saltylab-firmware/jetson/ros2_ws/src/saltybot_bringup/SENSORS.md

saltybot_bringup — Sensor Topic Reference

ROS2 Humble | ROS_DOMAIN_ID=42 | DDS: CycloneDDS

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rosbridge WebSocket (web dashboard)

The web dashboard connects to ROS2 topics via rosbridge WebSocket on port 9090.

# Start rosbridge (and compressed camera republishers):
ros2 launch saltybot_bringup rosbridge.launch.py

# Or via docker-compose:
docker compose up -d rosbridge

Browser connection (roslibjs):

var ros = new ROSLIB.Ros({ url: 'ws://jetson.local:9090' });
ros.on('connection', () => console.log('connected'));
ros.on('error',      (e) => console.error('error', e));
ros.on('close',      () => console.log('disconnected'));

Whitelisted topics (configured in config/rosbridge_params.yaml):

Topic	Type	Notes
/map	nav_msgs/OccupancyGrid	Use throttle_rate: 5000 (0.2 Hz)
/scan	sensor_msgs/LaserScan	5.5 Hz, 1440 pts
/tf	tf2_msgs/TFMessage	Use throttle_rate: 100 (10 Hz)
/tf_static	tf2_msgs/TFMessage	One-shot on connect
/saltybot/imu	sensor_msgs/Imu	50 Hz, pitch/roll/yaw
/saltybot/balance_state	std_msgs/String	JSON balance controller state
/cmd_vel	geometry_msgs/Twist	Subscribe to monitor Nav2 commands
/person/target	(custom)	Person tracking target
/person/detections	(custom)	Person detection results
/camera/front/image_raw/compressed	sensor_msgs/CompressedImage	JPEG 75%, 640×480
/camera/left/image_raw/compressed	sensor_msgs/CompressedImage	JPEG 75%, 640×480
/camera/rear/image_raw/compressed	sensor_msgs/CompressedImage	JPEG 75%, 640×480
/camera/right/image_raw/compressed	sensor_msgs/CompressedImage	JPEG 75%, 640×480

Bandwidth tips:

• Raw 640×480 YUYV = ~900 KB/frame. rosbridge republishes JPEG-compressed ≈ 15–25 KB/frame.
• Always use throttle_rate for cameras in roslibjs (e.g. throttle_rate: 200 = max 5 fps).
• /map is large (~100 KB); use throttle_rate: 5000 or subscribe only on demand.

Verify connection:

# Check WebSocket is listening
ss -tlnp | grep 9090

# List topics visible to rosbridge
ros2 topic list | grep -E 'map|scan|imu|camera|person|cmd_vel'

---

Build & Run

# From inside the container (or ros2_ws root on host after sourcing ROS2):
cd /ros2_ws
colcon build --packages-select saltybot_bringup --symlink-install
source install/local_setup.bash

# Sensors only (verify data before SLAM):
ros2 launch saltybot_bringup sensors.launch.py

# Full SLAM stack (saltybot-ros2 docker-compose service uses this):
ros2 launch saltybot_bringup slam.launch.py

# Individual drivers:
ros2 launch saltybot_bringup realsense.launch.py
ros2 launch saltybot_bringup rplidar.launch.py

---

Topic Reference

RPLIDAR A1M8

Topic	Type	Rate	Notes
/scan	sensor_msgs/LaserScan	~5.5 Hz	360°, 1440 pts/scan, 12m range

angle_min:  -π  (-180°)
angle_max:  +π  (+180°)
range_min:   0.15 m
range_max:  12.00 m
scan_time:  ~0.182 s
frame_id:   laser

Intel RealSense D435i

Topic	Type	Rate	Notes
/camera/color/image_raw	sensor_msgs/Image	15 Hz	RGB8, 640×480
/camera/color/camera_info	sensor_msgs/CameraInfo	15 Hz	Intrinsics
/camera/depth/image_rect_raw	sensor_msgs/Image	15 Hz	Z16, 640×480
/camera/depth/camera_info	sensor_msgs/CameraInfo	15 Hz	Intrinsics
/camera/aligned_depth_to_color/image_raw	sensor_msgs/Image	15 Hz	Depth in color frame
/camera/imu	sensor_msgs/Imu	~200 Hz	Accel + gyro fused (linear_interpolation)

TF Tree

map
└── odom                        (published by slam_toolbox once moving)
    └── base_link               (robot body frame)
        ├── laser               (RPLIDAR A1M8)  ← static, 10cm above base
        └── camera_link         (RealSense D435i) ← static, 5cm fwd, 15cm up
            ├── camera_depth_frame
            ├── camera_color_frame
            └── camera_imu_frame

Note: Static TF values in sensors.launch.py are placeholders. Update after physical mount with real measurements.

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Verification Commands

# List all active topics
ros2 topic list

# Check data rates
ros2 topic hz /scan
ros2 topic hz /camera/color/image_raw
ros2 topic hz /camera/imu

# Spot-check data
ros2 topic echo /scan --once
ros2 topic echo /camera/imu --once

# TF tree
ros2 run tf2_tools view_frames
ros2 run tf2_ros tf2_echo base_link laser

# SLAM map topic (after slam.launch.py)
ros2 topic hz /map
ros2 topic echo /map --no-arr   # metadata without raw data flood

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Troubleshooting

RPLIDAR not found

# Check udev symlink
ls -la /dev/rplidar
# If missing, fall back to:
ros2 launch saltybot_bringup rplidar.launch.py serial_port:=/dev/ttyUSB0
# Install udev rule (host, not container):
sudo cp /path/to/jetson/docs/99-saltybot.rules /etc/udev/rules.d/
sudo udevadm control --reload-rules && sudo udevadm trigger

RealSense not detected

# Check USB3 port (blue port on Nano)
lsusb | grep "8086:0b3a"
# Expected: Bus 002 Device 00X: ID 8086:0b3a Intel Corp. Intel RealSense D435i

# Install udev rules (host, not container):
sudo cp /etc/udev/rules.d/99-realsense-libusb.rules /etc/udev/rules.d/
sudo udevadm control --reload-rules && sudo udevadm trigger

IMU not publishing

# Verify enable_gyro and enable_accel are true
ros2 param get /camera/camera enable_gyro
ros2 param get /camera/camera enable_accel
# Check unite_imu_method (should be 2)
ros2 param get /camera/camera unite_imu_method