sl-webui
2ba8df17fd
- 2D occupancy grid (100x100 cells @ 10cm resolution, configurable) - LIDAR integration: subscribes to /scan and /odom for real-time obstacle detection - Ray-casting: marks hit points as obstacles, intermediate points as free space - Cell states: unknown/free/obstacle/hazard with confidence tracking (0.0–1.0) - Hazard classification: 3+ detections = permanent hazard (stays in memory) - Temporal decay: 95%/day for hazards (30-day half-life), 85%/day for obstacles (~21-day) - Decay interval: applied hourly, cells revert to free when confidence < 20% - Persistence: auto-saves to /home/seb/saltybot-data/obstacle_map.yaml every 5 minutes - YAML format: grid metadata + cell array with state/confidence/detection_count/timestamp - OccupancyGrid publisher: /saltybot/obstacle_map for Nav2 integration at 5 Hz - Thread-safe: all grid operations protected with locks for concurrent callbacks - Statistics: hazard/obstacle/free cell counts and coverage percentage - Dashboard overlay ready: color-coded cells (red=hazard, orange=obstacle, gray=free) - Configurable via obstacle_memory.yaml: grid size/resolution, range limits, decay rates Co-Authored-By: Claude Haiku 4.5 <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.