sl-jetson
2d144f5bcc
Master saltybot_bringup.launch.py with: - Profile support (full/minimal/headless) for flexible deployments - Boot order: hardware → perception → control → social → monitoring - Dependency-ordered launch with 30-second boot timeout - Consolidated saltybot_params.yaml with all stack parameters - Stack state publisher (/saltybot/stack_state) - Post-launch diagnostics self-test - Graceful shutdown support (motors first) Boot sequence (Issue #447): - t=0s: hardware (robot description, STM32 bridge) - t=2-6s: perception (sensors, cameras, detection, SLAM) - t=2-14s: control (cmd_vel bridge, follower, Nav2) - t=17-19s: social & monitoring (rosbridge, stack state) Features: - full profile: complete stack (SLAM, Nav2, detection, follower) - minimal profile: hardware + control only - headless profile: sensors + control (no CSI cameras) - Configurable modes: indoor (SLAM+Nav2), outdoor (GPS nav), follow Parameters consolidated in config/saltybot_params.yaml: - Hardware (bridge, motors) - Perception (sensors, detection, SLAM) - Control (follower, Nav2) - Social (TTS, gestures, face tracking) - Monitoring (rosbridge, health checks) New: stack_state_monitor_node.py (publishes stack boot state) 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.