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- SQLite database at /home/seb/saltybot-data/social_memory.db - Tables: persons (name, embeddings, relationship_tier, notes), encounters (person_id, timestamp, transcript, mood) - ROS2 services: /saltybot/social_memory/lookup, /update, /encounter, /stats - Automatic tier promotion by encounter count (5→regular, 20→favorite) - Quality-based promotion: 80%+ positive interactions required - Custom greetings per relationship tier (stranger/regular/favorite) - Encounter tracking: transcript, mood, engagement_score, positive_interaction flag - Face embedding storage support for face recognition integration - Relationship score computation from interaction history - Thread-safe concurrent service calls - Periodic stats publishing on /saltybot/social_memory/stats_update - Backup/restore functionality with gzip compression - Full database statistics: person counts by tier, total encounters, database size - Configurable via social_memory.yaml: thresholds, backup dir, publish interval Two packages: - saltybot_social_memory: Service definitions (CMake, ROS2 services) - saltybot_social_memory_node: Python service server with SQLite backend 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.