PART 1 AUDIT: Zero Leap Motion / UltraLeap references found in any
saltybot_* package. Existing gesture_node.py (saltybot_social) already
uses MediaPipe — no cleanup required.
PART 2 NEW PACKAGES:
saltybot_hand_tracking_msgs (ament_cmake)
- HandLandmarks.msg — 21 landmarks (float32[63]), handedness,
gesture label + direction, wrist position
- HandLandmarksArray.msg
saltybot_hand_tracking (ament_python)
- _hand_gestures.py — pure-Python gesture classifier (no ROS2/MP deps)
Vocabulary: stop (open palm) → pause/stop,
point (index up) → direction command + 8-compass,
disarm (fist) → emergency-off,
confirm (thumbs-up) → confirm action,
follow_me (peace sign) → follow mode,
greeting (wrist oscillation) → greeting response
WaveDetector: sliding-window lateral wrist tracking
- hand_tracking_node.py — ROS2 node
sub: /camera/color/image_raw (BEST_EFFORT)
pub: /saltybot/hands (HandLandmarksArray)
/saltybot/hand_gesture (std_msgs/String)
MediaPipe model_complexity=0 (lite) for 20+ FPS
on Orin Nano Super; background MP init thread;
per-hand WaveDetector instances
- test/test_hand_gestures.py — 35 tests, 35 passing
Covers: Landmark, HandGestureResult, WaveDetector, all 6 gesture
classifiers, priority ordering, direction vectors, confidence bounds
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.