sl-jetson c3d36e9943
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feat(social): face-tracking head servo controller — Issue #279
Adds face_track_servo_node to saltybot_social:
- Subscribes /social/faces/detected (FaceDetectionArray)
- Picks closest face by largest bbox area (proximity proxy)
- Computes pan/tilt error from bbox centre vs image centre using
  configurable FOV (fov_h_deg=60°, fov_v_deg=45°)
- Independent PID controllers for pan and tilt (velocity/incremental
  output with anti-windup); servo position integrates velocity*dt
- Clamps commands to ±pan_limit_deg / ±tilt_limit_deg
- Returns to centre at return_rate_deg_s when face lost >lost_timeout_s
- Dead zone suppresses jitter for small errors
- Publishes Float32 on /saltybot/head_pan and /saltybot/head_tilt
- 81/81 tests passing

Closes #279
2026-03-02 17:38:02 -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.