sl-controls
570ebd3d22
Implement magnetometer-based heading calculation with tilt compensation and magnetic declination correction for France (1.5° east). Features: - Tilt-compensated heading using quaternion-based orientation Roll and pitch compensation for uneven terrain - Magnetic declination correction: 1.5° for France - Heading normalization to 0-360 degree range - Publishes both Float64 (degrees) and quaternion representations - 10Hz publishing frequency with configurable parameters Algorithm: - Subscribe to IMU (quaternion orientation) and magnetometer data - Convert quaternion to roll/pitch/yaw for tilt compensation - Project magnetometer vector onto horizontal plane using trig functions - Apply declination correction and normalize heading - Publish heading as Float64 degrees and quaternion (Z-axis rotation only) Test Coverage: - 30+ unit tests covering: - Node initialization and parameters - Quaternion to Euler conversion (identity, 90° rotations) - Heading quaternion creation (0°, 90°, 180°, custom angles) - Tilt-compensated heading with roll, pitch, combined tilts - Declination correction application - Sensor subscription handlers - Heading angle normalization and wrapping - Realistic scenarios (level, tilted uphill/sideways, 3D tilt, weak signal, continuous rotation) Topics: - Subscribed: /saltybot/imu/data (Imu), /saltybot/mag (MagneticField) - Published: /saltybot/heading (Float64), /saltybot/heading_quaternion (QuaternionStamped) Config: frequency=10Hz, declination_deg=1.5 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.