Launch Files

Overview

The sn4_bringup package contains ROS 2 launch files that orchestrate the startup of the entire FEB autonomous racing system. Launch files are organized hierarchically to enable modular testing and deployment of individual subsystems or the complete system.

Launch File Hierarchy

The launch system follows a hierarchical structure:

full_launch.py (Complete System)
├── microcontroller.py
├── perception.py
│   ├── camera.py
│   └── lidar.py
├── localization.py
└── pnc.py

Launch Files Reference

full_launch.py

Purpose: Master launch file that brings up the complete autonomous racing system.

Description:

Launches all subsystems required for autonomous operation:

• Microcontroller communication

• Perception (cameras and LiDAR)

• Localization (SLAM)

• Planning and Control (PnC)

Subsystems Included:

Launch File	Description
microcontroller.py	Dual microcontroller interface
perception.py	Complete perception system
localization.py	GraphSLAM localization
pnc.py	Planning and control stack

Usage:

ros2 launch sn4_bringup full_launch.py

When to Use:

• Full system testing on the vehicle

• Competition runs

• Complete end-to-end validation

Source:

from launch import LaunchDescription
from launch.actions import IncludeLaunchDescription
from launch.launch_description_sources import PythonLaunchDescriptionSource
from ament_index_python.packages import get_package_share_directory
import os

def generate_launch_description():
    launch_dir = os.path.join(
        get_package_share_directory('racecar_bringup'), 'launch'
    )

    microcontroller_launch = IncludeLaunchDescription(
        PythonLaunchDescriptionSource(os.path.join(launch_dir, 'microcontroller.py'))
    )

    perception_launch = IncludeLaunchDescription(
        PythonLaunchDescriptionSource(os.path.join(launch_dir, 'perception.py'))
    )

    localization_launch = IncludeLaunchDescription(
        PythonLaunchDescriptionSource(os.path.join(launch_dir, 'localization.py'))
    )

    pnc_launch = IncludeLaunchDescription(
        PythonLaunchDescriptionSource(os.path.join(launch_dir, 'pnc.py'))
    )

    return LaunchDescription([
        microcontroller_launch,
        perception_launch,
        localization_launch,
        pnc_launch
    ])

—

perception.py

Purpose: Master perception launch file that starts both camera and LiDAR perception.

Description:

Orchestrates the complete perception subsystem by including both camera and LiDAR launch files.

Subsystems Included:

Launch File	Description
camera.py	Dual RealSense camera setup
lidar.py	RSLiDAR sensor

Usage:

ros2 launch sn4_bringup perception.py

When to Use:

• Testing complete perception system

• Sensor data collection

• Perception algorithm development

Source:

from launch import LaunchDescription
from launch.actions import IncludeLaunchDescription
from launch.launch_description_sources import PythonLaunchDescriptionSource
from ament_index_python.packages import get_package_share_directory
import os

def generate_launch_description():
    """
    Master perception launch file.

    Launches both camera and LiDAR perception subsystems:
    - camera.py: Dual RealSense camera setup
    - lidar.py: RSLiDAR sensor
    """
    launch_dir = os.path.join(get_package_share_directory('sn4_bringup'), 'launch')

    camera_launch = IncludeLaunchDescription(
        PythonLaunchDescriptionSource(os.path.join(launch_dir, 'camera.py'))
    )

    lidar_launch = IncludeLaunchDescription(
        PythonLaunchDescriptionSource(os.path.join(launch_dir, 'lidar.py'))
    )

    return LaunchDescription([
        camera_launch,
        lidar_launch,
    ])

—

camera.py

Purpose: Launch dual Intel RealSense depth cameras for vision-based cone detection.

Description:

Starts two RealSense camera nodes with hardware-specific serial numbers and configurations:

• D435i (Left Camera): Includes IMU, mounted upside down - Serial: 344422072170 - Resolution: 1280x720 @ 30 FPS - Features: RGB + aligned depth + IMU

• D435 (Right Camera): Standard mounting - Serial: 042222071145 - Features: RGB + aligned depth

Published Topics:

Topic	Description
/camera/realsense_imu/color/image_raw	Left camera RGB image
/camera/realsense_imu/aligned_depth_to_color/image_raw	Left camera aligned depth
/camera/realsense2/color/image_raw	Right camera RGB image
/camera/realsense2/aligned_depth_to_color/image_raw	Right camera aligned depth

Configuration:

Both cameras use:

• Color enabled: Yes

• Depth enabled: Yes

• Depth alignment: Enabled (aligned to color frame)

• Profile: 1280x720 @ 30 FPS

Usage:

ros2 launch sn4_bringup camera.py

When to Use:

• Testing camera perception only

• Camera calibration

• Vision algorithm development

—

lidar.py

Purpose: Launch RSLiDAR sensor for point cloud acquisition.

Description:

Starts the RSLiDAR SDK node for LiDAR point cloud streaming. Includes optional RViz2 visualization (commented out by default).

Published Topics:

Topic	Description
/rslidar_points	Raw LiDAR point cloud (PointCloud2)

Configuration:

• Namespace: rslidar_sdk

• Output: Screen (for debugging)

Usage:

ros2 launch sn4_bringup lidar.py

When to Use:

• Testing LiDAR perception only

• Ground plane calibration

• Point cloud visualization

—

localization.py

Purpose: Launch localization and perception fusion for SLAM.

Description:

Starts the GraphSLAM node for vehicle localization and map building, along with the dual camera perception node for early-stage sensor fusion.

Nodes Launched:

Package	Executable	Purpose
graphslam_global	graphslam_global	SLAM and mapping
early_stage_fusion	dual_realsense	Camera+LiDAR fusion

Published Topics:

• /slam/state - Vehicle state estimate

• /slam/map - Track map with cone boundaries

Usage:

ros2 launch sn4_bringup localization.py

When to Use:

• SLAM algorithm testing

• Map building

• Localization debugging

—

pnc.py (Planning and Control)

Purpose: Launch the complete planning and control stack.

Description:

Starts all planning and control nodes required for autonomous navigation:

Nodes Launched:

Package	Executable	Purpose
global_path	global_path	Global racing line planning
local_path	local_path	Local dynamic path planning
mpc	mpc	Model Predictive Control

Typical Data Flow:

1. Global path planner receives track map from SLAM

2. Generates optimal racing line

3. Local path planner adjusts for dynamic obstacles

4. MPC controller tracks the reference trajectory

Usage:

ros2 launch sn4_bringup pnc.py

When to Use:

• Planning algorithm development

• Control tuning

• Path planning testing without full system

—

microcontroller.py

Purpose: Launch dual microcontroller interface for vehicle control.

Description:

Starts the microcontroller communication node that interfaces with the vehicle’s low-level control systems.

Nodes Launched:

Package	Executable	Purpose
microcontroller	dual_mcu	Dual MCU communication

Published Topics:

• Vehicle state feedback

• Sensor data from MCU

Subscribed Topics:

• Control commands (steering, throttle, brake)

Usage:

ros2 launch sn4_bringup microcontroller.py

When to Use:

• Testing vehicle interface

• Low-level control debugging

• Hardware-in-the-loop testing

—

all_sensors.py

Purpose: Launch minimal sensor suite (microcontroller + perception).

Description:

Lightweight launch file for sensor data collection without planning/control. Useful for data logging and sensor validation.

Subsystems Included:

Launch File	Description
microcontroller.py	Vehicle interface
perception.py	Cameras and LiDAR

Usage:

ros2 launch sn4_bringup all_sensors.py

When to Use:

• Sensor data collection

• Bag recording sessions

• Sensor calibration and validation

—

p131_sim.py (Simulation)

Purpose: Launch configuration for simulation testing.

Description:

Starts planning, control, and SLAM nodes for simulation environments. Excludes hardware drivers (cameras, LiDAR, microcontroller).

Nodes Launched:

Package	Executable	Purpose
mpc	mpc	Model Predictive Control
global_path	global_path	Global path planning
local_path	local_path	Local path planning
graphslam_global	graphslam_global	SLAM (using simulated data)

Usage:

ros2 launch sn4_bringup p131_sim.py

When to Use:

• Algorithm testing in simulation (Gazebo, EUFS sim)

• Safe testing without hardware

• Development without vehicle access

Launch File Best Practices

Testing Individual Subsystems:

Test components individually before running the full system:

# Test cameras only
ros2 launch sn4_bringup camera.py

# Test LiDAR only
ros2 launch sn4_bringup lidar.py

# Test perception (cameras + LiDAR)
ros2 launch sn4_bringup perception.py

# Test full system
ros2 launch sn4_bringup full_launch.py

Common Launch Workflows:

1. Hardware Bring-up:

   # Step 1: Verify sensors
   ros2 launch sn4_bringup all_sensors.py
   
   # Step 2: Add localization
   ros2 launch sn4_bringup localization.py
   
   # Step 3: Full system
   ros2 launch sn4_bringup full_launch.py
   

2. Algorithm Development (Simulation):

   # Use simulation launch
   ros2 launch sn4_bringup p131_sim.py
   

3. Sensor Calibration:

   # Cameras
   ros2 launch sn4_bringup camera.py
   
   # LiDAR ground plane
   ros2 launch sn4_bringup lidar.py
   

Troubleshooting

Launch File Not Found:

Ensure package is built and sourced:

cd ~/feb-system-integration
colcon build --packages-select sn4_bringup
source install/setup.bash

Camera Serial Number Issues:

If cameras fail to start, verify serial numbers:

rs-enumerate-devices | grep Serial

Update camera.py with correct serial numbers if hardware changed.

Node Launch Failures:

Check individual node status:

ros2 node list
ros2 node info /node_name

View logs for specific nodes:

ros2 launch sn4_bringup <launch_file> --show-args