sl-webui
57420807ca
UI (src/hooks/useCamera.js, src/components/CameraViewer.jsx):
- 7 camera sources: front/left/rear/right CSI, D435i RGB/depth, panoramic
- Compressed image subscription via rosbridge (sensor_msgs/CompressedImage)
- Client-side 15fps gate (drops excess frames, reduces JS pressure)
- Per-camera FPS indicator with quality badge (FULL/GOOD/LOW/NO SIGNAL)
- Detection overlays: face boxes + names (/social/faces/detections),
gesture icons (/social/gestures), scene object labels + hazard colours
(/social/scene/objects); overlay mode selector (off/faces/gestures/objects/all)
- 360° panoramic equirect viewer with mouse/touch drag azimuth pan
- Picture-in-picture: up to 3 pinned cameras via ⊕ button
- One-click recording (MediaRecorder → MP4/WebM download)
- Snapshot to PNG with detection overlay composite + timestamp watermark
- Cameras tab added to TELEMETRY group in App.jsx
Jetson (rosbridge bringup):
- rosbridge_params.yaml: whitelist + /camera/depth/image_rect_raw/compressed,
/camera/panoramic/compressed, /social/faces/detections,
/social/gestures, /social/scene/objects
- rosbridge.launch.py: D435i colour republisher (JPEG 75%) +
depth republisher (compressedDepth/PNG16 preserving uint16 values)
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.