sl-firmware f5877756d5 feat: Map save/load service for SLAM Toolbox persistence (Issue #480)
Implement automatic map serialization and persistence for slam_toolbox:
- New SlamToolboxPersistenceNode with auto-save every 5 minutes
- Auto-load most recent map on startup
- Services: /saltybot/save_map, /saltybot/load_map, /saltybot/list_maps
- Export to Nav2-compatible YAML + PGM format
- Stores maps in ~/.saltybot-data/maps/ with .posegraph format
- Integrates with slam_toolbox serialize/deserialize services

Changes:
- Created saltybot_mapping/slam_toolbox_persistence.py
- Added slam_toolbox_persistence.launch.py
- Updated slam.launch.py to include persistence service
- Updated CMakeLists.txt to install new executable
- Added slam_toolbox dependency to package.xml

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
2026-03-05 14:46:33 -05:00
..

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

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.