sl-jetson
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Add saltybot_social_tests package with full pytest + launch_testing harness: - test_launch.py: start social_test.launch.py, verify all nodes up within 30s - test_topic_rates.py: measure topic Hz over 3s window vs. minimum SLAs - test_services.py: /social/enroll, /social/nav/set_mode, person CRUD, mood query - test_gpu_memory.py: total allocation < 6 GB, no leak over 30s - test_latency.py: inject→transcript→LLM→TTS state-machine SLA profiling - test_shutdown.py: no zombies, GPU memory released, audio device freed - test_helpers.py: TopicRateChecker, NodeChecker, ServiceChecker, GpuMemoryChecker - mock_sensors.py: camera/faces/fused/persons/uwb publishers at correct rates - social_test.launch.py: CI-mode launch (no mic/speaker, mock sensors auto-started) - conftest.py + pytest.ini: gpu_required / full_stack / stack_running markers - docker/Dockerfile.ci + docker-compose.ci.yml: CPU-only CI container - docker/entrypoint-ci.sh: launch stack + wait 10s + run pytest - bags/record_social_test.sh + bags/README.md: rosbag recording for replay - .gitea/workflows/social-tests-ci.yml: lint + core-tests + latency-gpu jobs 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.