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.transform.translation.x = x t.transform.translation.y = y t.transform.rotation = quaternion_from_euler( 0 , 0 , theta) br.sendTransform(t) # Listening for transforms (with timeout and exception handling) tf_buffer = tf2_ros.Buffer() listener = tf2_ros.TransformListener(tf_buffer) try : trans = tf_buffer.lookup_transform( 'map' , 'base_link' , rospy.Time( 0 ), # Get latest available rospy.Duration( 1.0 ) # Wait up to 1 second ) except (tf2_ros.LookupException, tf2_ros.ConnectivityException, tf2_ros.ExtrapolationException) as e: rospy.logwarn( f"TF lookup failed: {e} " ) 5. Actionlib for Long-Running Tasks import actionlib from my_msgs.msg import PickPlaceAction, PickPlaceGoal, PickPlaceResult # Server class PickPlaceServer : def __init__ ( self ): self .server = actionlib.SimpleActionServer( 'pick_place' , PickPlaceAction, execute_cb= self .execute, auto_start= False # ALWAYS set auto_start=False ) self .server.start() def execute ( self, goal ): feedback = PickPlaceFeedback() # Check for preemption INSIDE your loop for step in self .plan_steps(goal): if self .server.is_preempt_requested(): self .server.set_preempted() return self .execute_step(step) feedback.progress = step.progress self .server.publish_feedback(feedback) result = PickPlaceResult(success= True ) self .server.set_succeeded(result) Common Pitfalls & Failure Modes Time Synchronization # BAD: Comparing timestamps from different clocks if camera_msg.header.stamp == lidar_msg.header.stamp: # Almost never true # GOOD: Use message_filters for approximate time sync import message_filters sub_cam = message_filters.Subscriber( '/camera/image' , Image) sub_lidar = message_filters.Subscriber( '/lidar/points' , PointCloud2) sync = message_filters.ApproximateTimeSynchronizer( [sub_cam, sub_lidar], queue_size= 10 , slop= 0.05 # 50ms tolerance ) sync.registerCallback( self .synced_callback) Callback Threading # ROS1 uses a single-threaded spinner by default. # Long-running callbacks BLOCK all other callbacks. # BAD: def callback ( self, msg ): result = self .expensive_computation(msg) # Blocks for 2 seconds! self .pub.publish(result) # GOOD: Use a MultiThreadedSpinner or process in a separate thread rospy.init_node( 'my_node' ) # ... setup ... spinner = rospy.MultiThreadedSpinner(num_threads= 4 ) spinner.spin() # Or use a processing thread: import threading, queue class MyNode : def __init__ ( self ): self .work_queue = queue.Queue(maxsize= 1 ) self .worker = threading.Thread(target= self ._process_loop, daemon= True ) self .worker.start() def callback ( self, msg ): try : self .work_queue.put_nowait(msg) # Non-blocking except queue.Full: pass # Drop old data def _process_loop ( self ): while not rospy.is_shutdown(): msg = self .work_queue.get() result = self .expensive_computation(msg) self .pub.publish(result) Parameter Server Anti-Patterns # BAD: Hardcoded values self .threshold = 0.5 # BAD: Global params without namespace self .threshold = rospy.get_param( 'threshold' , 0.5 ) # Collides across nodes # GOOD: Private params with defaults self .threshold = rospy.get_param( '~threshold' , 0.5 ) # GOOD: Dynamic reconfigure for runtime tuning from dynamic_reconfigure.server import Server from my_pkg.cfg import MyNodeConfig self .dyn_server = Server(MyNodeConfig, self .dyn_callback) Nodelets for Zero-Copy Transport When nodes exchange large data (images, point clouds) within the same process, nodelets eliminate serialization overhead: // my_nodelet.h # include <nodelet/nodelet.h> # include <pluginlib/class_list_macros.h> class MyNodelet : public nodelet::Nodelet { virtual void onInit () { ros::NodeHandle& nh = getNodeHandle (); ros::NodeHandle& pnh = getPrivateNodeHandle (); // Use shared_ptr for zero-copy: pass pointers, not copies pub_ = nh. advertise <sensor_msgs::Image>( "output" , 1 ); sub_ = nh. subscribe ( "input" , 1 , &MyNodelet::callback, this ); } }; PLUGINLIB_EXPORT_CLASS (MyNodelet, nodelet::Nodelet) Package Structure my_robot_pkg/ ├── CMakeLists.txt ├── package.xml ├── setup.py # For Python packages ├── config/ │ ├── robot_params.yaml # Default parameters │ └── dynamic_reconfigure/ # .cfg files ├── launch/ │ ├── robot.launch # Top-level launcher │ ├── drivers.launch # Hardware drivers │ └── perception.launch # Perception pipeline ├── msg/ # Custom message definitions │ └── Detection.msg ├── srv/ # Service definitions │ └── GetPose.srv ├── action/ # Action definitions │ └── PickPlace.action ├── src/ # C++ source │ └── my_node.cpp ├── scripts/ # Python nodes (executable) │ └── perception_node.py ├── include/my_robot_pkg/ # C++ headers │ └── my_node.h ├── rviz/ # RViz configs │ └── debug.rviz ├── urdf/ # Robot model │ └── robot.urdf.xacro └── test/ # Unit and integration tests ├── test_perception.py └── test_perception.test # rostest launch file Debugging Toolkit # Essential diagnostic commands rostopic list # See all active topics rostopic hz /camera/image_raw # Check publish rate rostopic bw /lidar/points # Check bandwidth rostopic echo /joint_states -n 1 # Inspect one message rosnode list # Active nodes rosnode info /perception # Connections and subscriptions roswtf # Automated diagnostics rqt_graph # Visual node/topic graph rqt_console # Log viewer with filtering # TF debugging rosrun tf tf_monitor # Monitor TF tree health rosrun tf view_frames # Generate TF tree PDF rosrun tf tf_echo map base_link # Print transform continuously # Bag file operations rosbag record -a # Record everything (careful with disk!) rosbag record /camera/image /tf # Record specific topics rosbag info recording.bag # Inspect bag contents rosbag play recording.bag --clock # Playback with simulated time ROS1 → ROS2 Migration Checklist When planning a migration, note these key differences: rospy → rclpy , roscpp → rclcpp catkin_make → colcon build roslaunch XML → ROS2 Python launch files Global parameter server → Per-node parameters rospy.Rate → node.create_timer() Single roscore → DDS discovery (no central master) message_filters works in both, but API differs Custom messages: same .msg format, different build system Nodelets → ROS2 Components (intra-process communication) dynamic_reconfigure → ROS2 parameters with callbacks Start migration from leaf nodes (sensors, actuators) and work inward. Use the ros1_bridge package to run both stacks simultaneously during transition.