343e53081a
saltybot_uwb_logger_msgs (new package):
- AccuracyReport.msg: n_samples, mean/bias/std (x,y,2D), CEP50, CEP95,
RMSE, max_error, per-anchor range stats, test_id, duration_s
- StartAccuracyTest.srv: request (truth_x/y_m, n_samples, timeout_s,
test_id) → response (success, message, test_id)
saltybot_uwb_logger (new package):
- accuracy_stats.py: compute_stats() + RangeAccum — pure numpy, no ROS2
CEP50/CEP95 = 50th/95th percentile of 2-D error; bias, std, RMSE, max
- logger_node.py: /uwb_logger ROS2 node
Subscribes:
/saltybot/pose/fused → fused_pose_<DATE>.csv (ts, x, y, heading)
/saltybot/uwb/pose → uwb_pose_<DATE>.csv (ts, x, y)
/uwb/ranges → uwb_ranges_<DATE>.csv (ts, anchor_id, range_m,
raw_mm, rssi, tag_id)
Service /saltybot/uwb/start_accuracy_test:
Collects N fused-pose samples at known (truth_x, truth_y) in background
thread. On completion or timeout: publishes AccuracyReport on
/saltybot/uwb/accuracy_report + writes accuracy_<test_id>.json.
Per-anchor range stats included. CSV flushed every 5 s.
Tests: 16/16 passing (test/test_accuracy_stats.py, no ROS2/hardware)
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.