sl-webui d10c385bdc feat: Add Issue #429 - Emotion engine with context-aware face expression selection
- ROS2 node subscribing to orchestrator state, battery, balance, person tracker, voice commands, health
- State-to-emotion mapping: navigation → excited, social → happy/curious, low battery → concerned, etc.
- Smooth emotion transitions (0.3–1.2s) with confidence tracking
- Idle behaviors: blink (~3s), look-around (~8s), breathing (sine wave)
- Social memory: familiarity-based warmth modifier (0.3–1.0) for known people
- Personality-aware responses: extroversion, playfulness, responsiveness, anxiety (0.0–1.0 configurable)
- Publishes /saltybot/emotion_state (JSON): emotion, intensity, confidence, expression name, context, idle_flags
- Configurable via emotion_engine.yaml: personality traits, battery thresholds, update rate
- Launch file: emotion_engine.launch.py

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
2026-03-05 08:53:42 -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.