sl-jetson ce6d5ee249
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feat(social): multi-camera gesture recognition — MediaPipe Hands + Pose (Issue #140)
Delivers Issue #140 (P2): real-time gesture detection from 4 CSI cameras via
MediaPipe Hands and Pose, publishing classified gestures on /social/gestures.

New files:
- saltybot_social_msgs/msg/Gesture.msg + GestureArray.msg — ROS2 message types
- saltybot_social/gesture_classifier.py — pure-Python geometric classifier
  (stop_palm, thumbs_up/down, point, come_here, follow, wave, arms_up,
   arms_spread, crouch); WaveDetector temporal sliding-window oscillation tracker
- saltybot_social/gesture_node.py — ROS2 node; round-robin multi-camera
  _FrameBuffer, lazy MediaPipe init, person-ID correlation via PersonState
- saltybot_social/test/test_gesture_classifier.py — 70 unit tests, all passing
- saltybot_social/config/gesture_params.yaml — tuned defaults for Orin Nano
- saltybot_social/launch/gesture.launch.py — all params overridable at launch

Modified:
- saltybot_social_msgs/CMakeLists.txt — register Gesture + GestureArray msgs
- saltybot_social/setup.py — add gesture_node console_scripts entry point

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-02 10:10:54 -05:00
..

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

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.