dd13569413
Add saltybot_phone/mqtt_ros2_bridge_node.py — ROS2 node bridging the three
MQTT topics published by phone/sensor_dashboard.py into typed ROS2 messages:
saltybot/phone/imu → /saltybot/phone/imu sensor_msgs/Imu
saltybot/phone/gps → /saltybot/phone/gps sensor_msgs/NavSatFix
saltybot/phone/battery → /saltybot/phone/battery sensor_msgs/BatteryState
(status) → /saltybot/phone/bridge/status std_msgs/String
Key design:
- paho-mqtt loop_start() runs in dedicated network thread; on_message
enqueues (topic, payload) pairs into a thread-safe queue
- ROS2 timer drains queue at 50 Hz — all publishing stays on executor
thread, avoiding any rclpy threading concerns
- Timestamp alignment: uses ROS2 wall clock by default; opt-in
use_phone_timestamp param uses phone epoch ts when drift < warn_drift_s
- IMU: populates accel + gyro with diagonal covariance; orientation_cov[0]=-1
(unknown per REP-145)
- GPS: NavSatStatus.STATUS_FIX for gps/fused/network providers; full 3×3
position covariance from accuracy_m; COVARIANCE_TYPE_APPROXIMATED
- Battery: pct→percentage [0-1], temp Kelvin, health/status mapped from
Android health strings, voltage/current=NaN (unavailable on Android)
- Input validation: finite value checks on IMU, lat/lon range on GPS,
pct [0-100] on battery; bad messages logged at DEBUG and counted
- Status topic at 0.2 Hz: JSON {mqtt_connected, rx/pub/err counts,
age_s per sensor, queue_depth}
- Auto-reconnect via paho reconnect_delay_set (5 s → 20 s max)
Add launch/mqtt_bridge.launch.py with args: mqtt_host, mqtt_port,
reconnect_delay_s, use_phone_timestamp, warn_drift_s, imu_accel_cov,
imu_gyro_cov.
Register mqtt_ros2_bridge console script in setup.py.
Add python3-paho-mqtt exec_depend to package.xml.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Jetson Nano — AI/SLAM Platform Setup
Self-balancing robot: Jetson Nano dev environment for ROS2 Humble + SLAM stack.
Stack
| Component | Version / Part |
|---|---|
| Platform | Jetson Nano 4GB |
| JetPack | 4.6 (L4T R32.6.1, CUDA 10.2) |
| ROS2 | Humble Hawksbill |
| DDS | CycloneDDS |
| SLAM | slam_toolbox |
| Nav | Nav2 |
| Depth camera | Intel RealSense D435i |
| LiDAR | RPLIDAR A1M8 |
| MCU bridge | STM32F722 (USB CDC @ 921600) |
Quick Start
# 1. Host setup (once, on fresh JetPack 4.6)
sudo bash scripts/setup-jetson.sh
# 2. Build Docker image
bash scripts/build-and-run.sh build
# 3. Start full stack
bash scripts/build-and-run.sh up
# 4. Open ROS2 shell
bash scripts/build-and-run.sh shell
Docs
docs/pinout.md— GPIO/I2C/UART pinout for all peripheralsdocs/power-budget.md— 10W power envelope analysis
Files
jetson/
├── Dockerfile # L4T base + ROS2 Humble + SLAM packages
├── docker-compose.yml # Multi-service stack (ROS2, RPLIDAR, D435i, STM32)
├── README.md # This file
├── docs/
│ ├── pinout.md # GPIO/I2C/UART pinout reference
│ └── power-budget.md # Power budget analysis (10W envelope)
└── scripts/
├── entrypoint.sh # Docker container entrypoint
├── setup-jetson.sh # Host setup (udev, Docker, nvpmodel)
└── build-and-run.sh # Build/run helper
Power Budget (Summary)
| Scenario | Total |
|---|---|
| Idle | 2.9W |
| Nominal (SLAM active) | ~10.2W |
| Peak | 15.4W |
Target: 10W (MAXN nvpmodel). Use RPLIDAR standby + 640p D435i for compliance.
See docs/power-budget.md for full analysis.