sl-perception
0ecf341c57
Software-complete implementation of the two-anchor UWB ranging stack. All ROS2 / serial code written against an abstract interface so tests run without physical hardware (anchors on order). New message - UwbTarget.msg: valid, bearing_deg, distance_m, confidence, anchor0/1_dist_m, baseline_m, fix_quality (0=none 1=single 2=dual) Core library — _uwb_tracker.py (pure Python, no ROS2/runtime deps) - parse_frame(): ASCII RANGE,<id>,<tag>,<mm> protocol decoder - bearing_from_ranges(): law-of-cosines 2-anchor bearing with confidence (penalises extreme angles + close-range geometry) - bearing_single_anchor(): fallback bearing=0, conf≤0.3 - BearingKalman: 1-D constant-velocity Kalman filter [bearing, rate] - UwbRangingState: thread-safe per-anchor state + stale timeout + Kalman - AnchorSerialReader: background thread, readline() interface (real or mock) ROS2 node — uwb_node.py - Opens /dev/ttyUSB0 + /dev/ttyUSB1 (configurable) - Non-fatal serial open failure (will publish FIX_NONE until plugged in) - Publishes /saltybot/uwb_target at 10 Hz (configurable) - Graceful shutdown: stops reader threads Tests — test/test_uwb_tracker.py: 64/64 passing - Frame parsing: valid, malformed, STATUS, CR/LF, mm→m conversion - Bearing geometry: straight-ahead, ±45°, ±30°, symmetry, confidence - Kalman: seeding, smoothing, convergence, rate tracking - UwbRangingState: single/dual fix, stale timeout, thread safety - AnchorSerialReader: mock serial, bytes decode, stop() 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.