplify the overall system architecture. The hardware component can be implemented as a ROS2 node that exposes services or actions for controlling the robot arms. The services or actions can be used to send joint commands, plan trajectories, or execute other control tasks. The hardware component can also publish sensor data and status information from the robot arms, allowing other ROS2 nodes to monitor the system's performance. However, this method requires careful design to avoid performance bottlenecks and ensure that the component can handle the combined load of all arms.

The key to this approach is to ensure that the read and write operations for each arm are executed in a non-blocking manner and that the component can handle the combined data flow from all arms. This may involve using multi-threading or asynchronous programming techniques to improve performance. Additionally, the component should be designed to handle errors and exceptions gracefully, ensuring that the system remains stable even if one of the arms encounters a problem.

2. Centralized Controller with DDS Synchronization

Another strategy involves using a centralized controller node that communicates with individual hardware interfaces for each arm via DDS. In this setup, the controller node acts as the brain, sending commands to each arm and receiving feedback. DDS, being the backbone of ROS2 communication, provides mechanisms for ensuring timely and reliable data delivery, which is crucial for synchronization. This approach allows for a more modular design, where each arm can be controlled independently, but the centralized controller ensures that the commands are coordinated. The controller node can implement advanced control algorithms, such as trajectory planning and force control, and can also incorporate sensor feedback to improve performance. However, this method requires careful configuration of DDS to ensure that the communication latency is minimized and that the data is delivered in a timely manner.

The controller node can use ROS2's real-time capabilities to ensure that the control loop is executed at a consistent rate. This may involve setting the DDS quality of service (QoS) parameters to prioritize the control data and minimize latency. Additionally, the controller node can use DDS features such as data filtering and content-based routing to reduce the amount of data that needs to be processed. The individual hardware interfaces for each arm can be implemented as ROS2 nodes that expose services or actions for receiving commands from the controller. These nodes can also publish sensor data and status information from the robot arms, allowing the controller to monitor the system's performance.

3. Distributed Control with Time Synchronization

For more advanced setups, consider a distributed control architecture where each arm has its own controller, but they synchronize their actions using a time synchronization protocol, such as PTP (Precision Time Protocol). This approach is particularly useful for systems where the arms are physically separated or have different hardware requirements. The key to this approach is to ensure that all controllers have a common understanding of time, which allows them to coordinate their actions even if they are not directly communicating. This can be achieved by using a time synchronization protocol such as PTP, which provides a high-precision clock synchronization mechanism. The distributed controllers can communicate with each other using DDS, allowing them to exchange information and coordinate their actions.

This approach offers high scalability and flexibility, but it also introduces challenges related to time synchronization and fault tolerance. The time synchronization protocol needs to be carefully configured to ensure that the clocks are synchronized with sufficient accuracy. Additionally, the system needs to be designed to handle failures in one of the controllers or communication links. The distributed controllers can use fault-tolerant communication protocols and redundancy mechanisms to improve the system's robustness. Each controller can monitor the status of the other controllers and take corrective action if a failure is detected.

Practical Steps: Implementing Synchronized Control

Let's break down the steps to implement a synchronized multi-arm system in ROS2:

Define Hardware Interfaces: Create custom hardware interfaces for each robot arm. These interfaces should inherit from rclcpp::HardwareInterface and implement the read() and write() methods. This is where you'll interact with the actual hardware drivers.
Choose a Synchronization Strategy: Decide on the best approach for your system (multi-interface component, centralized controller, or distributed control). Consider factors like complexity, performance requirements, and scalability.
Implement the Control Logic: Develop the control algorithms that will govern the movement of your arms. This could involve trajectory planning, inverse kinematics, force control, or other techniques. Your control logic should take into account the synchronization requirements of your application.
Configure DDS: Fine-tune DDS settings (QoS profiles, data types, etc.) to ensure timely and reliable communication between components. This is crucial for minimizing latency and maximizing synchronization.
Test and Tune: Thoroughly test your system and tune the control parameters to achieve the desired performance. Use ROS2's diagnostic tools to monitor the system's behavior and identify potential bottlenecks.

Code Snippets and Examples

While a full code example is beyond the scope of this article, let's look at some snippets to illustrate key concepts. Imagine we're implementing a multi-interface hardware component:

#include "rclcpp/rclcpp.hpp"
#include "rclcpp/hardware_interface.hpp"
#include <vector>
#include <string>

class MultiArmHardware : public rclcpp::HardwareInterface {
public:
  rclcpp_lifecycle::node_interfaces::LifecycleNodeInterface::CallbackReturn on_init(const rclcpp_lifecycle::State &) override {
    // Initialize hardware interfaces for each arm
    return rclcpp_lifecycle::node_interfaces::LifecycleNodeInterface::CallbackReturn::SUCCESS;
  }

  std::vector<rclcpp::hardware_interface::StateInterface> export_state_interfaces() override {
    std::vector<rclcpp::hardware_interface::StateInterface> state_interfaces;
    // Export state interfaces for each joint in each arm
    return state_interfaces;
  }

  std::vector<rclcpp::hardware_interface::CommandInterface> export_command_interfaces() override {
    std::vector<rclcpp::hardware_interface::CommandInterface> command_interfaces;
    // Export command interfaces for each joint in each arm
    return command_interfaces;
  }

  rclcpp::hardware_interface::return_type read(const rclcpp::Time & time, const rclcpp::Duration & period) override {
    // Read joint states from each arm
    return rclcpp::hardware_interface::return_type::OK;
  }

  rclcpp::hardware_interface::return_type write(const rclcpp::Time & time, const rclcpp::Duration & period) override {
    // Write joint commands to each arm
    return rclcpp::hardware_interface::return_type::OK;
  }

private:
  // Data structures to hold joint states and commands for each arm
};

#include "rclcpp_components/register_node_macro.hpp"

RCLCPP_COMPONENTS_REGISTER_NODE(MultiArmHardware)

This snippet shows the basic structure of a hardware component in ROS2. You'll need to fill in the details for your specific robot arms, including the joint names, state interfaces, and command interfaces. The read() and write() methods are where you'll interact with the hardware drivers to read joint states and send commands. Remember to handle the synchronization logic within these methods to ensure that the arms move together as intended.

Resources and Further Reading

To deepen your understanding, check out these resources:

ROS2 Control Documentation: This is your go-to resource for everything related to control in ROS2.
ROS2 DDS Configuration: Learn how to fine-tune DDS for real-time performance.
ROS2 Hardware Interface Tutorial: Get hands-on experience with creating hardware interfaces.
ROS2 Multi-Robot Systems: Explore advanced topics in multi-robot coordination.

Conclusion: Embracing the ROS2 Way for Multi-Arm Synchronization

While the transition from ROS1's combined_robot_hw to ROS2 requires a shift in thinking, the modularity and real-time capabilities of ROS2 offer powerful tools for building synchronized multi-arm systems. By carefully designing your hardware interfaces, choosing the right synchronization strategy, and leveraging DDS, you can achieve precise and coordinated control of your robots. So, roll up your sleeves, dive into the code, and let's get those arms working together! Remember, the ROS2 community is here to help, so don't hesitate to ask questions and share your experiences.

Now, let’s tackle those keywords and ensure this article is optimized for search engines and, more importantly, for you, the reader!