History

sl-jetson a9b2242a2c feat(social): Orin dev environment — JetPack 6 + TRT conversion + systemd (#88 )

- Dockerfile.social: social-bot container with faster-whisper, llama-cpp-python
  (CUDA), piper-tts, insightface, pyannote.audio, OpenWakeWord, pyaudio
- scripts/convert_models.sh: TRT FP16 conversion for SCRFD-10GF, ArcFace-R100,
  ECAPA-TDNN; CTranslate2 setup for Whisper; Piper voice download; benchmark suite
- config/asound.conf: ALSA USB mic (card1) + USB speaker (card2) config
- models/README.md: version-pinned model table, /models/ layout, perf targets
- systemd/: saltybot-social.service + saltybot.target + install_systemd.sh
- docker-compose.yml: saltybot-social service with GPU, audio device passthrough,
  NVMe volume mounts for /models and /social_db

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

2026-03-02 08:08:57 -05:00

config

feat(social): Orin dev environment — JetPack 6 + TRT conversion + systemd (#88 )

2026-03-02 08:08:57 -05:00

docs

feat: Orin Nano Super platform update + 4x IMX219 CSI cameras

2026-02-28 22:59:13 -05:00

models

feat(social): Orin dev environment — JetPack 6 + TRT conversion + systemd (#88 )

2026-03-02 08:08:57 -05:00

ros2_ws/src

feat(social): multi-modal tracking fusion — UWB+camera Kalman filter (Issue #92 )

2026-03-01 23:59:10 -05:00

scripts

feat(social): Orin dev environment — JetPack 6 + TRT conversion + systemd (#88 )

2026-03-02 08:08:57 -05:00

systemd

feat(social): Orin dev environment — JetPack 6 + TRT conversion + systemd (#88 )

2026-03-02 08:08:57 -05:00

docker-compose.yml

feat(social): Orin dev environment — JetPack 6 + TRT conversion + systemd (#88 )

2026-03-02 08:08:57 -05:00

Dockerfile

feat: update SLAM stack for Jetson Orin Nano Super (67 TOPS, JetPack 6)

2026-02-28 21:46:27 -05:00

Dockerfile.social

feat(social): Orin dev environment — JetPack 6 + TRT conversion + systemd (#88 )

2026-03-02 08:08:57 -05:00

README.md

feat: Jetson Nano platform setup and Docker env (bd-1hcg)

2026-02-28 12:46:14 -05:00

README.md

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 peripherals
docs/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.