Phone side — phone/video_bridge.py: - MJPEG streaming server for Android/Termux phone camera - Dual camera backends: OpenCV VideoCapture (V4L2) with automatic fallback to termux-camera-photo for unmodified Android - WebSocket server (ws://0.0.0.0:8765) — binary JPEG frames + JSON info/error control messages; supports multiple concurrent clients - HTTP server (http://0.0.0.0:8766): /stream — multipart/x-mixed-replace MJPEG /snapshot — single JPEG /health — JSON stats (frame count, dropped, resolution, fps) - Thread-safe single-slot FrameBuffer; CaptureThread rate-limited with wall-clock accounting for capture latency - Flags: --ws-port, --http-port, --width, --height, --fps, --quality, --device, --camera-id, --no-http, --debug Jetson side — saltybot_phone/phone_camera_node.py: - ROS2 node: receives JPEG frames, publishes: /saltybot/phone/camera sensor_msgs/Image (bgr8) /saltybot/phone/camera/compressed sensor_msgs/CompressedImage /saltybot/phone/camera/info std_msgs/String (stream metadata) - WebSocket client (primary); HTTP MJPEG polling fallback on WS failure - Auto-reconnect loop (default 3 s) for both transports - Latency warning when frame age > latency_warn_ms (default 200 ms) - 10 s diagnostics log: received/published counts + last frame age - Registered as phone_camera_node console script in setup.py - Added to phone_bringup.py launch with phone_host / phone_cam_enabled args 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.