/ros1

name: ros1
description: >
  Best practices, design patterns, and common pitfalls for ROS1 (Robot Operating System 1) development.
  Use this skill when building ROS1 nodes, packages, launch files, or debugging ROS1 systems. Trigger
  whenever the user mentions ROS1, catkin, rospy, roscpp, roslaunch, roscore, rostopic, tf, actionlib,
  message types, services, or any ROS1-era robotics middleware. Also trigger for migrating ROS1 code
  to ROS2, maintaining legacy ROS1 systems, or building ROS1-ROS2 bridges. Covers catkin workspaces,
  nodelets, dynamic reconfigure, pluginlib, and the full ROS1 ecosystem.

ROS1 Development Skill

When to Use This Skill

• Building or maintaining ROS1 packages and nodes
• Writing launch files, message types, or services
• Debugging ROS1 communication (topics, services, actions)
• Configuring catkin workspaces and build systems
• Working with tf/tf2 transforms, URDF, or robot models
• Using actionlib for long-running tasks
• Optimizing nodelets for zero-copy transport
• Planning ROS1 → ROS2 migration

Core Architecture Principles

1. Node Design

**Single Responsibility Nodes**: Each node should do ONE thing well. Resist the temptation to build monolithic "do-everything" nodes.

# BAD: Monolithic node
class RobotNode:
    def __init__(self):
        self.sub_camera = rospy.Subscriber('/camera/image', Image, self.camera_cb)
        self.sub_lidar = rospy.Subscriber('/lidar/points', PointCloud2, self.lidar_cb)
        self.pub_cmd = rospy.Publisher('/cmd_vel', Twist, queue_size=10)
        self.pub_map = rospy.Publisher('/map', OccupancyGrid, queue_size=1)
        # This node does perception, planning, AND control

# GOOD: Decomposed nodes
class PerceptionNode:    # Fuses sensor data → publishes /obstacles
class PlannerNode:       # Subscribes /obstacles → publishes /path
class ControllerNode:    # Subscribes /path → publishes /cmd_vel

**Node Initialization Pattern**:

#!/usr/bin/env python
import rospy
from std_msgs.msg import String

class MyNode:
    def __init__(self):
        rospy.init_node('my_node', anonymous=False)

        # 1. Load parameters FIRST
        self.rate = rospy.get_param('~rate', 10.0)
        self.frame_id = rospy.get_param('~frame_id', 'base_link')

        # 2. Set up publishers BEFORE subscribers
        #    (prevents callbacks firing before publisher is ready)
        self.pub = rospy.Publisher('~output', String, queue_size=10)

        # 3. Set up subscribers LAST
        self.sub = rospy.Subscriber('~input', String, self.callback)

        rospy.loginfo(f"[{rospy.get_name()}] Initialized with rate={self.rate}")

    def callback(self, msg):
        # Process and republish
        result = String(data=msg.data.upper())
        self.pub.publish(result)

    def run(self):
        rate = rospy.Rate(self.rate)
        while not rospy.is_shutdown():
            # Periodic work here
            rate.sleep()

if __name__ == '__main__':
    try:
        node = MyNode()
        node.run()
    except rospy.ROSInterruptException:
        pass

2. Topic Design

**Naming Conventions**:

/robot_name/sensor_type/data_type

# Examples:
/ur5/joint_states              # Robot joint states
/realsense/color/image_raw     # Camera color image
/realsense/depth/points        # Depth point cloud
/mobile_base/cmd_vel           # Velocity commands
/gripper/command               # Gripper commands

**Queue Sizes Matter**:

# For sensor data (high frequency, OK to drop old messages):
rospy.Subscriber('/camera/image', Image, self.cb, queue_size=1)

# For commands (don't want to miss any):
rospy.Publisher('/cmd_vel', Twist, queue_size=10)

# For large data (point clouds, images) - use small queues to prevent memory bloat:
rospy.Subscriber('/lidar/points', PointCloud2, self.cb, queue_size=1)

# NEVER use queue_size=0 (infinite) for high-frequency topics
# This WILL cause memory leaks under load

**Latched Topics** for data that changes infrequently:

# Robot description, static maps, calibration data
pub = rospy.Publisher('/robot_description', String, queue_size=1, latch=True)

3. Launch File Best Practices

<launch>
  <!-- ALWAYS use args for configurability -->
  <arg name="robot_name" default="ur5"/>
  <arg name="sim" default="false"/>
  <arg name="debug" default="false"/>

  <!-- Group by subsystem with namespaces -->
  <group ns="$(arg robot_name)">

    <!-- Conditional loading based on sim vs real -->
    <group if="$(arg sim)">
      <include file="$(find my_pkg)/launch/sim_drivers.launch"/>
    </group>
    <group unless="$(arg sim)">
      <include file="$(find my_pkg)/launch/real_drivers.launch"/>
    </group>

    <!-- Node with proper remapping -->
    <node pkg="my_pkg" type="perception_node.py" name="perception"
          output="screen" respawn="true" respawn_delay="5">
      <param name="rate" value="30.0"/>
      <param name="frame_id" value="$(arg robot_name)_base_link"/>
      <remap from="~input_image" to="/$(arg robot_name)/camera/image_raw"/>
      <remap from="~output_detections" to="detections"/>
      <!-- Load a YAML param file -->
      <rosparam file="$(find my_pkg)/config/perception.yaml" command="load"/>
    </node>

  </group>

  <!-- Debug tools (conditionally loaded) -->
  <group if="$(arg debug)">
    <node pkg="rviz" type="rviz" name="rviz"
          args="-d $(find my_pkg)/rviz/debug.rviz"/>
    <node pkg="rqt_graph" type="rqt_graph" name="rqt_graph"/>
  </group>
</launch>

4. TF Transform Tree

**Rules**:

• Every frame has EXACTLY one parent (tree, not graph)
• Static transforms use `static_transform_publisher`
• Dynamic transforms publish at consistent rates
• ALWAYS set timestamps correctly

import tf2_ros

# Publishing transforms
br = tf2_ros.TransformBroadcaster()
t = TransformStamped()
t.header.stamp = rospy.Time.now()  # CRITICAL: Use current time
t.header.frame_id = "odom"
t.child_frame_id = "base_link"
t