sl-perception
2180b61440
Add saltybot_uwb_position — ROS2 Python package that reads JSON range
measurements from an ESP32 DW3000 UWB tag over USB serial, trilaterates
the robot's absolute position from 3+ fixed infrastructure anchors, and
publishes position + TF2 to the rest of the stack.
Serial protocol (one JSON line per frame):
Full frame: {"ts":…, "ranges": [{"id":0,"d_mm":1500,"rssi":-65}, …]}
Per-anchor: {"id":0, "d_mm":1500, "rssi":-65.0}
Accepts both "d_mm" and "range_mm" field names.
Trilateration (trilateration.py, numpy, no ROS deps):
Linear least-squares: linearise sphere equations around anchor 0,
solve (N-1)x2 (2D) or (N-1)x3 (3D) system via np.linalg.lstsq.
2D mode (default): robot_z fixed, needs >=3 anchors.
3D mode (solve_z=true): full 3D, needs >=4 anchors.
Outlier rejection:
After initial solve, compute per-anchor residual |r_meas - r_pred|.
Reject anchors with residual > outlier_threshold_m (0.4 m default).
Re-solve with inliers if >= min_anchors remain.
Track consecutive outlier strikes; flag in /status after N strikes.
Kalman filter (KalmanFilter3D, constant-velocity, 6-state, numpy):
Predict-only coasting when anchors drop below minimum.
Q=0.05, R=0.10 (tunable).
Topics:
/saltybot/uwb/pose PoseStamped 10 Hz Kalman-filtered position
/saltybot/uwb/range/<id> UwbRange on arrival, raw per-anchor ranges
/saltybot/uwb/status String/JSON 10 Hz state+residuals+flags
TF2: uwb_link -> map (identity rotation)
Anchor config: flat float arrays in YAML.
Default layout: 4-anchor 5x5m room at 2m height.
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.